AcqKnowledge 5 Software Guide Acq Knowledge

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AcqKnowledge 5 Software Guide
®

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For Life Science Research Applications
Data Acquisition and Analysis with BIOPAC Hardware Systems

Reference Manual for
AcqKnowledge 5.0.3 Software & MP160/MP150/MP36R, BioHarness, Mobita, Stellar, BioNomadix,
BioNomadix Logger, BioNomadix Smart Center Hardware/Firmware
on Windows® 10, 8.x, and 7 or Mac OS 10.10-10.13
®

42 Aero Camino, Goleta, CA 93117
Tel (805) 685-0066 | Fax (805) 685-0067
info@biopac.com | www.biopac.com

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AcqKnowledge 5 Software Guide

TABLE OF CONTENTS
PREFACE TO ACQKNOWLEDGE SOFTWARE GUIDE .................................................. 15
Welcome .......................................................................................................................................................... 15
Supported Platforms ......................................................................................................................................... 15
What’s new for AcqKnowledge 5.0.3 ................................................................................................................ 16
Using this Manual............................................................................................................................................. 16
User Support System ........................................................................................................................................ 17
Where do I find help? ....................................................................................................................................... 18

PART A — GETTING STARTED ....................................................................................... 21
Chapter 1 MP Systems Overview ......................................................................................................................... 21
MP36R support ................................................................................................................................................ 22
MP System Requirements ................................................................................................................................. 22
Automator Integration and Scripting Support .................................................................................................... 23
MP System with AcqKnowledge Features ......................................................................................................... 24
Application Notes ............................................................................................................................................. 25
Application Features ......................................................................................................................................... 26
Chapter 2 AcqKnowledge Overview ..................................................................................................................... 27
Launching the AcqKnowledge software ............................................................................................................ 28
Setting up channels using Module Setup (MP160 and MP150 Hardware) .......................................................... 30
Setting up channels manually ............................................................................................................................ 30
Basic Analog Channel Information ................................................................................................................... 31
Basic Digital Channel Information .................................................................................................................... 31
Basic Calculation Channel Information ............................................................................................................. 31
Selecting Hardware........................................................................................................................................... 31
Setting Up Acquisitions .................................................................................................................................... 32
Starting an Acquisition ..................................................................................................................................... 33
Stopping an Acquisition .................................................................................................................................... 33
Display Modes.................................................................................................................................................. 34
Playback Mode (Replay) ................................................................................................................................... 39
Data Views ....................................................................................................................................................... 41
Analysis ........................................................................................................................................................... 42
Selecting a waveform........................................................................................................................................ 44
Show/Hide Channel .......................................................................................................................................... 44
Collapsing Channels ......................................................................................................................................... 45
Zoom ............................................................................................................................................................... 46
Select an area.................................................................................................................................................... 46
Keyboard data selection .................................................................................................................................... 46
Transform data ................................................................................................................................................. 47
Measurements .................................................................................................................................................. 47
Events (Markers) .............................................................................................................................................. 48
Grids ................................................................................................................................................................ 48
Horizontal Split View ....................................................................................................................................... 48
Autoscroll Horizontal Axis Controls ................................................................................................................. 49
Journals ............................................................................................................................................................ 50
Saving data ....................................................................................................................................................... 50
Format change warnings ..................................................................................................................................... 50
“Data Snapshot” — Embedded Archive ............................................................................................................ 51
Print ................................................................................................................................................................. 52

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AcqKnowledge with BioNomadix Smart Center ................................................................................................ 53
Chapter 3

User Interface & Context Menu Features ........................................................................................... 56

Toolbars ..................................................................................................................................................................... 57
Main, Display and Scaling Toolbars .................................................................................................................. 58
Hardware Toolbar ............................................................................................................................................. 58
Cursor Toolbar ................................................................................................................................................. 58
Selection Palette ............................................................................................................................................... 62
Start/Stop Toolbar............................................................................................................................................. 62
Channel Button Toolbar .................................................................................................................................... 63
Event Toolbar ................................................................................................................................................... 63
Focus Area Toolbar .......................................................................................................................................... 63
Measurements Toolbar ...................................................................................................................................... 63
Custom Toolbars for Transformations and Analysis........................................................................................... 63
Toolbar Position Retention and Changes ........................................................................................................... 64
Axis Controls.................................................................................................................................................... 64
Enable Cursor Tools During Acquisitions.......................................................................................................... 65
Button Transparency ......................................................................................................................................... 65
Customizable Chart Track Dividers ................................................................................................................... 65
Plotting Background Colors .............................................................................................................................. 65
Spectrum Analyzer Palette ................................................................................................................................ 65
Keyboard Shortcuts........................................................................................................................................... 65
Tooltips ............................................................................................................................................................ 69
Mouse Controls ................................................................................................................................................ 70
Mouse Scrollwheel Support .............................................................................................................................. 70
Modification History......................................................................................................................................... 71
Cancelling Transformations and Transformation Progress Bar ........................................................................... 71
Typed Event Label Drawing Improvements....................................................................................................... 72
Choose MP160 and MP150 Help Button ........................................................................................................... 72
Tooltips ...................................................................................................................................................................... 72
Channel Label, Units Length and Tooltips ......................................................................................................... 72
Graph Window Tooltip Improvements .............................................................................................................. 72
Menu Item Tooltips .......................................................................................................................................... 72
Chapter 4 Editing and Analysis Features ............................................................................................................. 73
Scroll bars ........................................................................................................................................................ 73
Scaling ............................................................................................................................................................. 74
Horizontal axis.................................................................................................................................................... 74
Vertical (Amplitude) axis .................................................................................................................................... 76
Range Guide (MP36R Hardware only) ................................................................................................................ 77
Adaptive Scaling............................................................................................................................................... 78
Show Textual Value Display ............................................................................................................................. 78
Grid Details ...................................................................................................................................................... 80
Grid Options ....................................................................................................................................................... 83
Journal Details .................................................................................................................................................. 85
Journal Contextual Menu .................................................................................................................................. 85
Rich Journals ...................................................................................................................................................... 86
Journal Toolbar Buttons ...................................................................................................................................... 86
Journal Numerical Table Tools ............................................................................................................................ 87
Example of Sum, Mean or Standard .................................................................................................................... 88
Example of Evaluate Expression ......................................................................................................................... 89
Adding a hyperlink to the Journal ........................................................................................................................ 89
Embedding PDFs in Journals............................................................................................................................... 90
Select a waveform / channel ................................................................................................................................ 91
Channel Labels ................................................................................................................................................. 91
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Show/Hide Channel .......................................................................................................................................... 92
Focus Areas...................................................................................................................................................... 92
Creating Focus Areas........................................................................................................................................ 92
Focus Areas in Specialized Analysis ................................................................................................................. 93
Printing Focus Areas......................................................................................................................................... 93
Measurements .................................................................................................................................................. 94
Measurement Display ......................................................................................................................................... 94
Measurement Area .............................................................................................................................................. 95
Measurements and Measurement Presets ............................................................................................................. 97
Measurement Validation ..................................................................................................................................... 97
Measurement Info / Parameters ........................................................................................................................... 97
Measurement Interpolation.................................................................................................................................. 97
Exporting measurements ..................................................................................................................................... 97

PART B—ACQUISITION FUNCTIONS: THE HARDWARE MENU ................................ 109
Overview........................................................................................................................................................ 109
Set Up Data Acquisition > Data Acquisition Settings ...................................................................................... 110
Chapter 5

Set Up Channels ................................................................................................................................ 112

Set Up Channels—The Basics ................................................................................................................................. 112
Module-based analog channel setup ................................................................................................................ 112
View by Channels........................................................................................................................................... 114
Set Up Channels—Advanced .................................................................................................................................. 117
Analog channels ............................................................................................................................................. 117
Increased Channel Count Support ................................................................................................................... 118
Analog channels MP36R ................................................................................................................................ 119
Offset ............................................................................................................................................................. 119
Adjustable, user defined, digital IIR filters for MP36R .................................................................................... 120
High Pass Filters MP36R ................................................................................................................................ 120
Additional controls in MP36R Input Channel Parameters ................................................................................ 121
MP36R Advanced Preset Settings ................................................................................................................... 121
MP36R Transducer SSID Table ...................................................................................................................... 122
Calculation Channels ...................................................................................................................................... 129
Metachannel ................................................................................................................................................... 130
Chapter 6 Calculation Channel Presets .............................................................................................................. 133
Integrate Calculation ......................................................................................................................................... 134
Smoothing Calculation ...................................................................................................................................... 139
Rate Calculation ............................................................................................................................................... 141
Signal Parameters Tab ...................................................................................................................................... 142
Output Tab ....................................................................................................................................................... 143
Function Calculation ......................................................................................................................................... 145
Filter IIR Calculation ........................................................................................................................................ 146
Expression ........................................................................................................................................................ 148
Delay Calculation ............................................................................................................................................. 155
Fourier Linear Combiners: FLC, WFLC, CWFLC Calculations ......................................................................... 160
Basic FLC ........................................................................................................................................................ 160
Weighted-Frequency FLC ................................................................................................................................. 160
Coupled WFLC/FLC ........................................................................................................................................ 160
Adaptive Filtering Calculation .......................................................................................................................... 161
Comb Band Stop Filter Calculation ................................................................................................................... 161
Metachannel ..................................................................................................................................................... 161
Rescale Calculation........................................................................................................................................... 162
Slew Rate Limiter ............................................................................................................................................. 163

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Filter - FIR........................................................................................................................................................ 164
Chapter 7
Data Acquisition ............................................................................................................................... 165
Data Acquisition—The Basics ........................................................................................................................ 165
Multiple Hardware ............................................................................................................................................ 168
Averaging (MP160 and MP150 Hardware only) .............................................................................................. 169
Overview .......................................................................................................................................................... 169
Averaging Setup ............................................................................................................................................... 171
Advanced Averaging—P300 ............................................................................................................................. 172
Repeating.......................................................................................................................................................... 174
Starting an acquisition..................................................................................................................................... 176
Stopping an Acquisition .................................................................................................................................. 176
Rewind ........................................................................................................................................................... 176
Saving acquisition data ................................................................................................................................... 176
Timers (Stop watches and Elapsed timers)....................................................................................................... 177
Timer Types ................................................................................................................................................... 177
Electrode Checker........................................................................................................................................... 179
Chapter 8 Set Up Triggering ............................................................................................................................... 180
Digital Triggers (MP160 and MP150) ............................................................................................................. 180
Analog Triggers .............................................................................................................................................. 181
Chapter 9 Set Up Stimulator .............................................................................................................................. 183
Analog Output for MP160 and MP150 Users................................................................................................... 187
Dual Stimulation ............................................................................................................................................. 188
Square waves .................................................................................................................................................. 189
Tone Stimuli ................................................................................................................................................... 190
Ramp Waves .................................................................................................................................................. 190
Arbitrary Waveform ....................................................................................................................................... 191
MP160/150 Stimulator Sample Rates .............................................................................................................. 192
Analog Output Upper Limits Summary ........................................................................................................... 195
Chapter 10
Output Control ............................................................................................................................... 196
CH# to Output ................................................................................................................................................ 198
MP36R Input > Output Scaling ....................................................................................................................... 199
Digital Outputs Control ................................................................................................................................... 200
Pulses Output Control ..................................................................................................................................... 201
Stimulator – BSLSTM Output Control ............................................................................................................ 201
Stimulator – Low Voltage Output Control ....................................................................................................... 201
Stimulator Human Stimulator (STMHUM) Output Control.............................................................................. 201
Pulse Sequence Output Control ....................................................................................................................... 203
Visual Stim Controllable LED – OUT4 Output Control ................................................................................... 207
Arbitrary Wave Output ................................................................................................................................... 208
Sound Sequence Output Control...................................................................................................................... 210
Pulse Definitions............................................................................................................................................. 212
Output Control Panel Descriptions .................................................................................................................. 212
Usage Guidelines & Setup Summary for BSLSTM Output Control .................................................................. 222
Chapter 11
Set Up Event Marking ................................................................................................................... 224
Events (Markers) ............................................................................................................................................ 224
Event (Marker) Overview.................................................................................................................................. 224
Event Toolbar ................................................................................................................................................... 225
Event Tooltips................................................................................................................................................... 225
Preferences for Events....................................................................................................................................... 225
Event Marking Setup Options............................................................................................................................ 227
Create/Toggle Focus Area Action ...................................................................................................................... 228
Event Palette ..................................................................................................................................................... 229
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Audio ............................................................................................................................................................... 233
Event Type Options .......................................................................................................................................... 234
Printing Events ................................................................................................................................................. 239
Events and Waveform Editing........................................................................................................................... 239
Constructing Graph Selections from Events....................................................................................................... 240
Event Plotting and Variable Sampling Rate ....................................................................................................... 240
Chapter 12
Other Hardware Menu Commands .............................................................................................. 241
Show Input Values.......................................................................................................................................... 241
Manual Control (MP160 and MP150 only) ...................................................................................................... 242
Set Up Linked Acquisitions ............................................................................................................................ 244
Configuring New or Open Graphs for Linked Acquisitions.............................................................................. 244
Linked Acquisitions Preferences ..................................................................................................................... 247
Limitations on Linked Acquisitions synchronization methods.......................................................................... 247
Incompatible Acquisition Mode Warning ........................................................................................................ 247
Manage Hardware Connections....................................................................................................................... 249
MP160 or MP150 Info .................................................................................................................................... 250
Segment Labels .............................................................................................................................................. 250
Sound Feedback ............................................................................................................................................. 250
Gauge............................................................................................................................................................. 252
Gauge Preferences ............................................................................................................................................ 252
Segment Timer “Stopwatch” option .................................................................................................................. 255
Autoplotting, Scrolling and Sweep Display Modes .......................................................................................... 256
Warn on Overwrite ......................................................................................................................................... 257
Organize Channel Presets ............................................................................................................................... 257

PART C—ANALYSIS FUNCTIONS ................................................................................. 259
Toolbars ........................................................................................................................................................... 259
Shortcuts .......................................................................................................................................................... 259
Analysis Shortcuts ............................................................................................................................................ 260
New ............................................................................................................................................................... 262
Graph Window ................................................................................................................................................. 262
New > Graph-specific Journal ........................................................................................................................... 262
New > Independent Journal ............................................................................................................................... 262
New > Data View ............................................................................................................................................. 262
New > Batch Acquisition .................................................................................................................................. 263
Batch Errors ..................................................................................................................................................... 263
Open .............................................................................................................................................................. 265
Open Recent ................................................................................................................................................... 271
Open Sample Data File ................................................................................................................................... 271
Open for Playback .......................................................................................................................................... 271
SMI BeGaze Import........................................................................................................................................ 271
Importing SMI Begaze Data into AcqKnowledge ............................................................................................ 272
Using the Software Timestamps Option to Align Data ..................................................................................... 272
Dataquest Import ............................................................................................................................................ 272
Dataquest Import ............................................................................................................................................ 274
Close .............................................................................................................................................................. 274
Save ............................................................................................................................................................... 275
Save As .......................................................................................................................................................... 275
Save Selection As ........................................................................................................................................... 281
Save Journal Text As ...................................................................................................................................... 282
File Format prompts.......................................................................................................................................... 282
Send Email Attachment .................................................................................................................................. 283
Copy to Dropbox – Open from Dropbox ......................................................................................................... 283
Page setup ...................................................................................................................................................... 284

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Print ............................................................................................................................................................... 284
Go to Startup Wizard ...................................................................................................................................... 285
Quit ................................................................................................................................................................ 285

Chapter 14
Edit Menu Commands ................................................................................................................... 286
Undo / Can’t undo .......................................................................................................................................... 287
Cut ................................................................................................................................................................. 287
Copy............................................................................................................................................................... 288
Paste ............................................................................................................................................................... 288
Clear............................................................................................................................................................... 288
Clear all .......................................................................................................................................................... 288
Select All ........................................................................................................................................................ 289
Insert waveform .............................................................................................................................................. 289
Duplicate waveform ........................................................................................................................................ 289
Remove waveform .......................................................................................................................................... 289
Remove last appended segment ....................................................................................................................... 289
Create Data Snapshot ...................................................................................................................................... 289
Merge Graphs ................................................................................................................................................. 290
Merging graphs as data segments .................................................................................................................... 291
Clipboard........................................................................................................................................................ 291
Journal............................................................................................................................................................ 293
Chapter 15
Transform Menu Commands ......................................................................................................... 296
Recently Used Transformations....................................................................................................................... 297
Digital Filters.................................................................................................................................................. 297
FIR Filters ........................................................................................................................................................ 300
Digital filter dialog............................................................................................................................................ 300
IIR Filters ......................................................................................................................................................... 302
Adaptive Filtering ............................................................................................................................................. 303
Comb Band Stop Filter...................................................................................................................................... 303
Fourier Linear Combiners ............................................................................................................................... 306
Basic FLC......................................................................................................................................................... 306
Weighted-Frequency FLC ................................................................................................................................. 306
Math Functions ............................................................................................................................................... 308
Template Functions......................................................................................................................................... 310
Set Template ..................................................................................................................................................... 310
Remove mean ................................................................................................................................................... 311
Template algorithms ......................................................................................................................................... 312
Adaptive Template Matching ............................................................................................................................ 314
Integral ........................................................................................................................................................... 315
Derivative ....................................................................................................................................................... 316
Integrate ......................................................................................................................................................... 317
Output Reset ..................................................................................................................................................... 317
Smoothing ...................................................................................................................................................... 320
Difference....................................................................................................................................................... 321
Resample ........................................................................................................................................................ 322
Resample Graph................................................................................................................................................ 322
Resample Waveform ......................................................................................................................................... 322
Expression ...................................................................................................................................................... 323
Delay.............................................................................................................................................................. 323
Rescale ........................................................................................................................................................... 324
Waveform Math.............................................................................................................................................. 324
Slew Rate Limiter ........................................................................................................................................... 325
Chapter 16
Analysis Menu Commands ............................................................................................................. 327
Histogram ....................................................................................................................................................... 327
Autoregressive Modeling ................................................................................................................................ 328
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Nonlinear Modeling........................................................................................................................................ 329
Power Spectral Density................................................................................................................................... 331
AR Time-Frequency Analysis ......................................................................................................................... 332
FFT Fast Fourier Transformation .................................................................................................................... 333
Inverse FFT ...................................................................................................................................................... 336
DWT/SWT ..................................................................................................................................................... 338
Inverse DWT .................................................................................................................................................. 338
Principal Component Analysis ........................................................................................................................ 339
Inverse PCA ..................................................................................................................................................... 339
Independent Component Analysis ................................................................................................................... 339
Inverse ICA ...................................................................................................................................................... 340
Find Cycle (Peak Detector) ............................................................................................................................. 341
Cycles/Peaks tab ............................................................................................................................................... 341
Find Next Cycle.............................................................................................................................................. 342
Find All Cycles in Graph ................................................................................................................................ 342
Find in Selected Area...................................................................................................................................... 342
Find All Cycles in Focus Areas ....................................................................................................................... 342
Find First Cycle .............................................................................................................................................. 342
Preview (Selection tab) ................................................................................................................................... 342
Find Cycle definitions..................................................................................................................................... 342
Selection tab ..................................................................................................................................................... 345
Output tab......................................................................................................................................................... 346
Output Measurements ....................................................................................................................................... 346
Output: Averaging—Offline ............................................................................................................................. 347
Output 3D Surface ............................................................................................................................................ 348
Output Events ................................................................................................................................................... 349
Event definition ................................................................................................................................................ 349
Event Location Table ........................................................................................................................................ 351
Output Focus Area ............................................................................................................................................ 352
Output: Clustering ............................................................................................................................................ 352
Algorithm Overview ......................................................................................................................................... 353
Clustering Settings ............................................................................................................................................ 353
Number of clusters............................................................................................................................................ 354
Locate Cluster Centers ...................................................................................................................................... 354
Manually .......................................................................................................................................................... 354
By Learning...................................................................................................................................................... 354
Training Set Definition ..................................................................................................................................... 354
Max. iterations .................................................................................................................................................. 354
Tolerance.......................................................................................................................................................... 355
Remove Outliers ............................................................................................................................................... 355
Clustering Criteria ............................................................................................................................................ 355
Clustering Output ............................................................................................................................................. 355
Find Rate........................................................................................................................................................ 358
Modes of Operation ........................................................................................................................................ 358
Additional Find Rate Dialog Settings, Output Tab ............................................................................................. 363
Specialized Analysis ....................................................................................................................................... 364
Chapter 17
Specialized Analysis ....................................................................................................................... 365
Detect and Classify Heartbeats ........................................................................................................................ 368
Locate Human ECG Complex Boundaries....................................................................................................... 368
Locate Animal ECG Complex Boundaries ...................................................................................................... 369
Gastric Wave Analysis .................................................................................................................................... 369
Gastric Wave Coupling ................................................................................................................................... 369
Chaos Analysis ............................................................................................................................................... 370
Detrended Fluctuation Analysis......................................................................................................................... 370
Optimal Embedding Dimension ........................................................................................................................ 370
Optimal Time Delay ......................................................................................................................................... 370

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Plot Attractor .................................................................................................................................................... 371
Correlation Coefficient ................................................................................................................................... 371
Electrodermal Activity .................................................................................................................................... 371
Derive Phasic EDA from Tonic ......................................................................................................................... 372
Event-related EDA Analysis.............................................................................................................................. 373
Sorting Options ................................................................................................................................................. 376
Locate SCRs ..................................................................................................................................................... 378
EDA Measurements .......................................................................................................................................... 379
Electroencephalography .................................................................................................................................. 381
Compute Approximate Entropy ......................................................................................................................... 381
Delta Power Analysis ........................................................................................................................................ 381
Derive Alpha RMS ........................................................................................................................................... 382
Derive EEG Frequency Bands ........................................................................................................................... 382
EEG Frequency Analysis .................................................................................................................................. 383
Seizure Analysis ............................................................................................................................................... 384
Seizure Analysis Parameters.............................................................................................................................. 385
Remove EOG Artifacts ..................................................................................................................................... 386
Preferences… ................................................................................................................................................... 387
Electromyography........................................................................................................................................... 388
Derive Average Rectified EMG......................................................................................................................... 388
Derive Integrated EMG ..................................................................................................................................... 388
Derive Root Mean Square EMG ........................................................................................................................ 389
EMG Frequency and Power Analysis ................................................................................................................ 389
Locate Muscle Activation.................................................................................................................................. 389
Preferences… ................................................................................................................................................... 390
Ensemble Average .......................................................................................................................................... 391
Epoch Analysis ............................................................................................................................................... 392
Focus Areas between Events and Segments ..................................................................................................... 393
Hemodynamic Analysis .................................................................................................................................. 393
ABP Classifier .................................................................................................................................................. 394
Arterial Blood Pressure ..................................................................................................................................... 394
ECG Interval Extraction .................................................................................................................................... 395
Estimate Cardiac Output from ABP ................................................................................................................... 396
Left Ventricular Blood Pressure ........................................................................................................................ 397
LVP Classifier .................................................................................................................................................. 398
Monophasic Action Potential............................................................................................................................. 399
MAP Classifier ................................................................................................................................................. 400
Preferences ....................................................................................................................................................... 400
HRV and RSA Analysis .................................................................................................................................. 401
Multi-epoch HRV – Statistical........................................................................................................................... 401
Multi-epoch HRV and RSA – Spectral .............................................................................................................. 402
R-R Poincaré Plot ............................................................................................................................................. 403
Respiratory Sinus Arrhythmia (RSA Time-series).............................................................................................. 404
Single-epoch HRV – Spectral ............................................................................................................................ 405
Frequency Bands ............................................................................................................................................ 407
PSD Options ................................................................................................................................................... 407
Improvements to PSD Options (AcqKnowledge 4.3 and higher)....................................................................... 408
Impedance Cardiography Analysis .................................................................................................................. 410
Body Surface Area ............................................................................................................................................ 410
dZ/dt Derive from Raw Z .................................................................................................................................. 410
dZ/dt Classifier ................................................................................................................................................. 410
ICG Analysis .................................................................................................................................................... 413
Ideal Body Weight ............................................................................................................................................ 416
PEP Pre-ejection Period .................................................................................................................................... 416
dZ/dt Remove Motion Artifacts ......................................................................................................................... 417
VEPT ............................................................................................................................................................... 417
Preferences ....................................................................................................................................................... 418
Magnetic Resonance Imaging.......................................................................................................................... 419
Artifact Frequency Removal.............................................................................................................................. 419
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Artifact Projection Removal .............................................................................................................................. 421
Median Filter Artifact Removal ......................................................................................................................... 421
Signal Blanking ................................................................................................................................................ 422
Neurophysiology ............................................................................................................................................ 423
Amplitude Histograms ...................................................................................................................................... 423
Average Action Potentials ................................................................................................................................. 423
Classify Spikes ................................................................................................................................................. 424
Dwell Time Histograms .................................................................................................................................... 424
Find Overlapping Spike Episodes ...................................................................................................................... 425
Generate Spike Trains ....................................................................................................................................... 425
Locate Spike Episodes ...................................................................................................................................... 425
Set Episode Width and Offset ........................................................................................................................... 426
Preferences ....................................................................................................................................................... 426
Noldus Format ................................................................................................................................................ 428
Principal Component Denoising...................................................................................................................... 429
Remove Common Reference Signal (for Mobita Hardware only) ..................................................................... 429
Remove Mean ................................................................................................................................................ 430
Remove Trend ................................................................................................................................................ 430
Respiration ..................................................................................................................................................... 430
Compliance and Resistance ............................................................................................................................... 430
Penh Analysis ................................................................................................................................................... 432
Pulmonary Airflow ........................................................................................................................................... 434
Preferences ....................................................................................................................................................... 435
Spectral Subtraction ........................................................................................................................................ 436
Stim-Response................................................................................................................................................ 436
Digital Input to Stim Events .............................................................................................................................. 437
Stim-Response Analysis.................................................................................................................................... 438
Waterfall Plot ................................................................................................................................................. 439
Wavelet Denoising ......................................................................................................................................... 440
ECG Analysis Algorithm References .............................................................................................................. 441
Chapter 18
Display Menu Commands .............................................................................................................. 443
Tile Waveforms .............................................................................................................................................. 444
Autoscale Waveforms ..................................................................................................................................... 445
Autoscale Single Waveform............................................................................................................................ 446
Optimize Ranges (MP36R Hardware only)...................................................................................................... 446
Overlap Waveforms ........................................................................................................................................ 446
Compare Waveforms ...................................................................................................................................... 447
Autoscale Horizontal ...................................................................................................................................... 447
Show All Data ................................................................................................................................................ 447
Show Default Scales ....................................................................................................................................... 447
Zoom Back / Forward ..................................................................................................................................... 448
Reset Chart Display ........................................................................................................................................ 448
Reset Grid ...................................................................................................................................................... 448
Adjust Grid Spacing ....................................................................................................................................... 448
Set Wave Positions... ...................................................................................................................................... 448
Set Channel Visibility ..................................................................................................................................... 449
Wave Color .................................................................................................................................................... 449
Active Slice Color............................................................................................................................................. 450
Horizontal Axis .............................................................................................................................................. 450
Show .............................................................................................................................................................. 452
Annotations ...................................................................................................................................................... 452
Channel Buttons ............................................................................................................................................... 452
Channel Input Values........................................................................................................................................ 452
Chart ................................................................................................................................................................ 452
Display Mode Toolbar ...................................................................................................................................... 452

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Dot plot ............................................................................................................................................................ 452
Dot size ............................................................................................................................................................ 452
Events............................................................................................................................................................... 452
Event Bar.......................................................................................................................................................... 452
Event Palette ..................................................................................................................................................... 452
Focus Areas ...................................................................................................................................................... 452
Focus Areas Bar................................................................................................................................................ 452
Grid .................................................................................................................................................................. 452
Grid Options ..................................................................................................................................................... 452
Hardware .......................................................................................................................................................... 452
Journal .............................................................................................................................................................. 452
Last Dot Only ................................................................................................................................................... 452
Line Plot ........................................................................................................................................................... 453
Line Thickness.................................................................................................................................................. 453
Main Toolbar .................................................................................................................................................... 453
Measurements ................................................................................................................................................... 453
Scaling Toolbar................................................................................................................................................. 453
Scope ................................................................................................................................................................ 453
Selection Palette ............................................................................................................................................. 453
Spectrum Analyzer Palette .............................................................................................................................. 454
Timers ............................................................................................................................................................ 454
Location Palette .............................................................................................................................................. 454
Stacked Plot Options....................................................................................................................................... 456
Step plot ......................................................................................................................................................... 456
Toolbar ........................................................................................................................................................... 456
X/Y ................................................................................................................................................................ 456
Customize Toolbars .......................................................................................................................................... 457
Spectrum Analyzer Palette Details..................................................................................................................... 458
Channel Information ....................................................................................................................................... 461
Preferences... .................................................................................................................................................. 462
Waveforms Preferences..................................................................................................................................... 466
Event Summary Preferences .............................................................................................................................. 467
Graph Preferences ............................................................................................................................................. 467
Journal Preferences ........................................................................................................................................... 468
Hardware Preferences ....................................................................................................................................... 468
Performance Preferences ................................................................................................................................... 469
Networking Preferences .................................................................................................................................... 469
Other Preferences .............................................................................................................................................. 469
Window Preferences ......................................................................................................................................... 470
Focus Areas Preferences ................................................................................................................................... 470
Location Preferences ......................................................................................................................................... 470
Video Capture Preferences ................................................................................................................................ 471
Resetting All Preferences to Factory Default ..................................................................................................... 471
Scroll options .................................................................................................................................................... 471
Size window... .................................................................................................................................................. 472
Cursor Style .................................................................................................................................................... 472
Create Data View............................................................................................................................................ 472
Create Focus Area........................................................................................................................................... 473
Organize Data Snapshots ................................................................................................................................ 473
Show All Data Snapshots ................................................................................................................................ 473
Load All Data Into Memory ............................................................................................................................ 473
Chapter 19
Program & OS Menus .................................................................................................................... 474
AcqKnowledge menu ...................................................................................................................................... 474
Window menu ................................................................................................................................................ 474
Bring All to Front ............................................................................................................................................. 474
Help menu ...................................................................................................................................................... 474
Chapter 20

Media Menu.................................................................................................................................... 476
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Synchronization Tip........................................................................................................................................ 478
Media > Set Up .............................................................................................................................................. 479
Linked Media ................................................................................................................................................. 480
Media > Capture ............................................................................................................................................. 480
Playback Preview ........................................................................................................................................... 480
Media Playback Example................................................................................................................................ 481
Media Capture Setup with CAM-HFR-A High Speed Camera ......................................................................... 482

PART D — LICENSED FUNCTIONALITIES ................................................................... 485
Chapter 21
Licensed Functionality: Network Data Transfer ........................................................................... 486
Data Connections............................................................................................................................................ 487
Variable Sampling Rates................................................................................................................................. 487
Transfer Types................................................................................................................................................ 488
Single Connection............................................................................................................................................. 488
Multiple Connection ......................................................................................................................................... 488
XML-RPC ........................................................................................................................................................ 489
Transport Protocol .......................................................................................................................................... 489
TCP/IP ............................................................................................................................................................. 489
UDP ................................................................................................................................................................. 489
XML-RPC ........................................................................................................................................................ 490
Real-time Delivery Guarantees ....................................................................................................................... 490
Data Formats .................................................................................................................................................. 491
Default Data Connection Settings.................................................................................................................... 491
Locating AcqKnowledge Servers .................................................................................................................... 492
Control Connections ....................................................................................................................................... 492
TCP Port ........................................................................................................................................................ 492
Control Procedure Calls .................................................................................................................................. 492
Channel Index Parameter Structures .................................................................................................................. 492
Querying Acquisition Parameters ...................................................................................................................... 493
Data Connection Configuration Commands ....................................................................................................... 494
Reading Data During Acquisition ...................................................................................................................... 497
Other Control Connection Commands ............................................................................................................... 498
Unity Interface for AcqKnowledge (requires Network Data Transfer License) ................................................... 499
Chapter 22
Licensed Functionality: Vibromyography ..................................................................................... 500
Sampling Rate Restrictions ............................................................................................................................... 500
Transducer Setup .............................................................................................................................................. 500
Post-Analysis Selection Adjustment .................................................................................................................. 501
Data Modification History Name....................................................................................................................... 501
VMG Calculation Channel Preset ...................................................................................................................... 501
VMG Sample Data Files ................................................................................................................................... 502
Chapter 23
Licensed Functionality: Scripting .................................................................................................. 503
Scripting Menu ................................................................................................................................................. 504
Script Editor ..................................................................................................................................................... 504
Variables Explorer ............................................................................................................................................ 505
Example Scripts ................................................................................................................................................ 505
Run Macro Calculation Channel........................................................................................................................ 505
More Scripting References ................................................................................................................................ 506
Chapter 24
Licensed Functionality: Remote Monitoring ................................................................................. 507
About Remote Monitoring ................................................................................................................................ 507
Remote Monitoring in AcqKnowledge Networking Preferences ....................................................................... 507
Remote Monitoring Client................................................................................................................................. 508
Remote Monitoring Client Browser ................................................................................................................... 508

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Table of Contents

Open Graphs Page............................................................................................................................................. 509
Configuration Settings Page .............................................................................................................................. 510
Data Monitoring Page ....................................................................................................................................... 511
Controls in Visible Range (Change Range) dialog ............................................................................................. 512
Chapter 25
Licensed Functionality: B-Alert ..................................................................................................... 513
Data Acquisition and Analysis with B-Alert™ ................................................................................................ 513
Acquisition Setup ........................................................................................................................................... 515
Channel Setup................................................................................................................................................. 515
B-Alert-specific Hardware Menu Options........................................................................................................ 516
Assign Definition File ..................................................................................................................................... 519
Output to ABM File Format ............................................................................................................................ 520
Opening the ABM Data File............................................................................................................................ 521
Linked Acquisitions in B-Alert ....................................................................................................................... 522
Cognitive Analysis Calculation Channels ........................................................................................................ 522
Data Output .................................................................................................................................................... 523
Chapter 26
Licensed Functionality: PV Loop Analysis .................................................................................... 524
Loop Location ................................................................................................................................................ 524
PV Loop Analysis Preferences ........................................................................................................................ 524
Baseline Analysis ........................................................................................................................................... 525
Locate ES and ED Boundaries ........................................................................................................................ 525
Realtime Display ............................................................................................................................................ 525
Full PV Loop Analysis .................................................................................................................................... 527
Multiple loop measures ................................................................................................................................... 528
Chapter 27
Licensed Functionality: Baroreflex Analysis ................................................................................. 533
Baroreflex Sequence Analysis ......................................................................................................................... 533
Sequence Analysis Setup Dialog ..................................................................................................................... 533
Baroreflex Slope Analysis ............................................................................................................................... 534
Slope Analysis Setup Dialog ........................................................................................................................... 534
Baroreflex Sequence Method Description ........................................................................................................ 536
Baroreflex Slope Method Description.............................................................................................................. 536
Chapter 28
Licensed Functionality: Actigraphy ............................................................................................... 537
Actigraphy User Interface ............................................................................................................................... 537
Creating Actigraphy Files ............................................................................................................................... 537
Importing Raw Accelerometer Data ................................................................................................................ 538
Opening an Existing Actigraphy File ............................................................................................................... 538
Actigraphy Analysis Settings .......................................................................................................................... 540
Actigraphy Analysis Settings Controls ............................................................................................................ 540
Sadeh Scoring Algorithm for Wake/Sleep Classification.................................................................................. 541
Sleep Derived Measures (Sleep Analysis) ........................................................................................................ 542
Activity Level Measures ................................................................................................................................. 542
Actigraphy Specialized Analysis ..................................................................................................................... 543
Chapter 29

BioHarness Bluetooth ..................................................................................................................... 545

Chapter 30
Stellar Telemetry ............................................................................................................................ 546
Stellar Telemetry System ................................................................................................................................ 546
Description of the Stellar Experiment Window Controls .................................................................................. 550
Further Information about Flexible Data Download ......................................................................................... 553
Stellar-specific Setup Window Menus ............................................................................................................. 553
Flexible Data Download Control Panel............................................................................................................ 559
Running a Stellar Experiment.......................................................................................................................... 560
Import and Display of Stellar Data in AcqKnowledge ...................................................................................... 562
Saving Graphs and Settings from Stellar Experiments...................................................................................... 562
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AcqKnowledge 5 Software Guide
Stellar Analysis in AcqKnowledge .................................................................................................................. 563
Chapter 31
Mobita ............................................................................................................................................ 566
AcqKnowledge Interface in Mobita ................................................................................................................. 566
Selecting or Adding Mobita Hardware in AcqKnowledge ................................................................................ 567
Mobita Menu .................................................................................................................................................. 567
Mobita Analog Channels Setup ....................................................................................................................... 568
Analog Channel Digital Filters........................................................................................................................ 568
Mobita Calculation Channels .......................................................................................................................... 569
Enable Common Average Value Removal ....................................................................................................... 569
Remove Common Reference Signal ................................................................................................................ 569
Mobita Acquisition (Length/Rate) Settings...................................................................................................... 570
Changing Acquisition Modes or Resetting Hardware....................................................................................... 571
Mobita Network Connection Utility ................................................................................................................ 571
Chapter 32
FaceReader ..................................................................................................................................... 574
How Does FaceReader Work? ........................................................................................................................ 575
Using FaceReader with AcqKnowledge ........................................................................................................... 575
Creating a FaceReader Project and Recording in AcqKnowledge ..................................................................... 576
Creating AcqKnowledge Graphs from a Saved FaceReader Analysis ............................................................... 577
FaceReader Signals......................................................................................................................................... 577
Valence and Arousal ....................................................................................................................................... 578
Connection Issues ........................................................................................................................................... 578

PART E — APPENDICES................................................................................................ 580
Appendix A - Frequently Asked Questions............................................................................................................. 580
Appendix B - Filter characteristics ......................................................................................................................... 583
Filter types ..................................................................................................................................................... 583
Window Functions.......................................................................................................................................... 584
Appendix C - Hints for Working with Large Files ................................................................................................. 586
Appendix D - Customizing Menu Functionality ..................................................................................................... 588
Appendix E—Locking/Unlocking the MP160/150 for Network Operations .......................................................... 589
INDEX ..................................................................................................................................................................... 591

Visit the online support center at www.biopac.com

Preface to AcqKnowledge Software Guide
Welcome
Welcome to the AcqKnowledge Software Guide. AcqKnowledge software is used in the BIOPAC MP160
(16-channel) or MP36R (4-channel) Research Systems, both of which perform acquisition and analysis of
life science data.
In addition to the MP Systems, AcqKnowledge also supports BIOPAC’s licensed BioHarness, B-Alert,
Mobita and Stellar Systems. For more information on these wireless hardware solutions, see the Licensed
Functionality Chapters at the end of the guide.
AcqKnowledge software not only makes data collection easier, but also performs analyses more quickly
and easily than a chart recorder. Easily edit data, cut and paste sections of data, perform mathematical and
statistical transformations, and copy data to other applications for reports and publication.
All BIOPAC data acquisition hardware with AcqKnowledge 5 is compatible with WindowsÒ 10/8/7 or
Mac OS 10.10-10.13.
This manual covers use of AcqKnowledge software with
MP160/150/MP36/BioHarness/Mobita/Stellar/Smart Center hardware and details BIOPAC equipment
available for a variety of applications. If a desired application is not addressed, visit the BIOPAC web site
at www.biopac.com to download one of our many Application Notes, or call to talk to an Applications
Specialist.
See also:
• BIOPAC Installation Guide—packed with the software installation disk.
• BIOPAC MP Hardware Guide—available under the Help menu and installed to the User Support
folder. Provides details on Hardware System modules, transducers, electrodes, etc., and setup and
calibration.
• BIOPAC Catalogs
H

H

MP Research Catalog

MRI catalog

VR & Stimulus Catalog

Supported Platforms
AcqKnowledge 5 is supported on the following:
Operating Systems
Hardware
Windows 10, 8, 7
MP160 and MP150 UDP
Mac OS 10.10-10.13
MP36R
BioHarness BT (Windows only)
Mobita (Windows only)
BioNomadix, BioNomadix Logger, BioNomadix Smart Center
Stellar (Windows only)

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AcqKnowledge 5 Software Guide

What’s new for AcqKnowledge 5.0.3
The following features have been added since AcqKnowledge 5.0.2 was released
· Bug Fixes
· 64-bit support for B-Alert systems
· New Realtime mode for Stellar Telemetry systems (Allows data to be streamed directly from Stellar
units into AcqKnowledge)
· macOS High Sierra support (10.13)
The following features have been added since AcqKnowledge 5.0.1 was released
· Bug Fixes
· Support for new BioNomadix Smart Center hardware
· Analysis Shortcuts – allows easy access to specialized analysis options from within a data channel
·

AcqKnowledge 5 and AcqKnowledge 4 can now run side-by-side on the same computer

IMPORTANT: AcqKnowledge 5 with MP160 hardware is not compatible with 32-bit operating systems. For 32-bit
system support, use previous-release AcqKnowledge 4.4.2 with MP150 hardware.

Using this Manual
The AcqKnowledge Software Guide is divided into four parts:
Part A Getting Started
Please review Getting Started whether new to computer-based data acquisition systems or an old hand at
physiological monitoring. Use this section to become acquainted with how the system works and the most
frequently used features.
Part B Acquisition Functions
Explains data acquisition features and gives a detailed summary of different acquisition parameters. Provides
an in-depth description of the commands used to determine acquisition rate, acquisition duration, and
specialized functions such as triggering, averaging, and online calculation of different values.
Part C Analysis Functions
Details information on analysis features; covers the range of post-acquisition analysis functions and
transformations available with the Hardware System. Describes how to edit data, take measurements and
perform basic file management options (save, print, etc).
Part D Appendices
Answers frequently asked questions, offers hints for working with files, includes information on upgrading
from previous versions, provides technical information about the Hardware Systems and other information
about the AcqKnowledge software.
See also:
BIOPAC Installation Guide
This guide was included with the software package. It contains full instructions for hardware and software
installation, and how to be up and running with the Hardware System in just a few minutes.
Hardware Guide
BIOPAC’s MP Hardware Guide is available under the Help menu. It gives practical examples of how the
data acquisition unit is used with different components for common types of data acquisition, and includes
sample results and applications for widely used test procedures. This guide provides instructions for
connecting external devices to the data acquisition hardware, electrodes, transducers, amplifiers, etc.

Visit the online support center at www.biopac.com

Part A — Getting Started

17

User Support System
User Support System files can be found in the following hard drive location; BIOPAC Systems, Inc/AcqKnowledge
5.x/User Support Systems in the Program Files or Applications folder.
n AcqKnowledge Software Guide is the software support document
n BIOPAC MP Hardware Guide is the hardware guide (with specifications)
The User Support files can also be opened directly from the installation media.
The files are in PDF format, and can be read by Adobe Acrobat Reader.
· Adobe Acrobat Reader can be downloaded for free at www.adobe.com.
The Samples folder in the BIOPAC program folder contains sample files and graph template Quick Start files for a
variety of applications. Quick Start templates are pre-configured for the channel setups and acquisition parameters
required for a variety of applications.
· In addition to the standard sample files, measurement sample data files are provided. These files are
configured for specific measurement types and include spreadsheets providing external data necessary for
measurement verification. Each spreadsheet contains procedures and examples for the associated
measurement data file. These sample data files consist of Event Measurements.acq, Traditional.acq (standard
mathematical measurements included in AcqKnowledge), Expression Sum_Calculate.acq and Correl
Coef.acq (Correlation Coefficient).
·

To open a graph template Quick Start file, choose File > Open then Browse to the BIOPAC Samples folder
(be sure to select/enable the desired file type).

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AcqKnowledge 5 Software Guide

Where do I find help?
The Introductory sections are intended to provide enough information to get up and running with the MP System,
and become familiarized with some basic AcqKnowledge functions. For detailed in-depth information, the following
resources are available.
Ø Help menu
The online Help menu includes basic information about standard AcqKnowledge functions and links to the
tutorial, software guide and hardware guide for online searchable Help while running AcqKnowledge, plus
links to the BIOPAC web site.
Please visit BIOPAC’s Tutorial Video page for instructional screencasts of many analysis routines and
software features.
Ø Application Notes
The BIOPAC web site at http://www.biopac.com has more than 50 available Application Notes. Download
the desired Application Note or call to request a hard copy.
Ø Acquiring data
For more specific information on different types of acquisitions, see Part B—Acquisition Functions. It covers
basic acquisition parameters in detail, and describes some acquisition features (such as peak detection
techniques and online Calculation channels) not covered in the Getting Started section.
Ø AcqKnowledge
Information about how to edit, display and transform data can be found in Part C—Analysis Functions. It
explains how to import and export data, how to save files, and other file management commands. This
section also explains how to use all of the post-acquisition features of the AcqKnowledge software.
Ø Connecting input devices
To find out how specific modules connect to the data acquisition hardware, turn to the BIOPAC Hardware
Guide PDF file. This section describes how to connect signal-conditioning modules to the data acquisition
unit and how to connect electrodes and transducers to the modules.
Ø Working with large files
Many users need to perform high speed (i.e., fast sampling rates) or long duration acquisitions. These types
of acquisitions tend to generate large (several megabytes) data files that can be difficult to load, store, and
view. The Hardware System can handle such acquisitions—see the Appendices for information on how to
optimize setup for these types of acquisitions.
Ø Troubleshooting
Includes a list of the most frequently asked questions regarding the Hardware System. Check this section
(Appendix A) for commonly encountered problems and solutions.
H

H

Visit the online support center at www.biopac.com

Part A — Getting Started

19

IMPORTANT SAFETY NOTICE
BIOPAC Systems, Inc. instrumentation is designed for educational and research-oriented life science
investigations. BIOPAC Systems, Inc. does not condone the use of its instruments for clinical medical applications.
Instruments, components, and accessories provided by BIOPAC Systems, Inc. are not intended for the diagnosis,
mitigation, treatment, cure, or prevention of disease.
The MP data acquisition unit is an electrically isolated data acquisition system, designed for biophysical
measurements.
Exercise extreme caution when applying electrodes and taking bioelectric measurements while using the hardware
with other external equipment that also uses electrodes or transducers that may make electrical contact with the
Subject. Always assume that currents can flow between any electrodes or electrical contact points.
Extreme caution is also required when performing general stimulation (electrical or otherwise) on a subject.
Stimulation currents should not be allowed to pass through the heart. Keep stimulation electrodes far from the heart
and located close together on the same side of the subject’s body.
It is very important (in case of equipment failure) that significant currents are not allowed to pass through the heart.
If electrocautery or defibrillation equipment is used, it is recommended that all BIOPAC Systems, Inc.
instrumentation be disconnected from the Subject.

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AcqKnowledge 5 Software Guide

Human Anatomy & Physiology Society Position Statement on Animal Use
(Adopted July 28, 1995, Modified January 2001, Approved April 29, 2012)
It is the position of the Human Anatomy and Physiology Society (HAPS) that dissection and the manipulation of
animal tissues and organs are important elements in scientific investigation that introduce students to the excitement
and challenge of their future careers. HAPS supports the use of biological specimens as part of a program of study,
provided their use is in strict compliance with federal legislation and the guidelines of the National Institutes of
Health and the United States Department of Agriculture, and that such use fulfills clearly defined educational
objectives.
The mission of the Human Anatomy and Physiology Society (HAPS) is to promote excellence in the teaching of
anatomy and physiology. A fundamental tenet of science is the ordered process of inquiry requiring careful and
thoughtful observation by the investigator. As subdivisions of biology, both anatomy and physiology share a long
history of careful and detailed examination, exploration and critical inquiry into the structure and function of the
human and animal body.
Consistent with the origins and nature of scientific inquiry, HAPS endorses the use of animals as part of the
laboratory experiences in both human anatomy and human physiology.
Historically, an important tool of investigation in human and animal anatomy has been dissection. A complete
anatomy learning experience that includes dissection goes beyond naming structures and leads the student to
conclusions and insights about the nature and relatedness of living organisms that are not otherwise possible. To
succeed in their future careers, students must become thoroughly familiar with anatomical structures, their design
features and their relationships to one another. Dissection is based on observational and kinesthetic learning that
instills a recognition and appreciation for the three-dimensional structure of the animal body, the interconnections
between organs and organ systems, and the uniqueness of biological material. Dissection conveys the inherent
variability of living organisms not otherwise observable in simulations and models. Physiology experiments
involving humans and live animals provide an excellent opportunity to learn the basic elements specific to scientific
investigation and experimentation. It is here that students pose questions, propose hypotheses, develop technical
skills, collect data, analyze results and develop and improve critical thinking and problem solving skills
Since effective teaching requires a diversity of strategies and approaches, HAPS endorses the use of computer atlases
and simulations, modeling, and video programs to meet educational objectives and the needs of students. Science
educators choosing not to use animals or biological specimens should choose alternatives that are able to convey
equivalent anatomical and physiological intricacies to meet their educational objectives.
Science educators have in common a respect and reverence for the natural world and therefore have a responsibility
to share this with their students. They must communicate the importance of a serious approach to the study of
anatomy and physiology. HAPS also encourages educators to be responsive to student concerns regarding use of
animals and to provide students who object to animal use with alternative learning materials.
HAPS contends that science educators should retain responsibility for making decisions regarding the educational
uses of animals and other strategies and techniques for the betterment of their student’s learning. Furthermore, it
opposes any legislation or administrative policy that would erode the educator’s role in decision making or restrict
dissection and animal experimentation in biology.
Used with permission of:
The Human Anatomy & Physiology Society (HAPS)
251 S. L. White Blvd., P. O. Box 2945, LaGrange, GA 30241-2945
800-448-HAPS (4277) Fax: (706) 883-8215 www.hapsweb.org

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Part A — Getting Started

21

Part A — Getting Started
Chapter 1
MP Systems Overview
Part A - Getting Started covers the basics of data acquisition and analysis with the MP System (MP160, MP150 or
MP36R), since these are the most commonly-used BIOPAC hardware systems. All material in this section is covered
in greater detail in subsequent sections (see Using this Manual, page 16 ).
X

BioHarness™ users should also see the BioHarness User Guide available under
the Help menu and installed to the User Support folder in the program folder.
Other BIOPAC hardware types, such as B-Alert, Mobita, and Stellar
are covered in the Licensed Functionality chapters at the end of the guide.
Overview
Data acquisition involves acquiring incoming signals (usually analog) and sending them to the computer, where they
are (a) displayed on the screen and (b) stored in the computer’s memory (or on hard disk). These signals can then be
saved for later analysis. Graphical and numerical representations of the data can also be produced for use with other
programs.
Function
MP160 (64-bit) and MP150 (32-bit)
Aggregate Sample Rate
Internal MP160/150 Buffer:
400 kHz
To Cpt. Memory or Disk:
300 kHz
Internal Buffer Size:
6 Mbytes
A/D Converter Signal/Noise Ratio: 86 dB typical
D/A Resolution:
16 bits
D/A Output rate:
Independent of A/D rate
Communication to Computer:
Ethernet (10 base T, UDP and DLC Type II)
AcqKnowledge software included with the MP system allows full control over editing data, how it is displayed
onscreen, and performs four general functions:
(a) Control the data acquisition process;
(b) Perform real-time calculations (such as digital filtering and rate detection);
(c) Perform post-acquisition transformations and analyses;
(d) Handle file management commands (saving, printing, etc.).
AcqKnowledge software shares the same interface on computers running Windows® or Mac® OS. However, most
optionally licensed features are available in the Windows version only.
The heart of the MP System is the MP data acquisition unit, which converts incoming physiological data into digital
signals to be processed and displayed in AcqKnowledge software. The MP160/150 data acquisition unit connects via
Ethernet, the MP36R connects via a USB connection.
The MP160 System also includes a High Level Transducer Module (HLT100C) for connecting external devices to
the MP160 unit. (The older-model MP150 System was supplied with a UIM100C Universal Interface Module.)
These Modules connect to the side of the MP160/150 unit.
A wall transformer is included with the MP System (MP160, MP150 or MP36R) to convert AC mains power into
DC power suitable for system operation and safety.

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AcqKnowledge 5 Software Guide

MP36R support
The MP36R is a four-channel data acquisition unit designed to work with AcqKnowledge 4.1 and above.
AcqKnowledge support for the MP36R unit includes:
§ Standard data acquisition and data acquisition features (triggering, multiple channels, variable sampling rate,
input values)
§ Output control functionality for controlling stimulators, digital channel, and channel redirection to output.
§ Standard analog presets for all SS series transducers
§ Electrode Check support
§ Multiple-MP device support. Similar to multiple MP160/150 support, each graph may acquire from a
maximum of one unique MP device.
§ Control channel support for changing digital output lines based on calculation channel analysis
MP36R Notes The computer sleep mode should be disabled—if the computer goes to sleep while AcqKnowledge 4

is running, communication with the MP36R may be lost and the application may freeze. To prevent
this from occurring, modify the computer settings to prevent the computer from going to sleep.
§ If sleep mode is enabled and causes the
application to freeze, force quit the application
and ‘power cycle’ the MP unit to re-establish
communication.
§ During an unresponsive period, the ‘Connect
Hardware’ dialog may display odd characters
in place of the MP serial number or the
computer, upon waking up, may generate a
“Driver irql not less or equal” error dialog.
AcqKnowledge software does not support MP36 units from the Biopac Student Lab product line
(without the “R” designation).
Mac OS users: Connect the MP36R directly to the computer, do not connect MP36R via hub or
keyboard.
MP System Requirements
Suggested minimum system requirements are detailed below. Recommendations are included to optimize system
performance; more memory and a faster system will enhance MP System performance. If planning to acquire data
for more than a few hours and/or are sampling at more than 2,000 samples per second, see the Disk Space note on the
following page.
H

H

For AcqKnowledge 5
OS

Requires Windows 10/8/7 or Mac OS 10.10-10.13
MP160/150 Requires Ethernet (UDP), MP36R requires USB.
Note To use an MP160/150 with UDP communication on a network with a non-Windows DHCP

Port

server, it is necessary to use firmware rev. 1.1.12 or greater in order for the MP160/150 unit to
properly be assigned an IP address. This is also true for any DHCP system with non-Windows
operating systems, such as Unix, Linux, Mac OS, and other DHCP-aware devices. UDP ports
for MP160 are 16004 and 16005, for MP150, 15000 and 15001

Hard Disk

Requires 1 GB to store the software and online manuals; additional 1 GB recommended for data storage

RAM

1 GB recommended

Processor

Windows: Dual Core or higher
Mac: Intel Core Duo or higher

Visit the online support center at www.biopac.com

Part A — Getting Started

23

Disk Space
With any program, adequate disk space is necessary for storage of data files. To acquire data for long periods
(more than a few hours) while sampling at relatively fast rates (more than 2,000 samples per second), as much
disk space as possible should be available. (A removable drive may also be used). See the Appendices for hints
on working with large files.
Automator Integration and Scripting Support
Mac OS X includes a visual scripting environment called “Automator.” Automator allows for drag and drop
creation of “Workflows.” Each workflow is a series of steps that is performed in another application. Each
individual step is called an action. An action encapsulates a simple operation within another application, such as
opening a text file in TextEdit or applying a filter within Photoshop.
Over 40 actions have been written to allow AcqKnowledge to be controlled from Automator workflows. Using
these actions, workflows can be constructed to perform sequences of transformations, automating postacquisition analysis, performing experimental protocols, and other repetitive operations.
Workflows can be constructed using Automator. It is also possible to create, edit, and execute workflows directly
from within the AcqKnowledge environment using the new “Workflow” menu. The Workflow menu allows the
creation of workflows specific to an individual user account or to one shared by all AcqKnowledge users. These
workflows can then be edited in the Automator environment. Each workflow created using Workflow > New
Workflow will appear at the bottom of the Workflow menu each time AcqKnowledge is launched. By simply
selecting the name of the workflow from the Workflow menu, AcqKnowledge will execute the workflow.
Workflows executed from the Workflow menu should begin with either an “Open Graphs” or a “Get Active
Graphs” action. Workflows intended for use outside of the AcqKnowledge environment (e.g. used as Folder
Actions) should begin with a “Launch Application” action to start AcqKnowledge followed by an “Open
Graphs” or a “Get Active Graphs” action.
For more information about Automator and help constructing workflows, see the Apple website at:
http://support.apple.com/kb/HT2488

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AcqKnowledge 5 Software Guide

MP System with AcqKnowledge Features
The MP System (MP160, MP150 or MP36R) with AcqKnowledge software is a complete system for acquiring
almost any form of continuous physiological data, whether digital or analog. The MP System can perform a range of
recording tasks, from high-speed to long duration acquisitions. For physiological applications, the MP System is
limited only by the computer speed and available memory or disk space. Features of the MP System include:
Easy to use

The MP System with AcqKnowledge offers power and convenience. In terms of hardware setup
the MP System (MP160, MP150 or MP36R) uses simple plug-in connectors and standard
interface cables.

Flexible

AcqKnowledge can be configured for a wide variety of applications, from single channel
applications to multiple-device measurements (up to 16 analog and 16 digital, or multiple
MP160s or MP150s). Control the length of acquisition, the rate at which data is collected, how
data is stored, and more.

Menu flexibility

Customize menu displays to show only necessary functions, thereby reducing the risk of error
or confusion in the lab. This is useful for teaching applications, giving instructors the option to
hide unnecessary menu items. See Appendix D—Customizing Menu Functionality.

High Speed
Sampling

Sample rates up to 400 KHz aggregate.

Variable Sample
Rates

Apply different sample rates between channels or operate the STM100C stimulator at a
different rate than the acquisition sample rate.

Template files

AcqKnowledge “Quick Start” templates are available for over 40 applications. Just open the
template file and start the acquisition—appropriate settings are established for the selected
application.

Online Calculation

Although AcqKnowledge includes an extensive array of measurements and transformations
applicable to collected data, computations often need to be performed while data is being
recorded. The online Calculation functions and presets allow users to calculate new channels
based on incoming signals. For example, this feature supports real time extraction of BPM and
many other signals based on raw ECG data.

Online
measurements

AcqKnowledge can instantly extract over 40 measurements and computations for any given
data point(s). These options are available from pull-down menus and include mean, peak-topeak, value, standard deviation, frequency, and BPM.

Measurement
Validation

Validate measurements with the ValidateMeasurements.acq sample file that was included with
the software. The measurement definitions (page 94) include measurement formulas and
“Sample data file” explanations.

Preview data

AcqKnowledge supports easy modification of the vertical scale and the horizontal scale.
Change the amplitude scale or the time scale to any desired value, or have AcqKnowledge
automatically scale them.

Simplified editing

Delete or edit sections data with a keystroke. Paste together sections from different waves, or
simply edit out noise spikes from individual waves.

Append mode

For certain applications, it may be necessary to only record data during selected portions of an
experiment. AcqKnowledge includes an “Append” recording mode, allowing unlimited pausing
and resuming of an acquisition. Appending data conserves storage space and processing time
for transformations.

Digital filtering

All data contains measurement error and noise. Reduce or eliminate errors in the data file by
using the included digital filters and smoothing transformations. Smooth data across any
number of samples, or filter out noise from any frequency or bandwidth. It’s also possible to
filter data as it is being recorded, rather waiting until post-acquisition. A wide range of online
filters can be applied to incoming data and results viewed in real time.

Digital Output

Control external devices when an input or calculation channel meets self-defined trigger
conditions. Use the Control channels to output a pulse when the analog channel signal falls
above or below a given threshold.

Visit the online support center at www.biopac.com

Part A — Getting Started

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X/Y plotting

View and acquire data in the form of an X/Y plot, with one channel displayed on the horizontal
axis and another on the vertical axis. This allows exploration of relationships between different
channels and opens up a whole range of applications, from chaos plots, to respiration analysis,
to vectorcardiograms.

Histogram function

Easily examine the variability and central tendency measures of any waveform data with the
histogram function. Set user-defined plotting options or let the software determine the “best fit”
for graphing data.

Math functions

In many cases, simply collecting raw data is not enough. AcqKnowledge includes an array of
built-in mathematical functions ranging from simple absolute value to computation of integrals,
derivatives, and operations involving multiple waveforms (such as subtracting one wave from
another). Daisy chain multiple functions together to form complex equations or expressions.

Annotation

AcqKnowledge includes a Journal window useful for adding comments relevant to the data,
and can be used while online or post-acquisition. This is especially useful for noting the
characteristics of an acquisition (what was involved, what manipulations took place, etc.) for
future reference.
See also: Text annotation, page 60.

Triggering

If an experiment requires measuring response times or starting an acquisition after a particular
event has occurred, AcqKnowledge supports triggering acquisition via a variety of methods.
Trigger on the level of a signal, or with an external synchronizing trigger.

Event markers

It’s often useful to make a note of when specific events have occurred so these events can be
recorded and specific changes noted. The event function allows for the insertion of event
markers into the recording and supports the addition of text for each event. Events can be
added while data is being collected or post-acquisition. Event functionality can be automated
for sequential application or customized to insert events using Function keys.

File compatibility

In AcqKnowledge, data can be saved and viewed in a number of different formats. For word
processing programs such as Microsoft Word®, use Copy to Clipboard and then paste into the
document. Use Save as Excel for Microsoft Excel®. Data can be outputted in text or graphical
form, and supports import of raw data from a text file. Open (and Import) or Save As (and
Export) supports many different file formats, such as MATLAB, Physionet, Igor Pro, SMI
Begaze, Dataquest and more.

Pattern recognition

Using advanced pattern search/recognition algorithms, AcqKnowledge can automatically find a
specific pattern within waveforms. This is useful for finding abnormal waveforms (such as
irregular ECG waves) within a data file.

Cycle/Peak
detection

AcqKnowledge has a built-in algorithm to find cycle data, such as positive or negative peaks,
from any size data file. Search for all cycles/peaks with one command and automatically log
statistics such as time and area to the Journal or spreadsheet.

Printing

AcqKnowledge provides a range of customizable graph printing options. No special printer
drivers are required.

Report generation

AcqKnowledge includes many features to simplify report generation. Use the Journal for notes
and quickly copy and paste graph data or measurements to the journal or to another program.
Cascade event markers to prevent print overlap and select the range of data to print and which
options to display (measurements, event markers, etc.). Use the Playback mode to simulate
acquisition for presentations.

User Support

Questions about compatibility with existing equipment or need to develop a specialized
measurement device? BIOPAC’s Applications Specialists are ready to help.
(www.biopac.com/support)

H

Application Notes
BIOPAC has prepared a wide variety of application notes as a useful source of information concerning certain
operations and procedures. These PDFs provide detailed technical information about either a product or application.
View or print application notes directly from the Support section of the BIOPAC website
https://www.biopac.com/application-note/.
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Application Features
Use the MP System with AcqKnowledge software for a wide array of applications, such as:
Active Electrodes
Allergies
Amplitude Histogram
Anaerobic Threshold
Animal studies
Auditory Evoked Response
(AER)
Automate Acquisition Protocols
Automated Data Analysis
Automatic Data Reduction
Autonomic Nervous System
Studies
Biomechanics Measurements
Blood Flow / Blood Pressure
/Blood Volume
Body Composition Analysis
Breath-By-Breath Respiratory
Gas Analysis
Cardiac Output
Cardiology Research
Cell Transport
Cerebral Blood Flow
Chaos Plots
Common Interface Connections
Connect to MP System (MP160,
MP150 or MP36R)s
Control Pumps and Valves
Cross- and Auto-correlation
Current Clamping
Defibrillation & Electrocautery
Dividing EEG into Specific
Epochs
ECG Analysis
ECG Recordings, 12-Lead
ECG Recordings, 6-Lead
EEG Spectral Analysis
Einthoven’s Triangle
EMG and Force
EMG Power Spectrum Analysis
End-tidal CO2
Episode Counting
Ergonomics Evaluation
Event-related Potentials
Evoked Response
Exercise Physiology
External equipment, controlling
Extra-cellular Spike Recording
Facial EMG
FFT & Histograms
FFT for Frequency Analysis
Field Potential Measurements
Fine Wire EMG
Forced Expiratory Flow &
Volume

Gait Analysis
Gastric Myoelectric Activity
Gastric Slow Wave Propagation
Gastrointestinal Motility
Analysis
Hardware Flexibility
Heart Rate Variability
Heart Sounds
Histogram Analysis
Imaging Equipment, Interfacing
Indirect Blood Pressure
Recordings
Integrated (RMS) EMG
Interface with Existing
Equipment
Interface with Third-party
transducer
Invasive Electrode
Measurements
Ion-selective Micro-electrode
Interfacing
Iontophoresis
Irritants & Inflammation
Isolated Inputs & Outputs
Isolated Lung Studies
Isometric Contraction
Isotonic Contraction
Jewett Sequence
Langendorff Heart Preparations
Laser Doppler Flowmetry
Left Cardiac Work
Long-term Monitoring
Lung Volume Measurement
LVP
Median & Mean Frequency
Analysis
Micro-electrode signal
amplification
Migrating Myoelectric Complex
Motor Unit Action Potential
Movement Analysis
MRI Applications
Multi-Channel Sleep Recording
Nerve Conduction Studies
Neurology Research
Noninvasive Cardiac Output
Noninvasive Electrode
Measurements
Nystagmus Investigation
Oculomotor Research
Off-line ECG Averaging
Online Analysis
Online ECG Analysis
Orthostatic Testing
Peripheral Blood Flow

Peristaltic (Slow Wave) Propagation
Planted Tissue
Pressure Volume Loops
Psychophysiology
Pulsatile Tissue Studies
Pulse Rate Measurement
Pulse Transit Time
Range of Motion
Real-time EEG Filtering
Real-time EEG Filtering
Recurrent Patterns
Regional Blood Flow
Relative BP Measurement
Remote Monitoring
Respiration Monitoring
Respiratory Exchange Ratio
Rheumatology
Saccadic Eye Movements
Sexual Arousal Studies
Signal Averaging
Simultaneous Monitoring
Single Channel Analysis
Single-fiber EMG
Software-controlled Stimulator
Somatosensory Evoked Response
Spectral Analysis
Spike Counting
SpO2 Analysis
Stand Alone Amplifiers
Standard Operating Procedures
Startle Eye Blink Tests
Startle Response
Stimulator, software-controlled
Systemic Vascular Resistance
Template Analysis
Tissue Bath Monitoring
Tissue Conductance Measurement
Tissue Magnitude & Phase Modeling
Tissue Resistance & Reactance
Ussing Chamber Measurements
Ventricular Late Potentials
Vestibular Function
Visual Attention
Visual Evoked Response
VO2 Consumption
Volume/Flow Loop Relationships
Working Heart Preparations

Visit the online support center at www.biopac.com

Chapter 2

AcqKnowledge Overview

Overview

AcqKnowledge software performs two basic functions: acquisition and analysis. The acquisition settings
determine the basic nature of the data to be collected, such as the amount of time data will be collected for
and at what rate data will be collected. All acquisition parameters can be found under the hardware (or MP)
menu. Other menu commands pertain to analysis functions such as viewing, editing, and transforming data.
Note: Minor differences exist between the Windows and Mac OS screen displays and keystroke/mouse
functionality. These differences are noted throughout this section.
Menu

Functionality

See Page

File

New, Open, Open Recent, Open Sample Data File, Open for Playback, SMI BeGaze
Import, Close, Dataquest Import, Dataquest Export, Save, Save As, Save Selection
As, Save Journal Text As, Send Email as Attachment, Copy to Dropbox, Open from
Dropbox, Page Setup, Print, Quit

262

Edit

Undo, Cut, Copy, Paste, Clear/Clear All, Remove Last Appended Segment, Insert
Waveform, Duplicate Waveform, Select All, Remove Waveform, Create Data
Snapshot, Merge Graphs, Clipboard (Copy Measurement, Copy Wave Data, Copy
Graph, Copy Acquisition Settings, Copy Data Modification History for All Channels,
Copy Data Modification History for Graph, Copy Focus Area Summary, Copy Event
Summary), Journal (Paste Measurements, Paste Wave Data, Paste Acquisition
Settings, Paste Modification History for All Channels, Paste Modification History for
Selected Channel, Paste Focus Area Summary, Paste Event Summary, Manage
PDFs, Show Journal)

286

Transform

operations that primarily modify the data in the graph
Recently Used, Digital Filters, Fourier Linear Combiners, Math Functions, Template
Functions, Integral, Derivative, Integrate, Smoothing, Difference, Resample
Waveform, Resample Graph, Expression, Delay, Rescale, Waveform Math, Slew Rate
Limiter

296

Analysis

operations that derive data & measurements from the graph
Recently Used, Histogram, Autoregressive Modeling, Nonlinear Modeling, Power
Spectral Density, Autoregressive Time-Frequency Analysis, FFT/IFFT, DWT Discrete
Wavelets, Principal Component Analysis/Inverse PCA, Independent Component
Analysis/Inverse, Find Cycle, Find Rate—plus a courtesy copy of the Specialized
Analysis package with classifiers and automation routines

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Display

Tile Waveforms, Autoscale Single Waveform, Autoscale Waveforms, Optimize
Ranges, Overlap Waveforms, Compare Waveforms, Autoscale Horizontal, Show All
Data, Show Default Scales, Zoom, Reset Chart Display, Reset Grid, Adjust Grid
Spacing, Set Wave Positions, Set Channel Visibility, Wave Color, Horizontal Axis,
Show, Customize Toolbars, Channel Info, Preferences, Size Window, Cursor Style,
Split View, Create Data View, Create Focus Area, Organize Data Snapshots, Show All
Data Snapshots, Load All Data Into Memory

443

MP160/MP150
MP36R

Set Up Data Acquisition, (Channels, Length/Rate, Event Marking, Segment Labels,
Stimulator, Trigger, Sound Feedback), Set Up Advanced Averaging, Show Input
Values, Show Manual Control, Show Gauge, MP160/150 info, Search for BioNomadix
Loggers, Quick Import BioNomadix Log, Import BioNomadix Logs, Disconnect
BioNomadix Logger, Configure BioNomadix User Alarms, AutoPlotting, Scrolling,
Sweep, Warn on Overwrite, Organize Channel Presets, Set Up Linked Acquisitions,
Exit Playback Mode, Manage Hardware Connections

109

B-Alert*
BioHarness*
Mobita*
Smart Center*

*Not all MP hardware menu items listed above will be available with MP36R, B-Alert,
BioHarness, Mobita, Smart Center, or other hardware.

Playback

Replaces the hardware menu when Playback mode is active (use File > Open for
Playback and Playback > Quit playback to toggle playback and acquisition modes)

39

Window

Controls the position of windows on the monitor

474

Help

Provides online support files (PDF format and web links).

474

Media

Capture or Playback media files(.avi, .wmv, or mpg) and synchronize with .acq data

476

Launching the AcqKnowledge software
After installation, connect the black or blue BIOPAC AcqKnowledge License Key to an
available USB port. The License Key must be connected in order for AcqKnowledge to run.
If AcqKnowledge is launched without the License Key connected, a prompt will appear:

After connecting the License Key, launch the software by double-clicking on the AcqKnowledge icon. If
hardware is not properly connected, the following messages may appear. (Examples shown are from
commonly-used MP160 or MP150 hardware.)

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Part A — Getting Started

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If a hardware prompt appears after launching AcqKnowledge, there are two primary causes: The hardware is
not properly connected and/or the power is turned off.
Ø To use AcqKnowledge without a data acquisition unit (depending on the dialog), choose Cancel,
Analyze Only, No Hardware, or set Preferences > Hardware > General to “Always work with no
data acquisition hardware connected.”

Assuming the hardware is properly connected, AcqKnowledge will launch the Startup Wizard. Use this
wizard to choose whether to create a new experiment, open a saved graph for analysis or to access the Help
and support options.

Standard Startup Wizard under
‘Create and/or Record a new
experiment’
Create empty graph

Functionality

Open graph template from disk

Opens new graph window for acquiring data with hardware. Combo box to the right
selects hardware, if more than one type is available.
Brings up ‘Open’ window for browsing to location of saved graph templates.

Use recent graph template

Activates list of recently-opened graph templates for easy selection.

Sample graph template

Activates list of sample graph templates stored in AcqKnowledge program folder for
easy selection.
Quits application or confirms selected operation.
If different hardware types have been previously added, they may be selected here
upon subsequent application launches. (If not, this menu will not be displayed.)

Quit/OK
Hardware type menu (center right of
screen)

NOTE: The Startup Wizard for BioNomadix Smart Center is different in appearance. See page 53.
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§

Open a graph file

§

BioNomadix Logger

§

Help

Presents similar options for analyzing existing graphs, including a checkbox
option to launch graphs in Playback mode. Playback mode will “replay”
previously recorded graph data in real time.
Presents options for importing BioNomadix Logger data from the Logger
device or from disk. Not applicable unless the wireless BioNomadix Data
Logger is being used. For further information about the Logger, click here.
Launch various help and support options, including Web screencast tutorials.

NOTE: The Startup Wizard may be disabled and bypassed if desired, after which AcqKnowledge will launch
directly to a graph window. Choose “Display > Preferences > Other > When application is launched," change
the default from “Show Startup Wizard” to “Create new empty graph window” and click OK.
It’s good practice to create a new graph window for each acquisition. To create a new graph window after the
original launch, choose “File > New.”
Setting up channels using Module Setup (MP160 and MP150 Hardware)
By default, AcqKnowledge presents the Module Setup dialog when a new graph window is launched via
“Create/Record a new experiment.” This view enables stepwise configuration of AcqKnowledge modules and
transducers simply by choosing from the list of supported hardware options, which can greatly simplify setup.

For further details on Module Setup, see page 112.
Setting up channels manually
If manual setup of channels independent of hardware is preferred, click “Cancel” in the Module Setup dialog
and choose the “View by Channels” option at the bottom of the channel setup screen. This will display the
manually-configured Input Channels Setup dialog.
NOTE: If desired, disable the default factory channel setup by going to “Display > Preferences > Hardware”
and changing the “When creating new graph windows use:” option from “Minimal channel setup” to
“User-defined default channel setup.” (For full details on this preference, see page 468.)
Also note that, when changing from “Minimal channel setup” to “User-defined default channel setup” the
following message will appear after clicking the“Clear Default Setup” button:

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Part A — Getting Started

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Basic Analog Channel Information

If using AcqKnowledge
with BioHarness™, Analog
channels can be turned
on/off but not changed.
By default, all channels are deselected on new graph windows. It’s recommended that all three boxes
(Acquire, Plot, and Value) be selected for each channel.
Acquire When the Acquire box is checked for a given channel, data will be collected on that channel.
Plot
Determines if data will be plotted in real-time during the acquisition. If the plot box is unchecked,
data will be recorded, but the associated channel will remain hidden.
Value
Enables a separate Show Input Values window to display the values for each channel in real time,
numerically and/or graphically.
Channel This is a dynamic alpha-numeric heading based on the type of channel selected: Analog (or
continuous), Calculation, or Digital. In the sample above, “A1” indicates Analog channel one.
Label
To the right of each channel number is an editable label for entering channel information.
Channel The channel sample rate is a function of the acquisition sample rate: all channel sample rate
Sampling options are equal to or less than the acquisition sample rate (as established via “Hardware
Rate
> Set Up Acquisition”). The options are a specific power of 2 less than the acquisition
sample rate. Use the pull-down menu to set the channel sample rate. See page 116 for details.
Basic Digital Channel Information
In contrast to analog data, Digital channels collect binary data that represent when a measuring instrument is
“on” or “off.” (For example, records whether a switch is open or closed, as in reaction time studies or control
applications.) Digital channels are acquired, plotted, and have values listed the same fashion as analog
channels. For more details about Digital channels, see page 129.
Basic Calculation Channel Information
Calculation channels are used for online computations and transformations of other channels. These channels
are configured similarly to analog and digital channels, but also have additional dialogues to specify the types
of transformations and computations to be performed.
Calculation channels include Presets as a quick way to get started—choose a preset and the software
automatically sets the gain, offset, etc. appropriate for the selected application.
When a new Calculation channel is enabled, a simple setup dialog corresponding to the selected preset is
presented, which helps facilitate proper setup. Choose from the list of available presets or create a custom
preset; see page 115 for details.
For a detailed summary of Calculation channel options, see the Calculation Channel section beginning on
page 129.
For a detailed look at launching and setup of AcqKnowledge software, watch the Tutorial video.
Selecting Hardware
When AcqKnowledge is first launched, an available data acquisition device can be selected from the “Connect
to:” dialog. The dialog lists all devices that are powered ON and sitting on the same local area network. When
using more than one MP160/150 device or working across a network, it will be necessary to lock/unlock an
MP160/150 to acquire data (see Appendix E on page 589 for details). The selected MP160/150 unit will be
listed in the upper left of the graph display as “Connect to:” if the Hardware toolbar display is enabled.
X

X

X

X129

X

X

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(To display the Hardware toolbar click the “add toolbar” icon

and check the “Hardware” option.

Setting Up Acquisitions

Once the channel parameters have been defined, the next step is to specify the acquisition settings. Choose
Hardware menu > Set Up Data Acquisition > Length/Rate from the Data Acquisition Settings dialog to
specify the type of acquisition to be performed. The basic parameters involve:
a) How data should be collected and stored
b) The data collection rate
c) The acquisition duration (total length)
Storage

Record and Append using Memory is the default acquisition option. Under this option, the MP System
automatically records data into a single continuous graph, and stores the data in computer memory
during the acquisition.
The third popup menu at the top of the dialog (which defaults to Memory) specifies where data should
be stored during the acquisition. Data can also be stored to disk or to the MP160/150 hardware. Up to
4 mb of data can be stored directly to the MP160/150. Data cannot be stored directly to the MP36R or
other BIOPAC hardware types.
Ø The advantage of storing to the MP data acquisition unit is that much faster
sampling rates may be obtained.
Ø The disadvantage of saving data to the MP data acquisition unit is limited storage
space and that data is not displayed onscreen while being collected. When the
acquisition has stopped, however, the data will automatically redraw on the screen.
The other option under storage is Averaging, which allows repeated trials of the same data. For more
information on this feature, see the averaging section on page 169.

Rate

Acquisition Sample Rate refers to how many samples the MP System acquires each second. The
higher the sample rate, the more accurate the signal processing. However, as the sampling rate
increases, so does the demand for system resources (memory, disk space, etc.). There is a “point of
diminishing return” in terms of sampling rate for almost all types of analog signals, where sampling
above a given threshold adds relatively little information.
The MP160/150 sampling rate has a lower bound of 0.1 samples per second, and an upper bound of
400 kHz aggregate. The MP160/150 must use a pre-defined rate; it does not accept custom rates.
Choose the best acquisition sample rate from the pop-up list.
Note: Channel sample rates are variable based on the acquisition sample rate. All channel sample
rate options are equal to or a specific power of 2 less than the acquisition sample rate.

Duration

The final acquisition parameter is Acquisition Length (Total Length), which controls how long an
acquisition will last. This can be scaled in seconds, minutes, hours, milliseconds or number of
samples. Set this value either by entering a number in the acquisition length box, or by moving the
scroll box left or right.

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Part A — Getting Started

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Starting an Acquisition
Once the channels and channel characteristics have been specified, the next step is to start the acquisition. If a
file window is not already open, choose File > New > Graph window.
Status light
To the left of the Start button is a circular status light. The status light indicates the communication link
between the computer and the data acquisition hardware unit.
§ If the data acquisition hardware unit is properly connected to the computer and is turned on, the circle will
be solid and green.
§ If the data acquisition unit is not properly connected or not communicating with the computer, the circle
will be gray.
§ Start
To start an acquisition, position the cursor over the
button and click the mouse, or select Ctrl+
Spacebar. If electrodes or transducers are connected to the data acquisition unit, a small value of random
signal “noise” with a mean of about 0.0 Volts will be collected.
§ For information on how to connect measurement devices to Hardware Systems, see the BIOPAC MP
Hardware Guide.pdf.
§ To start an acquisition using a variety of “triggers,” see page 180.
§ Graphs that open without a Start Button
o Compressed Graphs
o Merge Graphs
o Igor Pro Experiment
o Original Data Snapshot
o PhysioNet
o Raw Data Files
o DWT, IDWT
o Text Files
o PCA, IPCA,
o Transform menu operations: Off-Line
Averaging; Filter Response
o ICA, IICA,
o Analysis menu operations:
o AR Model separate graph output
Histogram; FFT (Magnitude and
o Nonlinear Modeling separate graph output
Phase); IFFT; Rate (put result in new
o HRV tachogram output
graph option)
o Chaos > Plot Attractor
o Chaos > Detrended Fluctuation Analysis
o MATLAB Graphs
Once an acquisition has started, the Start button in the acquisition window will toggle to a Stop button, and
two opposing arrows will blink, indicating that data is being collected (see below). The “BUSY” indicator
light on the front of the data acquisition unit will also illuminate, showing that data is being collected.
Stopping an Acquisition
To stop an acquisition at any time, click the
button or select Ctrl+ Spacebar.
An acquisition will stop automatically when it has recorded an amount of data equal to that indicated in the
Total Length box. To save this data file, choose File > Save.
The double-arrow icon to the right of the Start/Stop button is the rewind segment button. Use this button to
remove any unwanted recording segments from the graph. For more details, see page 176.

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Display Modes
The display modes are Chart, Scope, X/Y, Stacked Plot, and Playback. The data display as it appears on the
screen can be changed at any time, even during an acquisition. To change the display mode, click the
corresponding icon in the toolbar.
Chart mode
Chart mode is the default display mode.
Chart mode plots data much as it might appear on a
chart recorder, with time on the horizontal axis.
Each channel of data is in its own “track” across the
screen, with borders between channels. The
waveforms will not cross boundaries into the tracks
of adjacent channels.
If a waveform is plotted off the scale of the channel
track, choose autoscale waveforms and
AcqKnowledge will select the “best fit” for
waveforms to their tracks.
Scope mode
Scope mode plots data much as it might appear on an
oscilloscope, with time on the horizontal axis.
Scope mode is similar to Chart mode, except there
are no borders between different channels.
§ To help emphasize the selected wave in Scope
mode, select the “Gray non-selected waves”
Preference (via Display > Preferences).
Waveforms can overlap. The autoscale waveforms
command will automatically separate the waveforms
in the graph window.
Note: When only one waveform is present, the scope
and chart modes are identical.
X/Y mode
X/Y mode plots data from two channels against each
other, with the values from one channel on the
horizontal axis and the values from another channel
on the vertical axis. Plotting a channel against itself
displays a straight line.
X/Y mode can be useful for chaos investigations and
respiration studies.
Note: When viewing data in X/Y mode as it is being
acquired, plotting only the most recently
acquired data point can be a useful option. To
do this, select Display > Show > Dot Plot and
then Display > Show > Last Dot only.
Switching to X/Y mode during acquisition can be
slow. For best performance, switch to X/Y mode
either before starting the acquisition or after stopping
the acquisition.

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Part A — Getting Started

35

X/Y mode continued
Plotted channels
·

To change the channel being plotted: Click the Channel label once and hold.

·

X-axis, click above the waveform; Y-axis, click left of the waveform.
To flip the axes: Click the button in the upper left.

·

To change the channel label for this plot: Click the Channel label.

Toolbar icons
The center cluster of toolbar items is specific to X/Y mode. The left two buttons in this group are shortcuts
for the Autoscale vertical and Autoscale horizontal functions. Adjacent to these buttons are two buttons that
perform the center vertical and center horizontal functions.
Tools
Cursor: In X/Y mode, the I-beam tool in the lower right hand corner of the graph window changes into a
crosshair. When the crosshair is moved into the graph window, the coordinates of the crosshair are
displayed in the upper left corner of the graph window. The X value refers to the crosshair coordinate in
terms of the horizontal axis, and the Y value describes the location of the cursor in terms of the vertical
scale. By holding down the mouse, a crosshair is drawn over the closest data point and the measurement
toolbar “snaps” to that position to show the amplitudes of the actual pair of data samples plotted on the
screen.

Autoscale:

X/Y plot with ECG on X-axis and BPM on Y-axis
In X/Y mode, the Autoscale waveform function changes to read Autoscale vertical, which
plots the vertical channel so that it takes up two-thirds of the vertical channel space. This
function controls the “height” of the data being plotted in the graph window.
Similarly, the Autoscale horizontal function plots the waveform so that the waveform is
plotted in the center two-thirds of the window. This function controls the “width” of the data
being plotted in the graph window.

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Autoscaling adjusts the center point and the range of data displayed. To manually change the
scale, click in either the horizontal or vertical scale area. In this case, the scale at the bottom
edge of the graph windows (which usually reflects time) is the scale for the X variable, and
the vertical scale controls the scale for the channel plotted on the Y-axis.
Center:
In X/Y mode, since only two channels can be displayed at a time, tile waveforms and
compare waveform are replaced with Center horizontal and Center vertical. These two Center
commands change the midpoint of the horizontal and vertical scales (respectively) so that the
midpoint of the scale is equal to the mean value (average) for that channel. These features are
useful for centering the display so that it is easier to interpret.
Ch. # Box: In X/Y mode, the channel numbering boxes are disabled.
Meas. Menu: In X/Y mode, the measurement popup menus are disabled.
Plot Recent Data Only
Use this option in X/Y mode to plot a user-defined amount of recent data. Checking the “Plot recent data
only” and entering a value will hide plotting for all data not included in the entered time value.

Plot recent data option not applied

Plot recent data option applied with 6 sec. value

Stacked Plot mode
Stacked Plot displays multiple time ranges on top of each other and is enabled for acquisitions set to Append
(except when in X/Y mode). In this mode, all appended segments are stacked in the display, but only one
segment “slice” is active (“selected”). To view an individual segment, click the Chart mode icon.
§ Click the Stacked Plot mode icon to display the Stacked Plot controls beneath the toolbar:

To change the active slice, click the

Jump Tool or the … icon.

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Part A — Getting Started

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The selected segment is used for all enabled software functions. This means that autoscaling can easily create
what looks like a mess if the selected segment is not appropriate for scaling the largest segment. In compound
action potential graphs in Stacked Plot, the last segment slice will most often be the largest, so selecting the
last segment before autoscaling will likely yield the expected result. The Transform menu is disabled in
Stacked Plot mode.
A commonly used data visualization technique for examining the evolution of waveform morphology is the
2D waterfall plot or “stacked plot.” A stacked plot draws multiple traces for a single waveform on top of each
other, or “slices.” Each individual slice is a time-shifted plot of the original waveform. The slices toward the
bottom of the plot occur earlier in time then the slices toward the top.
Data can be acquired in stacked plot mode, but it is processor intensive. If acquisition setup includes high
sampling rates or control channels with low latency, acquire in chart or scope mode and switch to stacked plot
mode after acquisition.
The slices can be aligned at any type of events in the graph. This allows for alignment at appended segments
but also at locations found through other means. For example, an ECG waveform can be aligned at the start of
the T-wave to examine how the T wave evolves in time.
Active slice
In stacked plot mode, there is a single slice called the “active slice.” By default it is
drawn in black. To change the color, select Stacked Plot Options > Drawing Settings.
The values on the axes in the graph, grid, displayed events and text annotations,
selections, and any transformations all apply to the active slice. The active slice can
be changed using the navigation buttons in the graph toolbar.
Vertical Separation The vertical separation between consecutive slices is expressed as a percentage of the
entire visible area. This percentage is kept constant through zooming and scrolling
operations.
Stacked Plot Options

Display > Show > Stacked Plot Options

Slicing Event…

Drawing Settings…

Use Stacked Plot Options to activate slices or visually distinguish the active slice from other slices being
drawn in Stacked Plot mode.

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Automatic baseline

Gray inactive slices

Bold active slice

Change active slice…

Automatically jump…

Adjusts the baseline of each inactive slice to overlap the baseline of the active slice
prior to the application of any vertical separation. This helps compensate for baseline
drift in a signal. If it is disabled, no baseline compensation is applied and the stacked
plot may exhibit visual vertical segment ordering problems resulting from baseline
drift (but in this mode can be used as a tool to examine baseline drift).
Draws the active slice with a solid pen and draws inactive slices with a dashed gray
pattern pen. The gray pattern alternates pixels between the chosen waveform color
and the white background and has the effect of lightening the inactive slices, so it
may be necessary to zoom in to see the effect.
Draws the active slice with a thicker pen. In step and line plot modes, plotting
normally occurs with a one pixel wide pen. Inactive slices will remain one pixel wide
while the active slice will have the thicker pen as indicated in the edit field. When the
waveform is in dot plot mode, the pixel width will be added to the waveform's default
dot size to increase the dot size for the active slice.
Draws the active slice in a different color than the chosen waveform color. When
enabled, the same color is used for the active slice of each waveform in the graph.
The color can be changed by clicking on the colorwell to the right of the checkbox to
generate a standard color picker to select color.

Use the Jump tool (green arrow) to change the active slice. Each time the active
slice is changed the left edge of the plot area will be changed to match the start of the
newly activated slice. When disabled, each time the active slice is changed the
display will be adjusted in such a way that the time interval between slice starting
positions and the display origin is kept constant.

Functionality in Stacked Plot mode
Autoscaling
When a graph is displayed in stacked plot mode, all autoscaling and related display operations (tile,
compare, overlap) will examine visible data of the active slice only. It’s not possible to perform
autoscaling operations using data of any inactive slice.
Autoscale Horizontal
In stacked plot mode, autoscale horizontal will make the active slice occupy the entire visible area. The
slicing event corresponding to the beginning of the slice will be placed at the left edge of the screen and
the next slicing event (or last sample point of the waveform if the active slice is the last slice) will be
placed at the right edge of the screen. The vertical offset will remain unaffected.
Data Views
Different data views may have independent Stacked Plot settings. All settings are independent including
drawing preferences, slicing events, vertical separation, and active slice settings. Stacked plot settings are
stored individually for each data view in the graph file and will be restored when the graph file is opened
from disk.

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Any graph-wide operation that may affect the active slice will update all data views that are configured to
use stacked plot mode. This includes operations that affect the data (e.g. transformations) or events (e.g.
waveform editing).
Graphs Containing No Slices
It is possible that graphs may not contain any slices whatsoever if no events match the slicing event
criteria. If a graph in Stacked Plot mode contains no active slices, it will be drawn as if the graph was in
regular chart mode with the following differences:
All data is drawn using any active slice settings given in the stacked plot drawing options.
The “Active slice” index will read “N/A.”
The previous/next/choose slice graph toolbar buttons and “Display > Show > Stacked Plot Options” menu
items will be disabled.
It will be possible to view all data using the horizontal scrollbar.
All autoscaling operations will function as if chart mode was active. Autoscale horizontal will make all of
the data of the selected waveform visible on screen.
If the table of available slices was being displayed prior to the removal/editing of the last matching slicing
event, the table will be emptied and the “OK” button dimmed. The cancel button will remain active for
the table window to be dismissed.
The slicing event, vertical separation, and drawing menu items and toolbar controls will remain active.
Playback Mode (Replay)

Playback mode will replay a graph file stored on disk in real
time to simulate acquisition. Analog, digital and calculation channels are
replayed as stored in the graph file. AcqKnowledge allows calculation
channels to be reconfigured, including adding channels without an
offline equivalent. Calculation channels from the original graph can be
modified, added, or removed without affecting the data stored on disk in
the original graph file.
1. Select File > Open for Playback.
2. Locate a graph file and then click Open.
3. A new graph window will be generated.
§ The “Connected to…: hardware menu will indicate that the
graph will be “acquiring” data from the specified file and the
Start button will change to a “Replay.”
4. Press Replay to begin playback.
§ The replay can be stopped, but not paused. If the acquisition
mode is changed to Append, no additional segments will be
displayed.
5. Select Playback > Exit Playback Mode to return to acquisition
status.

Use Open for Playback to
experiment with different
calculation channels settings on
the same data or to recreate an
experiment for demonstration
purposes.
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Playback mode has millisecond timing accuracy and allows for reconfiguration of most acquisition
parameters. Exceptions include:
§ Length is limited to the amount of data in the file
§ Acquisition Sample Rate is fixed (use Channel Sample Rate to downsample)
§ Number of analog and digital channels is fixed
§ Save last, MP, and Averaging modes are disabled
§ “Append” will replay the same data.
Do not record data while playing back a data file. If one data file is open in "Playback" mode and is
'replaying' and a second data file is open in hardware mode and is acquiring data, clicking back and forth
between graph windows causes the hardware device menu to flip to the Playback menu (even though
'Connected to' shows communication with an MP160/150 unit).
Watch the AcqKnowledge Playback Mode video tutorial for a detailed demonstration of this feature.

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Data Views
A “Data View” window is used to provide an alternate view of the same data. It allows the presentation of
data in two or more modes for comparison, such as X/Y plots and chart plots. To compare responses in real
time, turn off Autoplot in one Data View (e.g., Dose 1) and continue Autoplotting in another (e.g., Dose 2).
To create a new Data View for the active (selected) graph, choose:
§ File > New and select type Data View
§ Display > Create Data View
§ Click the Data View toolbar icon
This will generate a new window displaying the active graph’s data, and will name the new window “Data
View of ‘Filename’
.
TIP Use the Jump-to tool (see page 60) to correlate data views.
Data Views share fundamental data characteristics such as channel labels, events, and sampling rates, but can
be customized for the following:
§ horizontal scale, precision, and offset
§ autoscrolling
§ vertical scale, precision, and offset
§ channel button display state
§ measurements, including number of
§ wave color
rows, precision, visibility, and use of
§ event display state
interpolation
§ channel order
§ grid settings, including spacing,
§ plot mode
visibility, and locking state
§ channel drawing mode (step, line, or dot,
§ selected area
including dot plot size and type)
§ autoplotting
§ hardware “connected to” display
§ hidden channels
The Data View window can be used like any other graph window. The menus and controls can be used to change
how the data is presented. An acquisition can be started or stopped in any of the Data Views for a graph, and any
transformations performed on the data in the Data View will be reflected in the graph and all of the other Data
Views. Printing a graph from a Data View will use the display settings of that Data View for outputting the graph.
When a file is saved to disk, the display configurations of any open Data Views are saved into the graph file.
When the graph file is reopened, all of the Data Views and their display settings will be restored.
§ Data Views are saved with the data file only if they are open at the time the original graph is closed and
saved.
§ Closing a Data View causes this view to be lost; it is not saved with original file.
§ Closing a Data View that was previously saved with a data file will not be saved if the data file is saved
after closing the Data View.
§ Closing a Data View will not invoke a warning that the Data View will not be saved.
§ Original Data Snapshot is not merged into the newly created data file.
In AcqKnowledge 4.3 and higher, a selected area can be shared across multiple Data Views by clicking and
holding the left mouse button over the I-beam toolbar cursor and choosing the “Link Selections Between Data
Views” option. (See example figure below.)
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Analysis
For purposes of illustration, a file containing data should be used. Sample files were installed with the software.
Select File > Open and choose a file from the list in the dialog. Sample data files can also be selected from the
Startup screen by choosing the “Open a graph file” and “Sample data file” options.
After opening the file called demo data.acq, the screen should resemble the following sample file display.

Sample File Display
The sample graph displays six different types of data, and there is a border between the waveforms.
To the left of each waveform is a vertical strip containing a text string that can be used to help identify each
waveform.
The time scale along the bottom denotes when the data was recorded relative to the beginning of the acquisition.
Ø Only the last eight seconds of the total data record are visible, although the file contains
the complete record.
Ø The data displayed on the left edge of the graph represent events that occurred about 22
seconds into the record, and the data displayed at the right edge of the screen represent
events that occurred about 30 seconds after the acquisition was started.
The maximum vertical scale range is from +10 to -10 Volts.
Ø This reflects the maximum input voltage the hardware unit can accept and is a greater
range than normally encountered.
Ø The display scale can be adjusted to virtually any value range, as demonstrated in the
graph window above.
As indicated by the horizontal scale, only a few seconds of data are displayed on the screen. Use Display >
Statistics to determine the total length of the record.
To view data that was collected earlier in the record, use the horizontal scroll bar to move to different points in the
record.
Alternatively, position the cursor in the horizontal scale area (where the numerical values are listed) and click the
mouse button. This will generate the following dialog (see page 74 for details).
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The Time scale box allows the amount of data that appears on the screen to be changed at any given time. In the
sample dialog, this is set to 2 seconds per division. The divisions on the screen are indicated by the four vertical
lines, thus displaying eight seconds at a time (two seconds per division times four divisions). By entering a larger
value in this box, more of the record will be displayed on the screen at any given time. Conversely, entering a
smaller value in this box will cause a shorter segment of data to be displayed on the screen.
Ø To display the entire waveform (in terms of duration), a shortcut is to choose Autoscale horizontal from
the Display menu. The Autoscale horizontal command fits the entire data file into the window, regardless
of the total length of the acquisition.
The Initial time offset
box allows “jumping”
to a different point in
the time display.
Changing the value in
this box allows for the
display of data
beginning at a certain
point in the record.
For example, to see
the data at the
beginning of this
record, input an initial
offset of 0 seconds.

As indicated in the time scale, the first data displayed (at the left edge of the screen) was collected at the
beginning of the acquisition. Also, the scroll box has moved to the left, indicating that the data on the screen
represents data collected earlier in the record.
After clicking in the horizontal scale area again, the same dialog will appear, and this time the value in the start
box should have changed to reflect the new section of data being displayed on the screen.

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AcqKnowledge also allows customization of the vertical scaling, or amplitude, of each waveform. Clicking the
vertical scale area produces a dialog (see page 76 for details).
Use the vertical scale dialog to change the range of amplitude values
displayed (scale) and set the value that appears in the center of the
vertical scale (midpoint).
Vary the midpoint and apparent magnitude of each waveform by
changing the values in each box. By changing the value in the scale
box, a smaller value has the effect of increasing the apparent amplitude.
Entering a number about half the current value will cause the amplitude
of the wave to appear to double.
· Scale—In the sample dialog, the units are set to 2 Volts per
division. As with the horizontal scale, there are four divisions
on the vertical axis, so this setting should show 8 Volts range of
data.
· Midpoint—The box below this controls the midpoint of this
range. In this case, the midpoint is set to 2 Volts, which means
that this channel will display the range from - 4 Volts to + 8
Volts.
As with the time scale, AcqKnowledge can automatically display the best fit in terms of midpoint and units per
division. To do this, select the Autoscale waveform command from the Display menu, and the amplitude and
offset of each wave will be adjusted to fit their sections.
Any modification in terms of rescaling (either horizontal or vertical) will only affect the way data is displayed,
and will not change the basic characteristics of the data file.
Selecting a waveform
Although all four waves are displayed at once, it’s optimal to operate on only one channel at a time. To do this,
select the desired channel by clicking it. Selecting a channel will allow for highlighting all or part of that
particular waveform, and enables discrete transformations on a given channel.
In the upper left corner of the graph window, there is a series of boxes that represent each channel of data. The
numbers in the boxes correspond to the channel used to acquire the data (the specifics of setting up channels are
discussed on page 30). In the previously-shown sample waveforms, ECG channels are represented by Channels 1
and 2, with respiration on Channel 4 and blood pressure on Channel 5.
To select one of these channels:
X

·

X

Position the
cursor over the channel box
and click the mouse, or

that corresponds to the channel to be selected

· Position the
cursor on the waveform of interest and click the mouse.
Show/Hide Channel
To “hide” a waveform, press ALT for Windows or OPTION for Mac and click the channel box.
Or, Alt+click on the channel number at the top of the channel label region.
To view a hidden waveform, repeat the appropriate key-click combination.
Alternatively, show/hide a channel via Display > Channel Visibility and checking/unchecking the channel boxes
in the Channel Visibility dialog. (See this Display menu option on page 449.)

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Collapsing Channels
In AcqKnowledge versions 4.4.1 and higher, individual or multiple channels may be quickly “collapsed” by
simply clicking the
button appearing in the upper left region of each channel. When a channel is collapsed, all
data is retained but hidden from view, and the button status changes to
while collapsed. Collapsing a channel
allocates more vertical space to remaining channels, enhancing the view of visible data.

Channel “Collapse” button
NOTE: In certain operating systems, the or
buttons may instead appear as and
characters. See below
example showing Channel 2 collapsed. Note that when a channel is collapsed, the channel label appears in a gray
horizontal bar indicating the channels’ location.

Channel 2 collapsed
To expand (unhide) the collapsed channel simply click the
label.

or

button, or double click the collapsed channel’s

NOTES:
·

Collapsing or expanding channels is supported in Chart or Stacked Plot mode only.

·

Pressing the Alt/Option key while clicking any button will collapse or expand all visible channels
with the exception of one. (A minimum of one channel must remain uncollapsed. It is not possible to
use the collapse or expand button on graphs with single channels.)

·

Collapsed channels are retained when a graph is saved and reopened.

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Zoom
Another way to examine data is to use the “zoom” tool. The zoom tool allows a selection of any portion of any
wave to be magnified. To use the zoom tool, click the
icon in the lower right portion of the screen. When
moving the mouse into the graph area, notice it changes from an arrow
to a crosshair (+). Start by positioning
the cursor in one corner of the box, holding down the left mouse button, and dragging the crosshair horizontally,
vertically, or diagonally to form a “box” which encompasses the area to zoom in on. After releasing the mouse
button, AcqKnowledge will automatically adjust the horizontal and vertical scales. To “unzoom,” choose Zoom
back from the Display menu.
Select an area
Once a channel has been selected, is possible to “edit” parts of that channel by selecting a section of the
waveform. The options available include cutting, copying, and pasting sections of waveforms. It’s also possible to
transform and analyze entire waveforms or specific sections of waveforms.
To use any of these functions, first select (or highlight) the area to be operated on. To select a section of a
waveform, position the cursor over the
icon in the lower right hand corner of the screen and click the mouse
button. Now move the cursor to the first point in the area to be selected When moving the cursor into the graph
area, notice that it changes from an arrow cursor to a standard I-beam editing tool.
To highlight a section of a waveform, position the
cursor at the left edge of the area to be selected and hold
down the mouse button. Now move the mouse to the right until the desired area has been selected.
To select more than one screen of data, position the
cursor at the left edge of the section to be highlighted,
then click and hold the mouse button. Use the scroll bars to move to a different point in the record, and when
reaching the desired endpoint (right edge) of the selected area, hold down the Shift key while positioning the
cursor and click the mouse. Selecting an area this way will also fine tune the selected area to include only a
specific range of data.
Once a channel has been selected and a section of data highlighted, it’s possible to operate on and edit that section
of the waveform. The editing commands behave much the same way as text editing functions. Cut, copy, delete or
paste sections of data as defined by the selected area. In most cases (depending on available memory), undo an
edit by choosing Undo from the Edit menu, or by using the shortcuts CTRL + Z for Windows or
+Z for Mac.
Selecting a portion of a waveform also allows for applying transformations to a particular area rather than the
entire area or all waveforms. Selecting an area also display snap measurements to be taken for parameters such as
Delta T, Mean, Standard Deviation, Frequency, etc. Measurement options are discussed in the next section.
The Selection Palette (Display > Show > Selection Palette) can also be used to select an area.
Keyboard data selection
Keystroke combinations can similarly used to select or deselect graph data on a sample-by-sample basis. This
helps add an enhanced level of precision to the selection operation. See data selection keyboard shortcuts on the
following page.
Keyboard Shortcut
Windows: Shift + Ctrl + Left Arrow
Mac: Shift + Command + Left Arrow
Windows: Shift + Ctrl + Right Arrow
Mac: Shift + Command + Right Arrow
Shift + Left Arrow
Shift + Right Arrow
Left Arrow
Right Arrow

Description
Subtracts one sample interval from the right edge of the selection. If the selection is
empty, no action is performed.
Subtracts one sample interval from the left edge of the selection. If the selection is
empty, no action is performed.
Adds one sample interval to the left edge of the selection.
Add one sample interval to the right edge of the selection.
Moves the selection one sample to the left, constructs a zero width selection.
Moves the selection one sample to the right, constructs a zero width selection.

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Transform data
AcqKnowledge includes a library of functions to transform data or perform mathematical
calculations on waveform data. All of these options are located under the Transform and
Analysis menus, and are discussed in detail in the Analysis section beginning on page
327.
When performing transformations
· If a section of a waveform is highlighted, the transformation will apply to that
section.
· If no area is selected, AcqKnowledge will always select a single data point.
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·

If the transformation can only be performed on a selected area (digital
filtering, for instance) and a single point is selected, the entire waveform will
be used (and the transform entire wave option will be disabled; close out of
the dialog and select an area if desired).

Measurements
Measurements appear in the row of
boxes across the top of the graph
window. The number of visible
measurement boxes and the display
precision can be specified in the
“Preferences” dialog of the Display
menu. Each measurement consists of
three parts: (a) the channel selection, (b)
the measurement function, and (c) the
result or actual measurement value.

For example, the results for “SC, Selected Channel” is:
Time
23.64800 sec
Delta T
9.44000 sec
Freq
1.05932 Hz
BPM
63.55932 BPM

The pop-up channel selection calculates a measurement either for the selected channel (SC) or from a numbered
channel in the graph. To switch between the channel options, click in the channel window. The pop-up menu
shows the channel numbers and labels for all channels in the file. By default, each measurement will reflect the
contents of the selected channel.
The pop-up measurement menu allows selection between different types of measurements. To choose a
measurement, click the measurement pop-up menu and select a measurement from the list.
· Some measurements (such as Time or Value) look at only a single data point whereas other measurements
(such as mean and delta T) examine a range of data on the selected channel.
· Some of the measurements that depend on a selected area (such as delta T) look at differences in the
horizontal axis measurement whereas other range measurements (such as peak-peak) use the vertical scale
information in calculating measurements.
For a complete description of each of the measurement functions, turn to page 94.
The final component of a measurement window is the measurement result.
· When an area is selected (or if the selected area is changed) the measurement result automatically updates
to reflect the change.
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Events (Markers)
In many instances it is useful to have the software mark an occurrence
or event during an acquisition so it can be referenced later. For
instance, a user may want to note when a treatment began or when an
external event occurred to be examined later. The software uses
“Events”, which are marked in the data to record events.
Event markers can be pre-established and automated. Event icons and labels appear at the top of the graph
window, and can be edited, displayed, or hidden from view.
Automatically insert event markers during an acquisition by pressing the Esc key. This will insert a event at the
exact time the key is pressed and will activate the text line entry, which allows immediate entry of a comment
associated with the event.
For a detailed description of events and event functions, including options to pre-establish event labels and set
function keys for different labels, see Set Up Event Hotkeys (page 224).
Watch the AcqKnowledge Events video tutorial for a detailed demonstration of this feature.
See also: Text Annotation, page 60.
X

X

Grids

Grid superimposes a set of horizontal and vertical lines on the graph window. The grid is designed to allow for
easy measurements, since the grid lines correspond to horizontal and vertical scale divisions. The grid can be
locked (analysis, printing) or unlocked (visual aid).
To activate the grid display, choose Display > Show > Grid or click the

toolbar icon.

§
§

To display minor grid lines, use Ctrl- .
To customize grid line and color and optimize the display and print features, choose Display > Show > Grid
Options.
For more information about using and printing grids, see page 80
Note: The Scale dialogs change when grid lines are locked. See page 74 for details on Horizontal Scale and page
76 for details on Vertical Scale.
Horizontal Split View
Horizontal Split View is a tool for “splitting” the data in a single graph into two simultaneously viewable areas
and displaying them side-by-side for convenient viewing. Split View is available for data plotted in scope, chart
or stacked plot modes. Both views can contain independent time scales, initial offset and autoscroll settings. This
can be useful for making side-by-side comparisons of data at different time ranges, or for reviewing the same
section of data in two separate time scales for more detailed examination. Split View configurations and scalings
can be saved and restored in the graph.
X

.

.

X

X

X

X

Split View can be activated via the following methods:
§ Choosing Display > Split View
§ Clicking the Split View toolbar button
Either method divides the graph into two equal regions with independent time scales, and the bar in the center can
be dragged to the desired location.

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In the above example, the view in the left pane was rescaled independently of the view of the same data on the
right pane. This will enable a closer view of an area of interest while maintaining the original data display. If a
Split View encompasses any events, annotations or focus areas, these will be visible in both panes.
§ Note that events, annotations, selected areas and focus areas appearing in the Split View are duplicate
displays of the same items. If any of these items are added, modified or deleted in one view, this change
will also be applied to the other view.
§ Split View is not supported in XY mode.
§ Printing of Split Views is not currently supported within the BSL application. If printing is desired, save the
graph in *.jpg format or use standard operating system screen capture utilities.
To exit Split View, uncheck the Display > Split View option or drag the Split View bar back to its home position
at the left of the horizontal scale.
Autoscroll Horizontal Axis Controls
During data acquisition, three plotting modes are offered. These are normally accessed via the Hardware menu,
but can be more easily dialed in by using the
button in the lower right of the horizontal axis region. This
button toggles between the following modes, and the button display changes to reflect the plotting type selected.
Status
Manual

Sweep

Autoscroll

Icon

Description
Horizontal axis is not modified by application during data acquisition. Only manual
adjustments affect the data plot. Equivalent to unchecking both Hardware Menu > Autoplotting
and Hardware > Scrolling.
Data is plotted until it reaches the right edge of the graph. At this point the data is scrolled,
clearing data display and showing the newly acquired data starting at the left edge. This
mimics the “sweep” of an oscilloscope. Equivalent to checking Hardware Menu > Autoplotting
unchecking Hardware Menu > Scrolling, and checking Hardware menu > Sweep.
New data is plotted at the right edge of the graph. When new data is acquired, existing data is
scrolled to the left, creating space to plot new data. Equivalent to checking both Hardware
Menu > Autoplotting and Hardware Menu > Scrolling.

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Journals
The Journal is a general-purpose text editor built into AcqKnowledge that acts as a notepad for recording notes
and data and saving text and/or numeric values for later review. The Journal can be used at the same time data is
being acquired. Every graph file has a graph-specific Journal file permanently linked to it. There is also an option
to generate independent Journals for data view, use with multiple graphs or protocols.
Graph-specific journal—Journal is saved with graph;
preferable for retaining notes and analysis within a
graph file. Display settings are independent. To save
a graph-specific Journal independent of its graph,
use File > Save Journal Text As option.
Independent Journal—Journal is saved into its own
file, separately from graphs; preferable when
performing analysis on multiple graphs at the same
time. Independent journals allow multiple journal
windows to be open at the same time (each graph
view can have its own journal associated with it), but
only one Independent Journal can be used at a time.
For more information on using Journals, see Journal Details on page 85.
Saving data
Once data has been collected, it can be saved as a file and opened later. The data file can be moved, copied,
duplicated and deleted just like any other computer file. By default, files are saved as AcqKnowledge (.acq) files,
which are a proprietary format designed to store information in a format as compact as possible. Although these
files can only be opened from within AcqKnowledge, the data in these files can be exported either as a text file or
as a graphic image.
Exporting data to a text file allows for examination of the data using other programs, such as a spreadsheet or
statistical analysis package. Saving data as a graphic (.jpg) allows working with the data in graphic format.
One of the most useful applications of this is the ability to edit and place AcqKnowledge data as it appears on the
screen. Use this feature to paste graphs into word processors, drawing programs, and page layout programs. To
learn more about these options, turn to the Save As section beginning on page 275.
Format change warnings
When a File > Save function requires a format change for compatibility or alters file content, a prompt is
generated to require the user to confirm the option to update format or convert and save.
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Created with a previous version of AcqKnowledge

Windows PC AcqKnowledge format

Saving as a “Graph Template” will erase all data

Imported from another file format

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“Data Snapshot” — Embedded Archive
“Data Snapshots” are essentially embedded archives of the original acquired data stored with the graph file which
can be viewed together at a later time to compare results to original waveforms or intermediate stages of analysis.
IMPORTANT Archive functions do not create a new file—they are not backup functions.
Original data is copied and pasted to the end of the original file.
This feature cannot be used to recover lost or damaged original data.
There are two ways to create a snapshot:
1. Automatic after acquisition: Display > Preferences > Other > Create Data Snapshots after acquisitions

When this is enabled, a date-stamped archive of the data in the graph when acquisition stopped is created.
In Append mode, the entire graph is archived with each Append, old data as well as the newly acquired
data.
This is a memory intensive function;
each archive that is added to a graph file
will increase its size on disk by
approximately 40%. When prompted,
click OK to proceed.
2. Manual: Edit > Create Data Snapshot

A snapshot is then taken of the data at that point in time and stored with the graph. Manual archives allow
preservation of intermediate stages in a complex analysis for future reference. A comment prompt will
appear for describing the archive. This description will be used in the header the archive is displayed.
To view the embedded archive(s) associated with a graph file, choose Display > Show All Data Snapshots.
This will open a new graph window for each archive associated with the graph. The time portion of the Filename
for each graph is from the computer clock (saved with semi-colons because using colons in a filename is not
supported). The “Data Snapshot from…” graph will open with no Start button.
Manual Archive: description and time
Original file
Automatic Archive: time only

Snapshots will also retain the following in addition to the data:
· Events - Text annotations
· Graph-specific journals

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Print
AcqKnowledge allows high-resolution printing of
hard-copy graph plots much as they appear onscreen.
· To print a file, choose Print from the File menu.
This will print the contents of the screen on the
selected printer.
· To print the entire file, choose Autoscale
Horizontal from the Display menu first.
· Printing a journal is a separate command from
printing a graph file.
Instruct AcqKnowledge to print the contents of a file
across several pages by entering a value in the Fit to
box. Entering “4” in this box, for instance, will place
the length of the page evenly across four pages when
printing.
Print options are available after clicking OK in the
initial File > Print dialog; see page 284.
X284

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AcqKnowledge with BioNomadix Smart Center
BioNomadix Smart Center is a small-form wireless data acquisition system that joined the BIOPAC product line
late in 2017. Smart Center works with BioNomadix Transmitters and combines ease-of-use and compactness with
the full functionality of AcqKnowledge software. Guided prompts are used to pair and set up the transmitters.
The Startup Wizard interface for AcqKnowledge with BioNomadix Smart Center varies from that of standard
AcqKnowledge implementation. Additional minor UI differences are present in AcqKnowledge software when
Smart Center hardware is being used.
Launching AcqKnowledge with Smart Center
AcqKnowledge for Smart Center is launched in the same fashion as standard AcqKnowledge, by
clicking the Desktop shortcut. The Smart Center License Key must be connected to a USB port in
order to launch and run AcqKnowledge for Smart Center.

The AcqKnowledge with Smart Center Startup Wizard appears as follows:

Record New Data

Launches the Startup Wizard for pairing transmitters and configuring other options.

Analyze Recorded
Data

Launches a list of the 10 most recently-opened data files. The default number of 10 listed
files can be modified by choosing “Display > Preferences > Other” in AcqKnowledge.

Quit

·

Highlighting any file in the list and clicking “Open” will open the selected file
for analysis in the AcqKnowledge application.

·

Selecting “Search Disk” launches a window for navigating to files not
appearing in the recent file list.

Exits application.
Clicking the “question mark” icon opens a dialog with information about the software build
and connected Smart Center unit.
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Selecting the “Record New Data” Startup option launches the following window:

To pair a BioNomadix Transmitter, click “Pair New Transmitter” and follow the onscreen prompts.

Once Transmitters are paired, there are two primary options, “Start Recording Now” and “Record Later.” The
“Start Recording Now” option launches the AcqKnowledge graph window and immediately begins recording data
from the paired transmitter. The “Record Later” option launches the AcqKnowledge graph window but it’s
necessary to click the “Start” button in the graph to begin recording. Refer to the BioNomadix Smart Center
Guide for further details about Smart Center operation.
TIP: Clicking the blue “exclamation point”
to the right of the paired BioNomadix Transmitter icon will open a
PDF detailing information and guidance about the paired transmitter.

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Differences and Limitations – AcqKnowledge for Smart Center vs. Standard AcqKnowledge:
As noted earlier, there are some minor user interface and functionality differences between AcqKnowledge with
Smart Center and Standard AcqKnowledge.
· Different startup screen (simplified wizard with record and analyze only, guided prompts for
pairing transmitters)
· Hardware limited to Smart Center only – switching via “Manage Hardware Connections” not
supported
· No manual channel setups, module setups, or calculation channels (number and type of channels
dictated on front-end by transmitter hardware)
· Sample rate locked to paired transmitter type (2 kHz max compared to 400 kHz aggregate in
MP160)
· Variable sample rates not supported
·
·
·
·

No stimulation setup in software
No triggering setup in software
Averaging not supported in Length/Rate acquisition setup
Linked acquisitions not supported

AcqKnowledge with Smart Center Menu
All remaining AcqKnowledge functionality is the same as in the standard MP160/MP36R application version.
Refer to the BioNomadix Smart Center Guide in the AcqKnowledge Help menu for further details about Smart
Center and BioNomadix Transmitter operation.

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Chapter 3

§
§
§
§
§
§
§
§
§
§
§

User Interface & Context Menu Features

Toolbars
Keyboard Shortcuts
Mouse Controls
Custom toolbars for transformations and analysis
Toolbar position retention and changes
Event tool enhancements
Typed event label drawing improvements
Choose MP160/150 Help Button
Button Transparency
Customizable Chart Track Dividers
Plotting Background Colors

§
§
§
§
§
§
§
§
§

Vertical axis scaling buttons
Long channel labels and units
Graph window tooltip improvements
Menu item tooltips
Channel Info
Transformation history
Canceling Transformations
Transformation Progress Bar
Focus Areas

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Toolbars
Many of the most commonly used features in AcqKnowledge can easily be
executed with a mouse click. The toolbars contain shortcuts for some of the
most frequently used AcqKnowledge commands. Click an icon to activate it;
icons are grayed out when they are not applicable.
By default, a minimal toolbar configuration is presented when AcqKnowledge
is first launched. The default toolbars will appear as follows:

The default toolbars consist of:
· Start/Stop button
· Cursor Toolbar (Arrow, I-beam and Zoom tools)
· Main Toolbar (Grid, Toolbar Display, Preferences and Customize Toolbar buttons)
The full range of available toolbars can be displayed by enabling the checkbox options in the Toolbar Display
shortcut button
, or via Display > Show and enabling the desired options. Once the toolbar options have
been selected, this will be the default toolbar display for all new graphs. All toolbars can be deselected and
hidden with the exception of the Start/Stop button and the Cursor Toolbar (Arrow, I-beam and Zoom tools).
Saved graphs created with different toolbar configurations will open with those toolbar options displayed.
Toolbar position—Toolbars can be dragged and repositioned to any border of the graph window, or floated
on top of a graph. Toolbars retain the last position they were left in after the application is closed and a new
graph reopened.
Restoring the default toolbar position – The default toolbar positions can be restored by going to Display >
Preferences > Other and selecting “Reset toolbar positions.” The application must then be closed and
relaunched for the reset to take effect.
TIP: Preferences can also be accessed by clicking the Preferences toolbar shortcut icon

.

NOTE: The “Reset toolbar positions” option restores the default toolbar locations only; it does not hide
toolbars or restore the default minimal toolbar configuration displayed upon first launch. To return
toolbars to the default minimal configuration, it is best to deselect unwanted toolbars in the toolbar
display menu.
(Use the Toolbar Display shortcut button
or Display > Show.)
The toolbars can be reset to the default minimal configuration by holding down the Shift key while
launching AcqKnowledge, but this is a “nuclear” option.” Choosing this option will reset ALL
program defaults to the factory configuration. Do not choose this option if the configuration contains
custom settings that need to be saved.

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Main, Display and Scaling Toolbars
Main Toolbar
TOOLBAR ICONS

Display Mode Toolbar
FUNCTION

Scaling Toolbar

Show/Hide gridlines in the graph window. Click and hold the mouse to display
various grid preset options.
Opens popup menu for showing/hiding individual toolbar options.
Opens the Preferences dialog.
Opens the customize toolbar menu.
Change display to scope mode.
Change display to chart mode (default).
Change display to X/Y mode.
Toggle Stacked Plot (overlap segment) mode; see page 36.
Horizontal Split View; see page 48.
Create Data View; see page 41.
Autoscale selected waveform only.
Autoscale waveforms along the horizontal axis.
Center waveforms vertically in the active window.
Center waveforms horizontally in the active window (X/Y mode only).
Hardware Toolbar

The hardware toolbar displays connected to information and includes quick access to add/change hardware.
Cursor Toolbar

Cursor tools are used in many of the on-screen functions described below, including editing, measurements,
and the amount of data displayed.
NOTE: The four rightmost icons on the Cursor toolbar (Event tool, Zap tool, Jump tool, and Annotation tool)
do not become visible until data has been acquired, or a graph containing data has been opened. See below for
full description of all toolbar button functionality.

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Cursor Tools
The cursor tools are also accessible via the Display menu (Display > Cursor Style)
This is a general-purpose” arrow” cursor tool, used for selecting waveforms, scrolling
through data, and resizing the chart boundaries between waveforms when in chart mode. All
other cursors default to this mode when the cursors are moved outside the graph area. Use
Alt-click to step through the channels; each click makes a new channel “active.” The arrow
cursor can also be activated by the Ctrl+B keystroke.
Holding down the left mouse button with the arrow tool positioned over a graph channel will
activate a single data point, which displays as a solid black vertical line. This is known as
“spot measurement” mode. Dragging the mouse will then update selected measurement
values to the new horizontal locations of the arrow’s position in the graph. The mouse button
should be depressed for approximately 0.5 seconds in order for spot measurement mode to
become active. Releasing the button restores the arrow cursor to its normal status.
This is a standard “I-beam” editing tool. This tool is used for selecting an area of a waveform
(or waveforms) to be edited or transformed. However, editing of the selected area is limited
to the channel currently selected in the graph. Click to I-beam icon to activate it. Now move
the cursor toward the waveform. Notice that the cursor changes from an arrow to an I-beam
when it is placed over the graph area.
When this cursor appears, select an area of data by holding down the mouse button and
dragging the mouse to either the left or right. Extend the selected area to include data that is
not on the screen by positioning the cursor at the left edge of the area to be selected and
clicking the mouse button. Next, use the scroll bars to scroll through the data until the desired
data appears on the screen. Hold down the shift key while positioning the cursor to select the
right edge of the area to be selected. Click the mouse button to select the area. To extend the
selection, hold the Shift key and move the cursor or the arrow keys. The I-beam cursor can
also be activated by the Ctrl+I keystroke.
Clicking and holding on the I-beam tool will generate a pop-up menu for displaying the
Selection Palette or linking selections between Data Views.

When “Link Selections Between Data Views” is selected, the standard I-beam cursor icon
will change to one with a link appearing across it. When enabled, any area selected in a Data
View or source graph will also be applied to any other associated data view. For more
details, see Data Views on page 41.
This is a standard “zoom” tool. The zoom tool is used for selecting and magnifying any
portion of any wave. Click the
icon to use the zoom tool. When moving the mouse into
the graph area, it will change from an arrow
to a crosshair (+). Start by positioning the
cursor in one corner of the box, then hold down the (left) mouse button and drag the
crosshair horizontally, vertically, or diagonally to form a “box” that encompasses the area to
be zoomed in. Release the mouse button, and AcqKnowledge will automatically adjust the
horizontal and vertical scales. To “unzoom,” choose Zoom back from the Display menu or
use the Ctrl+minus keystroke.
Hold the “Alt” key to change the zoom mode to zoom out (“– “in the magnifier). The zoom
tool can also be activated by the Ctrl+G keystroke.
Grid
Control

Adjust the grid lines horizontal and vertical. Hold the option key for locked grids to drag to
the end.

Event
Definition

Inserts an event at the mouse click location. See page 231 for Event details.
231

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§

On a plot, the horizontal location matches the ‘x’ coordinate of the click
§ In Chart mode, the event will be placed on the channel track where the click took
place.
§ In Scope mode, the event will be defined on the active channel.
§ Within the events bar, clicks define global events.
When Event Definition is active, the cursor changes to a flag and the cursor includes a
downward pointing arrow to indicate where the event will be defined.
The Event Definition tool is disabled in X/Y mode and if events are not visible.
Event
Removal
“Zap”

Jump-to

Deletes event(s) from a graph with the mouse. It allows for quick editing to eliminate
misclassified events found through visual inspection.
§ If the user clicks a single event, that event will be removed from the graph.
§ If the user clicks and drags to define a rectangular area (similar to the zoom tool), all
events between the left and right edges of the area will be removed; the event icon does
not need to lie vertically within the bounded area in order to be removed.
When Event Removal is active, the cursor changes to a lightning bolt.
Data views and advanced analysis output display multiple representations of the same data at
the same time. Sometimes this association may be abstract or difficult to visualize. The
Jump-to tool is a green arrow, and is available in all display modes and during acquisitions.
Use the “Jump-to” tool to correlate data.
·
·

·
·
·
Text
Annotation

Click the Jump tool on a data point to “jump” all of the open data views for that
graph to the same time.
Click the Jump tool on a point in an X/Y plot to jump data views in chart or scope
mode to the point in time corresponding to the point in the X/Y plot. This can be
useful for correlating PV loops back to other acquired signals.
Rate analysis output graphs will jump back to the corresponding point of source data
at the start of that cycle.
Clustering scatterplots will select the appropriate segment of the source graph
corresponding to the chosen data point.
Change the active segment in Stacked Plot mode; once a trace is selected the display
will adjust to show the new active segment.

Use Text Annotation to add floating text notes on top of data in a graph; the text notes move
and scale with the data. During report or figure preparation, it is nice to be able to add
additional textual information on top of signals to help clarify signals for readers or draw
their attention to particular areas of visual interest. AcqKnowledge provides a text annotation
facility to assist in figure preparation.
Click the A icon and then click in the graph window to generate the Text Annotation
Contents dialog. Drag the red “handles” from the annotated text to add connector lines to
connect the text to the data.

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Text
Annotation
continued

Connector handles

Resize a range

Add a range

Move a connector

Text annotations are short pieces of text that float above channel data and can be used to
draw visual attention to particular areas of interest in a graph. These text annotations can be
simple outlined text, can have a connector from the outline boundary to a specific sample
point on the waveform, or have a range indicator of a specific width. Each text annotation is
tied to a sample of data in a channel; when the data is moved by copying, pasting, or other
waveform editing operations, text annotations remain fixed to their corresponding sample
positions, similar to channel events.
Although text annotations are tied to horizontal locations like event markers, they are
displayed in a relative fashion. The relative pixel distance between the text annotation outline
boundary and the sample of data remains the same under zoom and autoscaling operations.
· For example, an annotation that is 20 pixels above a T-Wave peak position will
continue to be drawn 20 pixels above regardless of zoom. This allows for flexible
data viewing while maintaining text annotation visibility.
Text annotation controls
With the tool active, click in the graph to define a new annotation.
Select
Click an annotation once to select it.
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Reposition
Drag a selected annotation to reposition it.
Add Connector Connectors or range indicators can be added to selected annotations by
using the editing handles on the edges of the selected annotation.
Edit Connector If the selected annotation has a connector to a data point of the graph, an
editing handle will appear on the end of the connector. The connector can
be moved to a different data sample of the graph by dragging the editing
handle on the end of the connector to the new position in the channel. To
remove the connector, grab the editing handle on the end of the connector
and drag the mouse inside the text annotation.

Range Indicator If the selected annotation has a range indicator, editing handles will
appear at both ends of the range indicator. To resize the range indicator,
grab an editing handle and move the mouse. To remove the range
indicator, grab an editing handle and move the mouse back inside the text
annotation.
Autoposition
Resizing windows or adding channels may reposition text annotations
outside of the visible area. Click and hold down the text annotation tool to
activate the text annotation popup menu. The “Autoposition Hidden
Annotations” option automatically
repositions all annotations so they are visible.

Clear all

Click and hold down the text annotation tool
to activate the text annotation popup menu.
The “Clear annotations” option will clear
annotations for a selected channel or for all
annotations. This action cannot be undone, so
a prompt will appear confirm the selection:

Selection Palette

Many tools within AcqKnowledge are based around the selection. The selected range of data in the graph is
used as the source for measurements, waveform editing, transformations, and other operations. The Selection
Palette is a floating dialog that can be used to precisely enter the selection. See page 453 for Selection Palette
guidelines.
Start/Stop Toolbar
toggles to

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Channel Button Toolbar
Toggles the display of channel number and label region.

Event Toolbar
Select an event to enable the toolbar. (Events and Event bar must first
be enabled via Display > Show Events and Event bar). Use the arrows
to move forward or backward through all event marker types. (If
events are placed in the waveform, the arrow navigation will locate
events in the selected channel only.)
Click the event palette icon to generate the event palette.
Focus Area Toolbar
Use the Focus Area feature to isolate portions of data that are of
particular interest within a graph. Focus Areas can be defined, added,
labeled and deleted within any portion of the graph. For more details
on creating and using Focus Areas, see page 92.
Measurements Toolbar

Click the down arrow for quick access to measurement preset
functions, including pre-loaded options for organizing
measurement rows and columns. Or create and save custom
measurement display presets by choosing New Preset, entering a
name for the preset and clicking OK.
Right-click in the measurement bar for quick access to options for
copying measurement and using linear interpolation.
Custom Toolbars for Transformations and Analysis
AcqKnowledge 4.1 and above allows users to construct new
toolbars for triggering transformations and analysis. An arbitrary
number of toolbars may be created and populated with buttons
that can trigger any menu item in the Transform and Analysis
menus. The contents of the text-only buttons match the menu
item title. These toolbars will persist for each user and their
positions and visibility within the graph window will be retained.
Transformation toolbars may be accessed via the
"Customize Toolbars" button.

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Toolbar Position Retention and Changes
Toolbars can be rearranged within the graph
window or detached and turned into floating
tool windows. Any modifications made by
the user to the position of most toolbars
within the graph window will be stored as an
application preference and used for new
graph windows as they are created and graph
files that are opened from disk. Default
toolbar positions have changed to move the Start button and cursor tools to the top of the graph window; users
preferring the ordering in previous versions may manually reposition the toolbars. Toolbar Tooltips may be
deactivated when toolbars are detached from a graph.
Axis Controls
If axis controls interfere with scale values,

adjust the opacity slider in Preferences > Graph
to hide the icons until the cursor passes over them
.
A “scaling” button acts as a shortcut for opening the grid and visible range dialog, similar to doubleclicking the axis. If a channel corresponds to an analog channel that has calibration steps, a calibration
wrench button be displayed and will open the hardware calibration dialogs. This allows visual access
to commonly used operations for channels.
Module dependent: Generate the scaling or calibration dialogs for the channel input or calculation.
Analog inputs will open to the scaling dialog and channels that require calibration will initiate a repeat
calibration routine.

Use Display > Channel Info or use the channel’s contextual menu to display the Channel Information.
Toggle the lock icon at the right edge of the window to change the lock state of the grid for horizontal
axis or the channel. Unlocked is open (latch to right); locked is closed.

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Enable Cursor Tools During Acquisitions
Enables access to cursor tools while recordings are in progress. (AcqKnowledge 4.2 and higher only, Display
> Preferences > Graph)
Button Transparency
Scaling, calibration, transformation history, and grid lock buttons may be made semi-transparent to allow
units, axis values, and other information underneath the buttons to remain visible. The Preferences > Graph
panel includes an “Axis controls” slider to change drawing from fully transparent to fully opaque.
When the mouse is positioned within the buttons, they will be drawn fully opaque regardless of transparency
setting. The transparency is shared by the scaling, calibration, transformation history, and grid lock buttons
and is the same for all open graphs as this is an application-level preference.
Customizable Chart Track Dividers
Users may change the color used to draw the dividers between channels tracks The Preferences > Graph panel
contains "Chart Track Divider Appearance" options.
Plotting Background Colors
Customizable background colors for individual graph channels are available in Preferences > Graph >
Plotting Background Colors.
Spectrum Analyzer Palette
The Spectrum Analyzer Palette provides a dynamic display of the frequency
decomposition of data, in real time or post-acquisition.
See page 458 for details.
X

X

Keyboard Shortcuts
Menu Option
Program info

Windows OS
Help > About AcqKnowledge

Quit

Ctrl + Q

Hide AcqKnowledge

minimize (corner box)

Mac OS
Help > About
AcqKnowledge
Q
minimize (corner box)

File menu
New

Ctrl + N

N

Open

Ctrl + O

O

Open > Recent

Ctrl + 1 (for most recent)

+ 1 (for most recent)

Open for Playback

--

--

SMI Begaze Import
Close

Ctrl + W

W

Save

Ctrl + S

S

Print

Ctrl + P

P

Quit

Ctrl + Q

Q

Save As
Save Selection As
Save Journal Text As
Send E-Mail Attachment
Page Setup

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Menu Option

Windows OS

Mac OS

Edit menu
Undo (when applicable)

Ctrl + Z

Z

Cut

Ctrl + X

X

Copy

Ctrl + C

C

Paste

Ctrl + V

V

Clear (journal)

none

none

Clear All
Remove Last Appended Segment

Use the Rewind toolbar icon

Insert Waveform
Duplicate Waveform

Ctrl + D

D

Select All

Ctrl + A

A

Remove Waveform
Create Data Snapshot
Merge Graphs
Clipboard
> Copy Measurements
> Copy Wave Data
> Copy Graph
> Copy Acquisition Settings
> Copy Data Modification History for
All Channels
> Copy Data Modification History for
Selected Channels
> Copy Focus Area Summary
> Copy Event Summary
Journal
> Paste Measurements
> Paste Wave Data
> Paste Graph
> Paste Acquisition Settings
> Paste Modification History for All
Channels
> Paste Modification History for
Selected Channels
> Paste Focus Area Summary
> Paste Event Summary
> Manage PDFs
> Show Journal

Ctrl + K
Ctrl + L

K
L

Ctrl + U

U

Ctrl + M
Ctrl + /

M
+/

Ctrl + J

J

Transform Menu
Recently Used
Digital Filters
Fourier Linear Combiners

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Menu Option

Windows OS

Mac OS

Math Functions
Template Functions
Integral
Derivative
Integrate
Smoothing
Difference
Resample Waveform
Resample Graph
Expression
Delay
Rescale
Waveform Math
Slew Rate Limiter
Analysis menu
Find Cycle

Ctrl + F

F

Find Next Cycle

Ctrl + E

E

Find All Cycles

Ctrl + R

R

Autoscale Single Waveform

Ctrl + Shift + Y

Shift Y

Autoscale Waveforms

Ctrl + Y

Y

Display menu
Tile Waveforms

Overlap Waveforms
Autoscale Horizontal
Show All Data

Ctrl + H
Ctrl + Shift + D

H
Shift

D

Show Default Scales
Zoom Back

Ctrl + - (minus key)

-

Zoom Forward

Ctrl + = (equal key)

+

Ctrl + Shift + =
Ctrl + Shift + L

+ Shift + =
+ Shift + L

Reset Chart Display
Reset Grid
Adjust Grid Spacing
Set Wave Positions
Wave Color
Horizontal Axis
Show > Selection Palette
> Location Palette
Customize Toolbars
Channel Info
Preferences
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Menu Option

Windows OS

Mac OS

Size Window
Cursor Style > Arrow
> Selection
> Zoom

Ctrl + B
Ctrl + I
Ctrl + G

B
I
G

Ctrl + Shift + T

+ Shift + T

Create Data View
Create Focus Area
Organize Data Snapshots
Show All Data Snapshots
Load All Data Into Memory
Script Menu
Script Step
Hardware Device Menu
Set Up Data Acquisition >
· Channels
· Length/Rate
· Event Marking
· Segment Labels
· Stimulator
· Trigger
· Sound Feedback
Set Up Advanced Averaging
Show Input Values
Show Manual Control
Show Gauge
MP160/150 Info
Autoplotting

Ctrl + T

T

Scrolling
Warn On Overwrite
Organize Channel Presets
Set Up Linked Acquisitions
Exit All Playback Graphs

Ctrl + Exit Playback Mode

Option + Exit Playback
Mode

Manage Hardware Connections

Start/Stop Acquisition

Ctrl + spacebar

Ctrl + spacebar

Delete recorded data
Deletes all recorded data segments

Ctrl + Rewind button

Option + Rewind button

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Window menu
Select Next Tab
Select Previous Tab

Ctrl + Tab
Ctrl + Shift + Tab

Tab
Shift + Tab

Ctrl + I
Ctrl + B
Ctrl + G

I
B
G

Help
Tutorial Screencasts from the Web
Open AcqKnowledge Tutorial
Application Notes from Web
Open AcqKnowledge Manual
Open Hardware Guide
About AcqKnowledge
Cursors
I-beam
Arrow (pointer)
Zoom
Grid
Event
Jump to
Annotation

Horizontal Scroll Location In chart, scope, or stacked plot mode (i.e., all but X/Y)
these keyboard shortcuts can be used to scroll to various
parts of the graph.
Home

Jumps to t = 0 (i.e., places first sample of data flush with
left of graph window)

End

Jumps to the end of the currently selected waveform (i.e.,
places last sample of data of the selected waveform flush
with right of graph window)

Page Up

Scrolls backward in time one full screen (i.e., places
leftmost sample of previous visible area at the right of the
new visible area).

Page Down

Scrolls forward in time one full screen (i.e., places
rightmost sample of previous visible area at the left of the
new visible area).

Tooltips
Tooltips is an assistance feature to help novice users learn how to use AcqKnowledge. Text is generated to
describe the software functionality of the item under the mouse. Unavailable items/controls will indicate why
they are unavailable. Tooltip visibility can be controlled by selecting or deselecting the “Show Menu
Tooltips” checkbox in “Preferences > Other.”

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Mouse Controls
Contextual menu items correspond to the AcqKnowledge main menu state.
The following options can be accessed with a right-click for Windows or Control-click for Mac.
§ Mac OS only: If the mouse is over a portion of the graph that has a context menu available, the
cursor will change to an arrow with a menu.
Graph window

Journal window

Horizontal Scroll

Vertical Scroll

Measurements

Events

Mouse Scrollwheel Support
The scrollwheel operates on whatever window is underneath the mouse; this window does not need to be the
topmost window. Many third-party mice include scrollwheels, scrolling balls, or trackpads to allow for quick
access to navigating through a document. Mice may provide two separate controls, one for scrolling vertically
and one for scrolling horizontally.
AcqKnowledge supports horizontal and vertical scrolling using the scrollwheels on the mouse. Scrolling is
supported in graph windows, journal windows, the event list in the event palette, and a number of other
dialogs and windows that contain scrollable lists. A dynamic zoom operation can easily be performed in an
AcqKnowledge graph channel by holding down the Ctrl key (PC) or the Option key (Mac). Scroll ‘up’ to
zoom in and ‘down’ to zoom out. (Zoom operation supported in AcqKnowledge 4.2 and higher)
· Mac OS: To increase the scroll speed, hold down the “Option” key while using the scrollwheel.

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Modification History
Modification history provides the ability to track operations performed on channel data. This gives a visual
indicator of whether operations have been applied to a channel and a record of the sequence of operations
and parameters for the operation. The channel history is viewed in the "Channel Info..." dialog. This dialog
is accessible via the “Channel Info” option in the graph channel’s contextual menu or the Display >
Channel Info menu item.

Cancelling Transformations and Transformation Progress Bar
Transformation cancel support offers Cancel buttons for in-progress dialogs that indicate the completion
status of threaded transformations. Progress dialogs have also been enhanced so the textual message
includes a graphical progress bar with the percentage that is completed. If the progress message does not
contain a percentage, an indeterminate progress bar will be displayed.
AcqKnowledge 4.1 and higher extends the analysis package to display dialogs while analysis routines are
in progress. This progress dialog contains a cancel button which may be used to terminate the analysis
before it is complete.
The event tool allows events to be inserted on a graph with the mouse. When performing event editing,
three new context menu shortcuts have been added to help make the process quicker:

§

Assign Current Event Type: Right-click an area with no data to set the type of event that will be
inserted on the next left-click of the mouse.

§

Event Palette: Toggles event palette displays.

§

Edit event: Right-click a specific event to open the event
palette to Selected Event controls for the event that was
right-clicked.

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Typed Event Label Drawing Improvements
The Event system has been enhanced to allow different drawing options for channel-specific events when
they are drawn in the data plotting area. These drawing options are applied to event labels, event
amplitude markings, and event time location text. The following drawing options may be customized:
§

Font (including family, size, italic/bold, and other options)

§

Rotation angle of text baseline

§

Text alignment (left, center, right)

Choose MP160 and MP150 Help Button
A Help button is available in the “Choose MP160” or “Choose MP150”dialog that appears when the
application is attempting to locate an MP device. The Help button opens a "Troubleshooting MP
Communications.pdf" document from the application's User Support System. This troubleshooting guide
provides common information from Technical Support for decoding the network blink states of the MP
unit and other steps to take to troubleshoot why the MP unit and computer cannot communicate properly.
Tooltips
Channel Label, Units Length and Tooltips
Character length limitations for channel label and units have been expanded: labels may now be up to
1032 characters and units may be up to 511 characters. Tooltips have been added to display the full
channel units when the vertical axis is moused over. Tool tips do not wrap, so long labels may extend
beyond the visible viewing area of the computer monitor.

Graph Window Tooltip Improvements
Several of the toolbar buttons and the Start/Stop button in the graph window are associated with keyboard
shortcuts that may be used instead of the buttons. Tooltips for these toolbar buttons display the corresponding
keyboard shortcuts. Toolbar Tooltips may be deactivated when toolbars are detached from a graph.

Menu Item Tooltips
Menu item tooltips display informational text about how menu items may be used. (Similar text was
displayed in earlier versions of AcqKnowledge for Windows in the status area and in earlier versions of
AcqKnowledge for Mac as Balloon Help). Analysis menu tooltips have been expanded to provide more detail
regarding the types of analysis that are performed by the selected item.

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Editing and Analysis Features

Overview
This section provides a brief overview of some of the most frequently used AcqKnowledge features and
functions. For more detailed information about specific features, turn to Chapters 9 through 13.
With AcqKnowledge running, choose File > Open Sample Data File and select the file called “demo
data.acq.” The screen should look like this:

Edit menu functionality during acquisition
The following Edit menu functions may move or alter memory and cannot be performed during acquisition:
Undo, Cut, Clear, Clear All, Paste, Insert Waveform, Duplicate waveform, and Remove Waveform.
Scroll bars
Note that there are four channels of data in this file (Heart Rate, ECG, EEG, Resp, EMG Raw, EMG,
Integrated EMG). Although this record is 30 seconds long, only a few seconds are displayed on the screen at
one time. Move to different locations in the record by moving the scroll box at the bottom of the screen.
Dragging the box left moves to earlier points in time, and moving right displays events closer to the end of the
record. Clicking on the arrows at either end of the horizontal scroll bar allows moving to different points in
time at smaller increments.
A vertical scroll bar is on the right side of the screen, and. When clicking the scroll arrow at the top of the
box, note that one waveform appears to move down within its “track” on the screen. Moving this scroll box
changes the amplitude offset of a selected channel. As with the horizontal scroll bar, either move the box or
click the arrows.

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Scaling
Horizontal axis
Click the horizontal scale (above the scroll bar) to generate a dialog where values can be entered for units
per division and horizontal scale offset.

Time Scale
The time interval (units per division) between the on-screen grid marks. There are four vertical divisions
per screen, and the default is 2.00 seconds per division, so eight seconds of data will be displayed on the
screen display. Entering a larger value will display more of the record, and entering a smaller value will
display less.
Initial offset
The time corresponding with the first data point displayed. For example, to display the middle 1/3 of the
data file (assuming the record is 30 seconds long), set the offset to 10 seconds and the seconds per
division to 2.5 seconds.
Precision
Controls number of decimal places following whole units appearing in the horizontal axis.
Hold Relative Position for Append acquisitions
This option is active in Append acquisition mode only. When checked, the display for appended
acquisitions will show the same relative position with respect to the start of acquisition. This is
convenient when performing short-duration; high-speed acquisitions where a user needs to zoom in on a
signal of interest and have the relative position (from the start of acquisition) stay the same.
When zooming in on a section of data within a recording segment, the next appended segment will “hold”
its relative horizontal position (start and end times with respect to the start of each segment).
When using the I-beam tool to select a sub-section of the data, this sub-section will hold its relative
position and update the measurement values on each subsequent appended segment.
If the selected data area falls within two or more appended segments, this feature is not implemented.
Example of Hold Relative Position feature:
Action Potential setup: 100,000 samples/sec, 50 millisecond recording length, Append mode and
stimulator set to output 19 milliseconds after the start of the recording.
After the first recording segment, the zoom tool is used to expand the area of interest (top figure below).
The I-beam cursor is used to select a measurement area around the nerve response. The “P-P”
measurement shows the nerve response amplitude. After clicking Start and recording the next segment,
the relative position of both the horizontal time scale and the measurement selected area, with respect to
the start of recording is maintained (bottom figure below). This makes it very easy to measure the changes
in the amplitude of the nerve response with changes in stimulus level.

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Global Grid Settings
Opens dialog for applying master grid settings for all channels. For more details, see Grids on page 80.
Channel Grid Settings
Opens dialog for selectively applying grid settings to one or more channels. For more details, see Grids
on page 80.

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Vertical (Amplitude) axis

Clicking in the vertical scale area (where the amplitude of each channel is displayed) generates the Set
Screen Vertical Axis dialog, where values can be entered for units per division and vertical scale offset.
Scale
Determines the limits of the viewable vertical axis scale (usually Volts). AcqKnowledge divides each
channel into four vertical divisions. When data is displayed in chart mode, each “track” is divided
into four divisions. When data is displayed in scope mode (or if there is only one channel of data) the
entire screen is divided into four intervals. To increase the apparent amplitude for a given channel, set
this value to a smaller number; entering a larger number will cause the waveform to appear to have
less variability.
Midpoint
Refers to median displayed value for a particular channel. A checkbox to the left of each of these
options allows these scaling options to be applied to all channels. By default, the selected scaling
options will only apply to the channel indicated in the dialog. To apply these to all channels, enable
all checkboxes.
Precision
Controls number of decimal places following whole units appearing in the vertical axis. Can be
applied to selected or all channels.
Apply to all channels
Applies settings selected in the various dialog options to all channels.

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Range Guide (MP36R Hardware only)
The Range Guide is a green bar that runs along the vertical scale in the graph
window for analog channels (see right).
It displays the maximum signal range for the Gain established for that channel.
The Range Guide can be used as a visual aid to establish the proper Gain.
The MP36R hardware measures the actual input voltage and compensates for the
Gain. As Gain increases, the peak-to-peak of a waveform stays constant but the
resolution increases.
Proper Gain will have a smoothing effect on the signal. For the best resolution,
establish Gain such that, allowing for baseline drift (if applicable) and the
maximum peak-to-peak of the signal, the maximum signal display is close to the
maximum range. If the signal is clipped (Fig. 1), lower the Gain. If the signal is too small compared to the
range (Fig. 2), increase the Gain to improve signal resolution. Gain settings create a trade-off between range
and resolution.

Fig.1: “Clipped” signal
Fig 2: Signal too small compared to range
Different gain settings applied to the same signal source show that
Higher Gain = better resolution + lower range (Figure 3, top)
Lower Gain = worse resolution + higher range (Figure 3, bottom)
To display the full range (Fig. 2 vs. Fig. 3, for example), adjust the
Vertical Scale.
The Range Guide will always reflect changes made to the channel
Scaling.
To quickly see the total range of each input channel, select
Optimize Ranges from the Display menu. This will automatically
adjust the upper and lower viewable limits of the Vertical Scales
Fig. 3
for all channels. For more information on Optimize Ranges, see page 446.
NOTE: Range Guide and Optimize Ranges are not available when using MP160 or MP150 hardware.

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Adaptive Scaling
Adaptive scaling uses the data to automatically determine the appropriate visible range for the data.
As the data changes or the baseline shifts, the visible area shifts along with the data to ensure that data
will always be plotted on the screen. Rather than limiting data visibility to a fixed voltage range, the
range adjusts for factors such as background noise, electrode movement, EMG interference,
disconnection, etc.
Adaptive scaling can be applied to channels individually and can be unique for each Data View. A
“settings” button is activated when to “Use adaptive scaling” is enabled.

Scaling changes will be applied whenever the domain of the plot area is changed. This includes
manual changes to the horizontal scale, horizontal scrollbar use, horizontal auto-scrolling when
dragging out a selected area, auto-scrolling or auto-plotting during acquisition, initial enabling of
adaptive scaling and auto-scrolling when executing Find Cycle/Peak functions.
Show Textual Value Display
This option enables a real-time display of the most recently acquired values on a channel-by-channel
basis, providing amplitude information akin to clinical monitoring displays. This can be useful for
obtaining a quick visual numerical summary of incoming data while a recording in progress.

In post-processing, the value display can be seen by performing a “spot measurement” (clicking the
arrow cursor on a single data point).

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Textual value display in spot measurement mode
Textual value display can be customized for font, color and style, and positioned at the top or bottom
of any selected channel. These options can be configured independently per channel or applied to all
channels.
·
·

In chart and stacked chart modes, the value display will appear for all enabled channels.
In scope mode, the value display will appear only if the selected channel has the value display option
enabled.
· Textual value display is not supported in XY mode.
To enable textual value display:
Click on the vertical axis area to open the setup dialog and enable the “Show textual values display”
checkbox. Use the Settings button to set the font style, size and color.

Channel Grid Settings
Opens dialog for selectively applying grid settings to one or more channels. For more information,
see Grid Details on page 80.

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Grid Details
Customize the grid behind the waveforms displayed in graph windows in a number of ways.

Grid Lock/Unlock
Each scale has a small padlock in the lower right
hand corner that displays the current state of the
grid lock for that axis and channel. Click the
padlock to change the lock state.
§

Unlocked grid—the number of grid lines
and their pixel spacing on screen is kept
constant through zoom and scaling
operations

§

Locked grid—the grid lines themselves
are maintained at constant values through
zoom operations, e.g. a grid line which is
located at .753 volts when the grid is
locked will continue to be located at .753
volts regardless of changes in scale.
Grids can be locked and unlocked on individual channels.
§ The lock for the horizontal axis is shared by all channels.
§ The vertical scale can be locked and unlocked independently.
The lock state of the grid can also be changed through the axis dialogs displayed when the mouse is clicked
on the axis scale values in the graph window.
§ Click the “Lock units/div” checkboxes.

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Grid Scaling
When the grid is locked, the scaling factors controlling how much data is visible on the screen (the distance
between consecutive major lines of the grid and a fixed location for one of the lines of the grid) are specified
differently. When the grid is unlocked, these scaling factors do not affect the grid.
The Grid Spacing option specifies the scaling factors and whether or not to “Show minor divisions” on the
grid display. Changing these values only affects the grid display, not how the waveform is scaled.

§ Vertical grid: the total range of vertical units displayed per track is specified (Major division) along with
the first value that should be displayed (First grid line).
§ Horizontal grid: the scaling factors are specified in how many seconds of data should be visible on the
screen (Major division) and the time offset of the left hand side of the display (First grid line).
§ Settings can be applied to a selected channel or all channels. (Controlled by checking or unchecking
‘Apply to all channels”).
Adjust Grid Spacing
To modify the horizontal and/or vertical grid spacing, choose “Display > Adjust grid spacing.” This will
generate the aforementioned dialog for modifying the locked axes of the selected waveform. (“Lock vertical
grid” and “Use channel specific horizontal grid” must be enabled in order for the gridline fields to become
active). Enter the desired values and click OK.
§ Settings can be applied to a selected channel or all channels. (Controlled by checking or unchecking
‘Apply to all channels”).
The following Grid items can also be selected by right clicking with a graph channel and using the contextual
menu.
Grid: Toggles Grid display on and off.
Adjust grid spacing: Use to change Grid spacing
for one or all channels (divisions between
gridlines and position).
Grid Options: Use to change Grid display for one
or all channels (Color, width, style, dash length,
dash spacing, and scale adjustment position).
Grid Preset: Use to select/create /save custom
Grid presets and organize them in a list. (left)

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Example of channel specific horizontal grid

Note in figure on left, the horizontal time scale division is
one second per division in the graph channel, but two
seconds per division in the horizontal axis. (Green bar area)

Horizontal Axis Grid Controls

§ Global Grid Settings: Brings up dialog specifying grid settings used in the shared Horizontal Axis of
the graph.
§ Channel Grid Settings: Brings up the ‘Adjust grid spacing dialog’ referred to on previous page.
Individual channel-specific grid settings take priority over the Global Grid Settings. If no channel-specific
grid setting exists, the Global settings are applied.
Grid Tool

The Grid Tool allows divisions of the grid to be specified with the mouse. This tool has four states:
Inactive
The cursor changes to a circle with a line running through it. The grid
cannot be adjusted since both the horizontal and vertical axes are unlocked.
Horizontal axis locked
The cursor changes to a horizontal line. A mouse click and drag will change
the location of the horizontal lines of the grid.
Vertical axis locked

The cursor changes to a vertical line. The tool can be used to adjust the
vertical spacing of the grid.

Both axes locked

The cursor changes to a crosshair. The rectangle of a full grid division can
be drawn over the data. Adjust the spacing of locked grid lines underneath
the waveform.
If the “Alt” (PC) or “Option” key (Mac) is held down for the Grid Tool in any of the active
modes, an ellipsis will appear under the cursor. After a mouse click or drag, a Grid Settings
dialog will be generated. This dialog is functionally similar to the grid dialogs accessible via the

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axis settings dialogs.
§ Based on lock status, the dialog will allow the adjustment of Horizontal, Vertical or combined settings.
§ The values displayed in the dialog correspond to the grid ranges that were just drawn out on the screen
with the grid tool if a mouse drag occurred.
§ If the mouse was simply clicked, the current grid settings are displayed.
§ This dialog allows the grid drawn out with the grid tool to be made more precise.
Grid Reset
To return to the original grid, choose “Display > Reset grid.”
This will reconstruct the default, unlocked grid of four divisions per screen with solid light gray grid lines.
Grid Options
The major and minor grid lines can be further customized with spacing, number of divisions, and different
colors and dashing styles. These are modified under the dialog generated via Display > Show > Grid options.

Line color
Line width
Dash style
Dash length
Spacing
# of Divisions

Click the color well to generate a color chooser.
Adjust the corresponding slider.
Select a style (solid or broken) from the pop-up menu.
Adjust the corresponding slider (for any dash mode that is not a solid line).
Adjust the corresponding slider (for any dash mode that is not a solid line).
Enter a value in the text field to set the maximum number of minor grid lines
to be displayed in a single major grid division.
Apply visual settings to all channels
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When checked, the visual settings for major and minor grid lines are applied to all
channels. When unchecked, the settings will be applied to the selected channel only.
Scale Adjustment
Select whether to use Start/End or Range/Midpoint parameters to determine
horizontal and vertical scale adjustments. Applied only when grids are locked.

10 sec. Horizontal Scale adjustment set to ‘Start/End’ parameters

10 sec. Horizontal Scale set to ‘Middle Point/Range’ parameters

To undo the selections and return to the original grid, choose “Display > Reset grid.” This will reconstruct the
default, unlocked grid of four divisions per screen with solid light gray grid lines.
Friendly Grid Scaling
Too much precision can create numbers that are difficult to quickly interpret, so “friendly” grid scaling
adjusts the range to the nearest possible whole numbers. For example, it’s easier to comprehend
4.1000000 than 4.1427385. Unlocked grids always restrict precision to the minimum needed for a given
magnitude. This produces a “friendly” scale that makes it easier to determine the range between the
gridlines when data is formatted for display or printing.
With unlocked horizontal grids, the horizontal scale values printed on a graph may not match the
horizontal scale values displayed on the application screen. For example, horizontal scale values
Displayed in the application:
0.00000 7.50000 15.00000 22.50000
Printed:
0.00000 7.50125 15.00250 22.50375
The precision will only match when using the “Visible area” print option. With selected area or entire
graph options, the precision will not match when grids are unlocked because friendly grid scaling is
applied on screen, but is not used during printing where the range is fixed to fill the entire page.
Note that the Zoom tool and vertical autoscale may produce different results. To accommodate the grid
precision, the Zoom result may be slightly more than specified in the zoom box. For precise correlation
from selected area to result, lock the grids (horizontal and vertical). Precision is not restricted for locked
grids or display ranges manually entered in the axis setting dialogs.
Watch the AcqKnowledge Grids video tutorial for a detailed demonstration of this feature.

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Journal Details
To create a journal, choose File > New > Graph-Specific Journal or Independent Journal or choose
Display > Show >Journal or Edit > Journal > Show Journal.
Once a Journal is open, text and data can be entered. To enter text, just begin typing when the journal is open.
AcqKnowledge will automatically “wrap” the text to fit the screen width.
In addition to formatting tools, Time Stamp, Date Stamp and Auto Time functions are
available in the journal window.
· Time and Date stamps refer to the computer’s clock to record the time and date, respectively, directly
into the Journal.
· Auto Time function records the time at the instant the carriage return is pressed, which is useful for
tagging commands as data is collected.
Measurements and data may also be pasted into an open Journal. To paste measurements into an open
Journal, select an area and choose “Paste measurements” from the Edit > Journal menu. Paste to Journal
functions only work if a Journal is open and vary for each journal type:
§ Graph-specific journals can only receive measurements and wave data from their associated graph
view
§ Independent Journals can receive measurements and wave data from any open graph. Results will be
put into both the graph-specific journal and the independent journal. Use Journal Preferences to autopaste to an independent journal if desired.
Set the Journal Preferences (page 468) to simultaneously record measurement name and units or control Event
(marker) paste functionality and detail.
To paste waveform data into a Journal, select an area and choose “Paste Wave Data” from the Edit >
Journal menu. Allow several seconds for the text file to be written. The result is a text file of the wave data
pasted into the active journal.
X468

X

TIP: When pasting a graph into a Journal: Pressing the Ctrl key (PC) or the Alt key
(Mac) will launch a dialog allowing the image to be resized prior to pasting.

A useful feature of the Journal is that it works in connection with the Cycle/Peak Detector and other
measurement functions to paste in values from waveform data for further analysis.
In the example above, the peak-to-peak and delta t measurements were pasted from the open graph window to
the Journal. See the Journal paste section on page 293 for more information on how to paste information to
Journal files.
Use Save as/Open Journal Template to retain SOP text, or standardize lab/computer details for record
keeping.
X293

X

Journal Contextual Menu
The Journal contextual menu allows quick access to common text
editing functions, as well as a tool for easily re-docking the Journal
window to any edge of the graph. To activate this menu, right-click
anywhere within the Journal window.

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Rich Journals
The AcqKnowledge Journal includes powerful rich text editing tools, offering advanced word processing
functionality. The following toolbar options are available within the Journal window:
· Font family
· Font style: bold, italic, underline
· Paragraph alignment: left, right, center, justify
· Font color
The following items can be pasted or embedded into the Journal text:
·

Images
Numbered lists
· Bulleted lists
· Tables
· Numerical statistics or expressions
Images must reside within a document in order to be pasted into the Journal. Pasting image files directly from
a location such as the Desktop is not currently supported.
·

Journal Toolbar Buttons
The Journal toolbar controls all formatting functions within the Journal window. Although the settings
customized in this toolbar are retained within a saved Journal, global default settings for subsequent Journals
are not overridden. To change the global defaults, the overall Journal Preference settings must be modified.
(Edit > Journal > Preferences). For more information, see Journal Preferences on page 468.

Journal Toolbar Icon

Function

Explanation

Clear

Clears text from Journal window

Replace

Replaces Journal text with contents of external text file

Save

Saves selected or full Journal text to an external text file

Page Setup

Opens dialog for modifying Journal text print configuration

Print

Prints the Journal text to the default printer

Time stamp

Inserts current time into Journal

Date stamp

Inserts current date into Journal

Time AND Date

Inserts current time and date into Journal when Enter/Return key is pressed

Font

Use to select font type and size for Journal session

Text style

Use to bold, italicize or underline text

Text alignment

Aligns paragraph text to left, center, right or justified position

Font color

Selects color of Journal text

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Numbering

Toggles text numbering on and off

Bulleting

Toggles text bulleting on and off

Increase indent

Increases indent in a bulleted or numbered list*

Decrease indent

Decreases indent in a bulleted or numbered list

Insert link

Adds hyperlink to Journal

Table

Inserts a table into the Journal

Table row

Adds a row to the table **

Table column

Adds a column to the table

Delete table row

Removes selected row from the table

Delete table
column

Removes selected column from the table

Merge cells

Merges selected cells within the table

Split cells

Splits selected cells within the table

*Active only when cursor is positioned within a bulleted or numbered list.
**Additional table tools are active only when a table is present.
NOTE: If the AcqKnowledge graph or Journal windows are decreased in size, the Journal toolbar will
become truncated and some buttons may no longer be in view. Buttons no longer visible on the toolbar can be
found in drop-down menus indicated by arrows. (See below)

Journal Numerical Table Tools
The Numerical Table Tools function allows easy insertion of measurements and numerical data into a Journal
table, which can then be computed and evaluated via basic mathematical operations and expressions. This
eliminates the need to export data to a spreadsheet application in order to validate statistics gathered during
the course of an experiment.
Numerical Tools operations permitted within a Journal table:
§
§
§
§
§

Insert a single measurement value
Insert all measurement values
Insert all measurement values with header row
Sum, Mean and Standard Deviation statistics for table rows and columns
Expression evaluation

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Menu Item

Function

Undo

Removes previous operation

Select All

Selects all cell contents

Insert Single Measurement Value

Pastes single selected measurement value into cell

Insert All Measurement Values

Pastes all measurement values into cells

Row Statistics

Performs Sum, Mean or Standard Deviation operations on row data

Column Statistics

Performs Sum, Mean or Standard Deviation operations on column data

Evaluate Expression

Performs mathematical operations and functions on cell contents

Word Wrap

Wraps text within visible Journal area. (Does not apply to table cells)

Example of Sum, Mean or Standard
Sum, Mean or Standard Deviation operations can be easily performed on table data. Right clicking within a
cell opens a contextual menu containing available operations under ‘Row’ or ‘Column’ statistics. Choose an
operation, and the result will appear in the selected cell. (See sum example below)

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Example of Evaluate Expression
This feature works very much like Excel®. Simply enter the cell identifiers into an empty cell, then right-click
and choose ‘Evaluate Expression.” The formula occupying the cell will be computed and be replaced by the
result. The mathematical operations and functions available for standard Biopac Expression syntaxes may be
used. (Transform > Expression). Expressions can be created beforehand then copied and pasted into a
Numerical Tools Table cell.

If the expression syntax used is incorrect or invalid, a warning dialog will appear.

TIP: To correct a mistake, use the Ctrl+Z (PC) or Command+Z (Mac)
keystroke to restore the previous cell data. Multiple levels of undo are
supported.
Adding a hyperlink to the Journal
Use the Journal hyperlink
toolbar button to insert a link to a web address into the Journal. This
operation is very similar to adding regular text.
1. Click into the Journal at the desired position for the link to appear.
2. Click on the “Insert link” toolbar button
3. Add the web address and some text identifying the link into the URL and Text fields.
NOTE: For the link to be active, the http:// designation must be entered before the web address.

4. Click OK, and the live link will appear in the Journal.
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·
·

To format the link text, select the link and use the Journal formatting tools.
To edit the link text, position the cursor at the end of the link and use the arrow keys to
navigate to the desired portion. Backspace to remove unwanted text and type in new text.

·
·

To delete a link, select the text and use the Delete key.
Once a link has been created, the URL portion cannot be edited from within the Journal, nor
can the original “Insert hyperlink” dialog be recalled. If the URL itself needs to be edited, a
new link must be created using the “Insert Link” button.
NOTE: Once a hyperlink is inserted into the Journal, entered additional text is also treated as a hyperlink. To
nest hyperlinks among existing text:
1. Insert hyperlink(s) at the end of Journal text.
2. Select the hyperlink text, right-click and choose “Cut” (or Ctrl+X).
3. Paste the hyperlink into the text at the desired location. (Ctrl+V) Pasting the link
into existing text does not affect formatting of subsequent text.
Embedding PDFs in Journals
Multiple PDF files can be pasted into a Journal as convenient tabbed windows with all formatting and
graphics intact. To do this, simply choose Edit > Journal > Manage PDFs, browse to the location of the
desired PDF files and choose “Embed new.”
TIP: It’s possible to also embed PDFs while in the Journal by right-clicking in the Journal window and
choosing “Manage PDFs” from the contextual menu.
The hyperlink tool described above can also be used to insert links to an embedded PDF. Simply choose
“PDF” and select the desired PDF display option:
Display only – Toggles to the embedded PDF’s tab and displays it in the Journal window.
Display and jump to page number – Toggles to the embedded PDF’s tab and jumps to the entered page
number.
Display and jump to destination named – Toggles to the embedded PDF’s tab and jumps to a named
destination in the PDF. (Enter the exact name of the destination present in the PDF and enter the desired text
to appear in the Journal link.)
Text – Use this field to enter identifying text for the PDF hyperlink. (Any unique identifier can be used.)

Note that a defined destination must be present in the embedded PDF in order for the “Display and jump to
destination” feature to function.
For more details on managing embedded PDFs, see page 295.
Watch the AcqKnowledge Journal video tutorial for a detailed demonstration of this feature.

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Select a waveform / channel
Although multiple waveforms can be displayed, only
one waveform at a time is considered “active.” Most
software functions only apply to the active waveform,
which is also referred to as the “selected” channel.
Selecting a channel allows for highlighting all or part of
that waveform, and enables transformations to be
performed on a given channel.
In the upper left corner of the graph window there are a
series of numbered buttons that represent each channel
of data. The numbers in the buttons correspond to the
channel used to acquire the data (the specifics of setting
up channels are discussed on page 30). In the sample
file, ECG channels are represented by Channel 1, with
respiration on Channel 2.
To select a channel, position the cursor over the channel button that
corresponds to the desired channel and click the mouse button or position the
cursor on the waveform of interest and click the mouse button.
Note that the selected channel box appears depressed and the channel label to
the right of the channel boxes changes to correspond to the selected channel.
Additionally, the channel label in the display (on the left edge of the track) will
be highlighted for the active channel.
Channel Labels
Each channel has a label on the left and right edge of the graph window.
The left label is used to identify the contents of each channel (ECG,
Respiration, etc.).
The right label is used to denote the units for each channel’s amplitude scale
(usually scaled in terms of Volts).
When a channel is active, its label is highlighted and also
appears by the channel buttons.
To change the label for a given channel
§ during or before acquisition
(including Append mode)
revise the Hardware menu > Set Up Channels label text
§ post-acquisition / analysis only
click the left label enter the desired text in the dialog

AcqKnowledge 4 Channel label

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Show/Hide Channel

It possible to “hide” a waveform display without changing the data file. To hide a channel:
Windows: Alt+click in channel box.
Mac OS: Option+click in channel box.
Or, Alt+click on the channel number at the top of the channel label region.
To view a hidden waveform, repeat the appropriate key-click combination.
Alternatively, a channel can be shown/hidden via Display > Channel Visibility and checking/unchecking
the channel boxes in the Channel Visibility dialog. (See this Display menu option on page 449.)
When a channel is hidden, the channel button will have a slash through it. View a hidden channel by
holding down the Alt or Option key and clicking in the channel box again.
Focus Areas
Focus areas are comprised of selected time ranges within the graph. The purpose of the “Focus on” tool is to
easily isolate selected areas within the graph window for discrete analysis. This can be useful for identifying
areas of interest within a larger data set by highlighting, naming and storing them permanently in the graph.
When a focus area is assigned, that portion of the graph will appear shaded with borders appearing at the
edges. The assigned focus area label will be displayed vertically in the shaded area. (See following page for
example.) Focus areas may be defined via the “Focus on” toolbar above the graph, in the Output tab of the
Find Cycle Analysis feature, and once defined, can be selected within the setups for most Specialized
Analysis tools.
· Focus areas are graph level data, similar to events. Defining a focus area in one data view defines it
for all data views, etc.
· Focus areas are drawn only for graph windows in chart, stacked plot, or scope mode. They are
overlaid on top of data and events but underneath text annotations and selections.
· Focus areas may overlap.
· Each focus area is required to have a unique name.
Creating Focus Areas
To create a focus area:
1. Select an area of interest in the graph data using the I-beam tool or selection palette.
2. Create the focus area using one of the following methods:
·

Click on the “add”

·

Choose “Display > Create Focus Area.”

·

Right-clicking in the graph and choosing “Create Focus Area” from the contextual menu.

button to the right of the “Focus on” toolbar.

3. Name the focus area by typing into the label field.

The new focus area label will appear in the “Focus on” toolbar field.

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The new focus area and label will appear in the graph.

Multiple and overlapping focus areas can be created by selecting additional data and using the “add”
button.
Navigate quickly to a focus area time selection in the horizontal axis by selecting its label from the
“Focus on” toolbar field.

To remove a focus area, use the “minus” “Focus on” toolbar button.
TIP: To remove multiple focus areas at once, hold down the Ctrl key (PC) or Option key (Mac) and click
the “minus” focus area toolbar button.
(A confirmation dialog will appear before focus areas are
removed.)
To rename a focus area, use the “ellipses” toolbar button.
To highlight the current focus area, click the “highlight” button.
Focus Areas in Specialized Analysis
Most Specialized Analysis tools can be limited to running analysis on a focus area by choosing the “focus
areas only” option in the setup dialog.

Printing Focus Areas
Focus areas can be included or excluded from a printed graph by selecting or deselecting the “Print focus
areas” option in Print Setup.

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Focus area preferences can be modified by using Display > Preferences > Focus Areas. For further details
see pages 465 and 470.
For Find Cycle focus area options, see the Find Cycle section on page 341.
To create focus areas in analysis mode based on events or appended segments, see the Specialized
Analysis > Focus Areas section on page 393.
Watch the AcqKnowledge Focus Area video tutorial for a detailed demonstration of this feature.
Measurements
A convenient feature in AcqKnowledge is the popup measurement windows. A variety of
different measurements can be taken, and different measurements can be displayed from the
same channel and/or similar measurements from different waveforms. AcqKnowledge can
display measurements for the selected channel or for any other channel. By default,
AcqKnowledge displays measurements from the selected channel (as denoted by the “SC” in
the measurement boxes).
To select a channel for measurement, position the cursor over the part of the measurement
window that reads “SC.” Click the mouse button and choose a channel number from the pulldown menu. The channel numbers in the pull-down menu correspond to the numbers in the
channel boxes in the upper left corner of the graph window.
To select a measurement, position the cursor on a measurement box and click the mouse
button. Choose a measurement from the pull-down menu; see page 98 for measurement
functions and the minimum samples for each (some of the values are single point
measurements while others require at least two points to be selected).
The measurements in the upper half of the menu reflect amplitude measurements, or
measurements which contain information about the vertical (amplitude) scale. Other
measurements use information taken from the horizontal axis (usually) and are found on the
section of the pull-down menu below the dividing line. Some of the measurement options
change (or are disabled) if units are selected for the horizontal scale.

In some cases, the computations involved in the measurement can produce nonsensical results
(such as dividing by zero, or calculating a BPM from a single point). In those cases, a
measurement value like INF or **** may be displayed. This means that the result was
undefined at this point.
Measurement menus are tinted to match the color of the corresponding waveform.
Measurement Display

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The number of measurement rows is set in Preferences > Measurements, as well as precision of units.
Measurement Area
It is important to remember that AcqKnowledge is always selecting either a single point or an area spanning
multiple sample points. If an area is defined and a single point measurement (such as Time) is selected, the
measurement will reflect the last selected point.
§

Single-point measurements
When a single point is selected, the cursor will “blink.” The following graph shows how the I-beam is
used to select a single point for measurements.

§

Selected range measurements
Drag the I-beam cursor to select an area; the selected area will be highlighted.

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IMPORTANT!
The first data point is “plotted” at zero (on the left edge of the graph); the first visible data point is sample
point 2. The selected areas below demonstrate this concept.

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97

Measurements and Measurement Presets
Measurements are commonly used in conjunction with the cycle detector and other analysis protocols to
perform data reduction. In complex data analysis using the cycle detector, often multiple different sets of
measurements may be used to perform multiple extraction passes on the data. The measurement presets
feature allows users to create multiple predefined measurement configurations and apply them to the graph to
change between different configurations. All aspects of the measurement configuration are stored, including
measurement functions, any parameters for the measurement, source channel, and number of measurement
rows. For more details on this function, see Measurements Toolbar section on page 63.
IMPORTANT: Calculations performed within expressions or measurement channels DO NOT incorporate
units such as milli, micro, centi, deci, etc. All calculations are performed with numbers as they are exhibited
within the text field. Time/frequency axis measurements may have their units fixed by using Preferences >
Measurements > Time Units/Freq Units. Selecting “Best Match for Value” will change the units based upon
the magnitude of the value.
Measurement Validation
Measurements can be validated with the ValidateMeasurements.acq sample file included with the software.
Pay attention to the “Sample data file” section of the measurement definitions that begin on page 98, and
where included, note which sample points to use for validation (i.e., the first four sample points are used to
validate the Correlate measurement using the ValidateMeasurements.acq file).
Other sample files configured for specific measurement types include spreadsheets to provide external data
necessary for measurement verification. Each spreadsheet contains procedures and examples for the
associated measurement data file. These sample data files consist of Event Measurements.acq, Traditional.acq
(standard mathematical measurements included in AcqKnowledge), Expression Sum_Calculate.acq and
Correl Coef.acq (Correlation Coefficient).
X

X

Measurement Info / Parameters
Measurements containing parameters have an “i” for
info button next to the measurement type in the measurement bar. Click the button to generate a dialog to edit
the parameters. To paste parameters, enable the Journal Preference via Display > Preferences > Journal >
Measurement paste settings > Include measurement parameters.
Measurement Interpolation
On a down-sampled channel, the cursor can fall on a point between physical samples. In such cases, in the
Line Plot mode only, some measurements will display interpolated values; the value is obtained by linear
interpolation with respect to the two adjoining samples.
§ To disable measurement interpolation, uncheck the “Use linear interpolation” option in the Display >
Preferences dialog.
§ If interpolation is disabled for Line Plot, or any time Step Plot or Dot Plot is selected, measurements
take on the value of the first physical sample immediately to the left of the cursor or edge of the
selection.
§ When measurements are pasted to the Journal, there is no indication of interpolated measurements.
§ A Calculation measurement can be an interpolated value. When a measurement uses an interpolated
value, the result box background changes from gray to light purple.
§ The “Delta S” and “Samples” measurements are never interpolated.
§ Measurements will not be interpolated if all measurements are set to “SC” (selected channel); the
cursor will snap to the left for the measurements.
§ Measurement tooltips will reflect measurement interpolation.
Exporting measurements
One of the most important reasons to take measurements is to save them; AcqKnowledge allows storage and
export of these measurements in different formats.
§ Copying measurements to the journal:
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To copy measurements (exactly as they appear in the measurement windows) and paste them to the
Journal, select Edit > Journal > Paste measurement. Under the default settings, only the values
themselves are copied to the journal; the settings can be changed to include the measurement name and
other options under Display > Preferences > Journal
§ Copying measurements to the clipboard:
To copy measurements (exactly as they appear in the measurement windows) to the clipboard and paste
them into a word processor or other application, select Edit > Clipboard > Copy measurements. Under
the default settings, only the values themselves are copied to the clipboard. These settings can be
changed to include the measurement name and other options via Display > Preferences > Journal.
Measurement Definitions
The table below explains the measurement options available and the range required for each. The default
option is for time to be displayed on the horizontal axis, although it can be set to display frequency or
arbitrary units (see page 450 for details on how to change the horizontal scaling options). Unless otherwise
noted, all of the measurements described here relate to those displayed when the horizontal scale reflects time.
X

Measurement
Area

Area
Minimum area:
3 samples
Uses:
All points of
selected area

Explanation
Area computes the total area among the waveform and the straight line that is
drawn between the endpoints.
Area is expressed in terms of (amplitude units multiplied by horizontal units) and
calculated using the formula:
n -1

Area = å ( f (xi ) - y(xi ) + f (xi+1 ) - y(xi +1 ) ) *
i =1

Dxi
2

Where:
n—number of samples;
i—index (i = 1.n-1);

x i , x i +1
point,

- values of two neighboring points at horizontal axis ( x1 – the first

xn – the last point);

f ( x i ), f ( x i + 1 ) - values of two neighboring points of a curve (vertical axis);

y ( x i ), y ( x i +1 ) - values of two neighboring points of a straight line (vertical axis).
At the endpoints y( x1 )= f( x1 ) and y( xn )= f( xn ).
Dxi =

DX
- horizontal sample interval;
n -1

The value of a straight line can be found by formula:

y(xi ) = m * xi + b

b = f ( x1 ) - m * x1 - intercept;
m=

DY
- slope of the straight line;
DX

DY = f ( x n ) - f ( x1 )

- vertical distance of increase at vertical axis;

DX = x n - x1 - horizontal distance of increase at horizontal axis.
Sample plot:

The area of the shaded portion is the result.

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Part A — Getting Started

Measurement

BPM
(Time domain
only)

99

Area

Minimum area:
2 samples
Uses:
Endpoints of
selected area

Explanation
Note: The Area measurement is similar to the Integral measurement except that a
straight line is used (instead of zero) as the baseline for integration.

Results: This calculation will always return a positive result.
Units: Volts - sec.
Sample data file:
“ValidateMeasurements.ACQ”
Result: 0.4533 Volts - sec.
BPM (beats per minute) computes the time difference between the first and last
points and extrapolates BPM by computing the reciprocal of this difference,
getting the absolute value of it and multiplying by 60 (60 sec).
The formula for calculation of BPM is:

æ 1 ö
÷ * 60
BPM = çç
÷
x
x
1 ø
è n
Where:

x1 , x n - values of the horizontal axis at the endpoints of selected area.

Calculate

Minimum area:
2 sources
Uses:
Results of
measurements
used in
calculation

Note: As mentioned, this measurement provides essentially the same information
as the Delta T and Freq measurement.
Results: Only a positive value.
Units: BPM.
Calculate can be used to perform a calculation using the other measurement
results. For example, the mean pressure can be divided by the mean flow.
When Calculate is selected, the channel selection box disappears.
The result box will read “Off” until a calculation is performed, and then it will
display the result of the calculation. When the selected area is changed, the
calculation will update automatically.
To perform a calculation, generate the “Waveform Arithmetic” dialog via
Ctrl-Click or right mouse click the Calculate measurement type box or click the
“info” button next to the measurement type box

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Measurement

Area

Explanation

Use the pull-down menus to select Sources and Operand.
Measurements are listed by their position in the measurement display grid (i.e.,
the top left measurement is Row A: Col 1). Only active, available channels appear
in the Source menu.

Cap_Dim

Corr_Dim
Correlate

Minimum area:
2 samples
Uses:
All points of
selected area

Calculation measurement Source operands are updated before a Calculation is
performed, which means that Calculations can be based on measurements that
are located after them in the measurement row/column ordering.
Calculation measurements can include other Calculation measurements as their
operands.
· If a cyclic dependency is introduced, the result reads “Error.”
· When interpolation is being used, a Calculation measurement can also be
an interpolated value.
· If either of the operands of a Calculation is interpolated, the result will be
displayed as an interpolated value (with a light purple background).
The Operand pull-down menu includes: Addition, Subtraction, Multiplication,
Division, Exponential.
The Constant entry box is activated when selecting “Source: K, constant” and it
allows definition of the constant value to be used in the calculation.
To add units to the calculation result, select the Units entry box and define the
unit’s abbreviation.
Click OK to see the calculation result in the calculation measurement box.
Capacity Dimension; fractal dimension estimate.
(Fractals measure the amount of self-similarity in a data set. AcqKnowledge
offers three alternate estimates for fractal dimension: Cap_Dim, Corr_Dim, and
Inf_Dim. The estimates will not agree, based on the heuristic and the
parameters.)
Correlation Dimension; fractal dimension estimate. Always greater than capacity if
parameters are the same. (See fractals note at Cap_Dim.)
Correlate provides the Pearson product moment correlation coefficient, r, over the
selected area and reflects the extent of a linear relationship between two data
sets:

xi

- values of horizontal axis and

f ( xi ) - values of a curve (vertical axis).

Use Correlate to determine whether two ranges of data move together.
Association
Correlation
Large values with large values
Positive correlation
Small values with large values
Negative correlation
Unrelated
Correlation near zero
The formula for the correlation coefficient is:
n
æn ö æn
ö
n * å(xi * f ( xi )) - ç å xi ÷ * ç å f (xi )÷
i =1
è i=1 ø è i=1
ø

Correlate =

2
2
n
n
é
æn ö ù é
æn
ö ù
2
2
ên * å( xi ) - ç å xi ÷ ú * ên * å( f (xi )) - ç å f (xi )÷ ú
è i=1 ø ûú ëê i=1
è i=1
ø ûú
ëê i=1

Where:
n—number of samples;
i—index (i = 1..n);

xi — values of points at horizontal axis ( x1 – the first point, xn – the last point);

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Part A — Getting Started

Measurement

101

Area

Explanation

f ( xi ) - values of points of a curve ( vertical axis).

Results:
Returns a dimensionless index that ranges from -1.0 to 1.0 inclusive.
Units: None
Sample data file:
“ValidateMeasurements.ACQ”
Result: -0.74825(for whole wave) and 0.95917 (for first four
sample points).
Delta

Minimum area:
2 samples
Uses:
Endpoints of
selected area

Delta S

Delta T(time)
Delta F
(frequency)
Delta X (arbitrary
unit)

Minimum area:
1 sample
Uses:
Endpoints of
selected area
Minimum area:
2 samples
Uses:
Endpoints of
selected area

Delta returns the difference between the amplitude values at the endpoints of the
selected area.
Delta

= f ( x n ) - f ( x1 )

Where:

f ( x1 ) , f ( x n ) —values of a curve at the endpoints of selected area.

Results:
If the data value at the starting location is greater than the data value at the
ending location of the cursor, then a negative delta will result. Otherwise, a
positive delta will result.
Units: Volts
Sample data file:
“ValidateMeasurements.ACQ”
Result: -2 Volts (for whole wave). This result shows the
absolute value of change of amplitude (2) and the minus
sign means a decrease of amplitude.
Delta S returns the difference in sample points between the end and beginning of
the selected area.
Results: This calculation will always return a positive result.
Units: Samples

The Delta T/F/X measurement shows the relative distance in horizontal units
between the endpoints of the selected area. Only one of these three units will be
displayed in the pop-up menu at a given time, as determined by the horizontal
scale settings.
Measurement
Horizontal Axis
Delta T
Time
Delta F
Frequency (FFT)
Delta X
Arbitrary units (Histogram Bins)
The formula for Delta T/F/X is:
Delta T

= x n - x1

Where:

x1 , x n - values of horizontal axis at the endpoints of selected area.
Results:
If the data value at the starting location is greater than the data value at the
ending location of the cursor, then a negative delta will result. Otherwise, a
positive delta will result.
For Delta T measurements with the horizontal axis format set to HH:MM:SS.

ü
ü

Values less than 60 seconds will result in a value in decimal
seconds.

Values greater than 60 seconds will result in an HH:MM:SS
format value
(See page 74 for details on how to change the horizontal scaling).
Units:
Delta T: Seconds (sec.)
Delta X: “arbitrary unit”
Delta F: Hz
Sample data file:
“ValidateMeasurements.ACQ”
Result: 0.12 sec. (for whole wave).
X

Evt_amp

X

Extracts the value of the measurement channel at the times where events are
defined. The measurement result is unitless. Specify Type, Location, and Extract;
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Measurement

Area

Explanation
see page 237 for details.
§ The amplitude is always taken from the measurement channel, which may be
different from the channel on which events are defined.
Evt_amp can be useful for extracting information such as the average T wave
height within the selected interval.
Evaluates the number of events within the selected area. The measurement
result is unitless. Specify Type and Location; see page 237 for details.
X

Evt_count

X

X

Evt_loc

X

Extracts information about the times of events. The measurement result uses the
units of the horizontal axis. Specify Type, Location, and Extract; see page 238 for
details.
Generates the Expression transformation dialog (page 148) and offers Source
“MC” Measurement Channel instead of “SC” Selected Channel to build recursive
formulas, i.e. result of the expression as it was evaluated x samples ago. Data
within the selected area is not changed.
Evaluation rules:
When a new selection is made, the first step in evaluation searches through the
measurement expression for any MMT() invocations. Any measurement whose
value is needed by MMT () is computed at this time prior to the expression
evaluation. This behavior is similar to calculation channels and successfully
allows measurements to the right and bottom of the expression measurement to
be used in the expression.
The expression is subsequently evaluated from the leftmost sample in the
selection to the right most sample. It is evaluated at the waveform sampling rate
of its source channel. Interpolation is not used at the boundaries to maintain a
consistent sample interval for the expression. After each expression evaluation,
the result is cached in memory for potential negative MC result references.
The rightmost value of the final expression becomes the value of the
measurement.
X

Expression

X

Freq (time
domain only)
It is important
to note…
This does not
compute the
frequency
spectra of the
data.
To perform a
spectral
analysis, use
the FFT
function (see
page 333).
X3

X

Minimum area:
2 samples

X

X

Freq computes the frequency in Hz between the endpoints of the selected area
by computing the reciprocal of the absolute value of time difference in that area.
The formula for Freq is:

Uses:
Endpoints of
selected area

Freq

æ 1 ö
÷
= çç
÷
x
x
1 ø
è n

Where:

x1 , x n - values of horizontal axis at the endpoints of selected area.
The information provided by this measurement is directly related to the Delta T
and BPM measurements, and is related to a lesser extent to Delta S
measurement. That is, if the Delta T interval between two adjacent peaks is
calculated, the BPM and Freq measurement can be extrapolated.
If the sampling rate is known, the Delta S can also be derived.
In the following example, observe the Delta T, Freq and BPM measurements for
the particular area. The Delta S can also be derived.

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Part A — Getting Started

Measurement

103

Area

Explanation

Selected area with measurements that describe
the same interval in different terms.
Note: It is important to note that this does not compute the frequency spectra of
the data. To perform a spectra analysis, use the FFT function (described on page
333).
Freq (or frequency) is only available in time domain windows.
Results: This calculation will always return a positive result.
Units: Hz
Sample data file:
“ValidateMeasurements.ACQ”
Result: 8.33 Hz (for whole wave).
Information Dimension; fractal dimension estimate. (See fractals note at
Cap_Dim.)
X

Inf_Dim
Integral

Minimum area:
2 samples
Uses:
All points of
selected area

X

Integral computes the integral value of the data samples between the endpoints
of the selected area. This is essentially a running summation of the data.
Integral is expressed in terms of (amplitude units multiplied by horizontal units)
and calculated using the following formula.
n -1
i
Integral =
i
i +1
i =1
Where:
n—number of samples;
i—index (i = 1.n-1);

Dx
(
)
(
)
[
f
x
+
f
x
]
*
å
2

x i , x i +1
point,

- values of two neighboring points at horizontal axis ( x1 – the first

xn – the last point);

f ( x i ), f ( x i + 1 ) - values of two neighboring points of a curve (vertical axis);
DX
- horizontal sample interval;
Dxi =
n -1

DX = x n - x1 - horizontal distance of increase at horizontal axis.

The following plot graphically represents the Integral calculation.

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Measurement

Area

Explanation

The area of the shaded portion is the result.
Results: The Integral calculation can return a negative value if the selected area
of the waveform extends below zero.
Units: Volts—sec.
Sample data file:
“ValidateMeasurements.ACQ”
Result: 0.300 Volts -sec.(for first 6 sample points) and –
0.155 Volts -sec.(for last 6 sample points—the wave below
zero).
Kurtosis indicates the degree of peakedness in a distribution, e.g. the size of the
“tails” of the distribution. Distributions that have sharp peaks in their center have
positive kurtosis; flatter distributions have negative kurtosis. A normal distribution
has a kurtosis of 0. The following formula is used to extract kurtosis

Kurtosis

n

å (xi - x )

4

i =1

kurtosis =

Lin_reg

Minimum area:
2 samples

n
2
æ n
ö
ç å (xi - x ) ÷
ç i =1
÷
ç
÷
n
çç
÷÷
è
ø

2

Where from a signal (x) containing n points:
Linear regression is a better method to calculate the slope when noisy, erratic
data is present.
§ For advanced modeling options, see Nonlinear modeling on page 329.
Lin_reg computes the non-standard regression coefficient, which describes the
unit change in f (x) (vertical axis values) per unit change in x (horizontal axis).
For the selected area, Lin_reg computes the linear regression of the line drawn
as a best fit for all selected data points using the following formula:
X

Uses:
All points of
selected area

Lin_reg =

X

n
æ n ö æ n
ö
n * å ( xi * f ( xi )) - ç å xi ÷ * ç å f ( xi )÷
i =1
è i =1 ø è i =1
ø
2
n
n
æ
ö
2
n * å ( xi ) - ç å xi ÷
i =1
è i =1 ø

Where:
n—number of samples;
i—index (i = 1.n);

xi — values of points at horizontal axis ( x1 – the first point, xn – the last point);
f ( xi ) - values of points of a curve ( vertical axis).
Note: For a single point, Lin_reg computes the linear regression of the line drawn
between the two samples on either side of the cursor.
Results:
If the data value at the starting location is greater than the data value at the
ending location of the cursor, then a negative delta will result. Otherwise, a
positive delta will result.
Units: Volts/sec.
This value is normally expressed in unit change per second (time rather then
samples points) since high sampling rates can artificially deflate the value of the

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Area

Lyapunov

Max

Minimum area:
2 samples
Uses:
All points of
selected area

Max T

Mean

Minimum area:
1 sample
Uses:
All points of
selected area
Minimum area:
2 samples
Uses:
All points of
selected area

Explanation
slope. If the horizontal axis is set to display Frequency or Arbitrary units, the slope
will be expressed as unit change in corresponding vertical axis values
(frequency or arbitrary units, respectively).
Sample data file:
“ValidateMeasurements.ACQ”
Result: 230.00 Volts/sec. (for 1-4 samples) and
–170.00 Volts/sec. (for samples 4-7).
Lyapunov exponent describes the exponential rate of divergence of a system
when perturbed from its initial conditions. For example, if the system is started
from two slightly different locations, this indicates how different their results will be
with time. Stable experiments have exponents equal to zero. Specify an
embedding dimension and a time delay; produces a single-valued measure. This
measure is quite dependent on the amount of data used.
Max (maximum) shows the maximum amplitude value of the data samples
between the endpoints of the selected area. To compare peak heights, select
each peak to see the maximum peak values or paste the results to the journal.
Also, since it’s possible to simultaneously obtain measurements for different
channels, maximum values for different channels can be easily compared.
Note: For a single point, Max shows the amplitude value in this point.
Units: Volts
Max T shows the time of the data point that represents the maximum value of the
data samples between the endpoints of the selected area.
Note: For a single point, Max T shows the time value in this point.
Units: Seconds

Mean computes the mean amplitude value of the data samples between the
endpoints of the selected area, according to the formula:
Mean =

1 n
* å f (x i )
n i =1

Where:
n—number of samples;
i—index (i = 1.n);

xi — values of points at horizontal axis; ( x1 – the first point, xn – the last point);
f ( xi ) - values of points of a curve ( vertical axis).
Units: Volts
Sample data file:
Median

Median T

Minimum area:
2 samples
Uses:
All points of
selected area
Minimum area:
2 samples
Uses:
All points of
selected area

Min

Min T

Minimum area:
2 samples
Uses:
All points of
selected area
Minimum area:
1 sample

“ValidateMeasurements.ACQ”
Result: 1.538462 Volts (for whole wave).
Median shows the median value from the selected area.
Note: The median and calculation is processor-intensive and can take a long
time, so it’s recommended that this measurement option only be selected when
actually ready to calculate. Until then, set the measurement to “none.”
Units: Volts
Median T shows the time of the data point that represents the median value of the
selected area.
Note: The median and calculation is processor-intensive and can take a long
time, so it’s recommended that this measurement option only be selected when
actually ready to calculate. Until then, set the measurement to “none.”
Units: Seconds.

Min (minimum) shows the minimum amplitude value of the data samples between
the endpoints of the selected area.
Note: For a single point, Min shows the amplitude value in this point.
Units: Volts.

Min T shows the time of the data point that represent the minimum value of the
data samples between the endpoints of the selected area.
Note: For a single point, Min T shows the time value in this point.
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Measurement

Moment

Area
Uses:
All points of
selected area
Uses:
All points of
selected area

Explanation
Units: Seconds.

Central Moment is a general-purpose statistical computation that can be used to
compute central variance and other higher-order moments of the data within the
selected area. Specify the order as an integer (generally). The central moment is
computed using the following formula:
m

n

mm =

Mut_inf

NLM

å (x - x )
i =1

i

n

Where:
x—signal;
n—points;
m—order.
Mutual Information determines how much could probabilistically be known about
an unknown signal given a known variable. Specify a time delay. Produces a
single valued result.
Nonlinear modeling (also called “arbitrary curve fitting“) determines the “best fit”
model for the selected data of the selected channel. The measurement result
corresponds to the value of one of the parameters of the best fit. NLM can be
used to extract Tau (time delay LVP constant) for assessing cardiac condition.
See page 329 for nonlinear modeling details.
§
If a Model Expression uses MMT() syntax to reference a measurement and
that referenced measurement is linearly interpolated, the results of the NLM
measurement will also be displayed as being linearly interpolated.
§
When combined with the Cycle/Peak Detector (on page 341), the NLM
measurement can be useful for extracting cycle-by-cycle best fit models for
an entire waveform.
None does not produce a measurement value. It’s useful when copying a
measurement to the clipboard or journal with a window size such that several
measurements are shown but don’t all need to be copied.
P-P (peak-to-peak) shows the difference between the maximum amplitude value
and the minimum amplitude in the selected area.
Results: The result is always a positive value or zero.
Units: Volts
Sample data file:
“ValidateMeasurements.ACQ”
Result: 13 Volts (for whole wave).
Extracts the mean value of the rate outputs within the selected area. Unless this
measurement is used on a rate analysis or calculation channel, this measurement
is not defined (****). The units of this measurement will match the amplitude units
of the measurement channel.
Extracts the median value of the rate outputs within the selected area. Unless this
measurement is used on a rate analysis or calculation channel, this measurement
is not defined (****). The units of this measurement will match the amplitude units
of the measurement channel.
Extracts the standard deviation value of the rate outputs within the selected area.
Unless this measurement is used on a rate analysis or calculation channel, this
measurement is not defined (****). The units of this measurement will match the
amplitude units of the measurement channel.
Samples shows the exact sample number of the selected waveform at the cursor
position—the first data point is not displayed, but is plotted at zero.
See page 96 for examples of selected area Samples.
Note: When an area is selected, the measurement will indicate the sample
number at the last position of the cursor.
Units: Samples.
Skew is a statistical measure of the degree of asymmetry in a distribution (away
from normal Gaussian distribution), e.g. if the distribution is weighted evenly or
trends toward an edge.
·
A normal distribution has a skew of 0.
·
A distribution with a prominent left tail has a negative skew.
·
A distribution with a prominent right tail has a positive skew
The following formula is used to extract skew:
X

X

X

None

n/a

P-P

Minimum area:
2 samples

Rate_mean

Uses:
All points of
selected area
Uses:
All points of
selected area

Rate_median

Uses:
All points of
selected area

Rate_stddv

Uses:
All points of
selected area

Samples

Minimum area:
1 sample

X

Uses:
All points of
selected area
Skew

X

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Area

Explanation
n

å ( xi - x )

3

i =1

skew =

Slope

Minimum area:
2 samples

Uses:
All points of
selected area

n
æ
ç
ç
ç
ç
ç
è

n

å (x
i =1

- x)

2

i

n

ö
÷
÷
÷
÷
÷
ø

3

Where a signal (x) contains n points:
Slope computes the non-standard regression coefficient, which describes the unit
change in f (x) (vertical axis values) per unit change in x (horizontal axis).
For the selected area, Slope computes the slope of the straight line that intersects
the endpoints of the selected area, using the formula:
Slope =

f (x n ) - f ( x1 )
x n - x1

Where:

f ( x1 ) , f ( x n ) —values of a curve at the endpoints of selected area.

x1 , xn - values of horizontal axis at the endpoints of selected area.
This value is normally expressed in unit change per second (time rather then
samples points) since high sampling rates can artificially deflate the value of the
slope.
Note: Lin_reg (linear regression) is a better method to calculate the slope when
noisy, erratic data is present.
For a single point, Slope computes the slope of the line drawn between the two
samples: the selected sample point and the sample point to its left.
Results:
If the data value at the starting location is greater than the data value at the
ending location of the cursor, a negative delta will result. Otherwise, a positive
delta will result.
Units: Volts/sec. (or corresponding to Freq or Arbitrary setting)
Sample data file:
“ValidateMeasurements.ACQ”
Result: 233.33333 Volts/sec. (for samples 1-4)
-166.66667 Volts/sec. (for samples 4-7) and
-16. 66667 Volts/sec. (for whole wave).
Stddev

Minimum area:
2 samples
Uses:
All points of
selected area

Stddev computes the standard deviation value of the data samples between the
endpoints of the selected area. Variance estimates can be calculated by squaring
the standard deviation value.
The formula used to compute standard deviation is:
Stddev =

n
1
æ
ö
* å ç f (xi ) - f ÷
n - 1 i =1 è
ø

2

Where:
n—number of samples;
i—index (i = 1.n);

xi — values of points at horizontal axis ( x1 – the first point, xn – the last point);
f ( xi ) - values of points of a curve ( vertical axis);
-

f =

Sum

Minimum area:
2 samples

1 n
* å f ( xi )
n i =1

- the mean amplitude value of the data samples between

the endpoints of the selected area.
Results: The result is always a positive value or zero.
Units: Volts
Sample data file:
“ValidateMeasurements.ACQ”
Result: 3.09570 Volts (for samples 1-4),
1.000 Volts (for samples 10-12).
Sum extracts a mathematical sum of the amplitudes of all of the samples within
the selected area. This straight sum can be used as a building block for more
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Measurement

Time

Value

X-axis:T/F/X
(horizontal units)

Area
Uses:
All points of
selected area
Minimum area:
1 samples
Uses:
All points of
selected area
Minimum area:
1 sample
Uses:
All points of
selected area
Minimum area:
1 sample
Uses:
All points of
selected area

Explanation
complicated formulas. Examples of its utility include HRV measurements, various
statistical measurements, and simple criteria for clustering. Sum is available from
within the measurement popup menus and from analysis scripts that allow for
extraction of measurements.
See the X-axis: T measurement for explanation.

Value shows the exact amplitude value of the waveform at the cursor position.
For the selected area, Value indicates the value at the last position of the cursor,
corresponding to the direction the cursor was moved (the value will be the leftmost sample point if the cursor was moved from right to left).
Units: Volts
The X-axis measurement is the exact value of the selected waveform at the
cursor position, based on the Horizontal Axis setting:
Measurement
Horizontal Axis Setting
Units
X-axis: T
Time
Sec.
X-axis: F
Frequency
Hz.
X-axis: X
Arbitrary units
Arb. units
For X-axis: T measurements, the time value is relative to the absolute time offset,
which is the time of the first sample point.
The X-axis: F measurement applies to frequency domain windows only (such as
FFT of frequency response plots). The Freq function for time domain windows is
described on page 102.
Note: If a range of values is selected; the measurement will indicate the horizontal
value at the last position of the cursor.
Results: This calculation will always return a positive result.
X

X

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Part B—Acquisition Functions: The Hardware Menu
Overview
AcqKnowledge software adds acquisition and control capability to the complete MP160/MP150/MP36R
Systems and other BIOPAC data acquisition hardware, such as wireless BioHarness, Mobita, or BioNomadix.
The MP (or Hardware) menu items will vary in appearance depending on the type of data acquisition hardware
in communication with the software, and the Hardware menu title will reflect the currently connected hardware
type. (It is also important to note that certain features in the MP160/150 and MP36R hardware menus are not
supported in all hardware types.) For the purposes of this guide, all supported data acquisition systems will be
referred to generically as being under the umbrella of the “Hardware” menu, unless otherwise noted.
This section describes the commands and procedures used to establish the various acquisition parameters for the
hardware, including how to:
· Set Up channels for data acquisitions
· Control acquisition parameters such as sampling rate and duration
· Perform online calculations and digital filters
· Set acquisitions to begin on command from a mouse click or external trigger
· Display values numerically and graphically during an acquisition
· Output waveforms and digital signals during an acquisition
· Control the on-screen waveform display characteristics
Some of the basic functions involved in setting up an acquisition were covered in Part A—Getting Started, but
this section will cover them in more detail, as well as describe some additional features. All commands
referenced here can be found under the hardware device menu.

The Options button (AcqKnowledge 5.0.3 and higher) is at
the lower right of the Data Acquisition Settings screen.
The supported Options are:
· Saving all modified Data Acquisition Settings as a
Graph Template for convenient use later
· Copying settings from one open graph to another
·

Applying the settings of the active graph to all other
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Set Up Data Acquisition > Data Acquisition Settings
In AcqKnowledge, many key setups are accessed by selecting Hardware menu > Set Up Data Acquisition. This
option displays the Data Acquisition Settings window, comprised of the following items:
· Channels – all channel and hardware module setups – see page 112
· Length/Rate – all acquisition setup parameters for the hardware – see page 165
· Event Marking – for setting up hotkeys to insert custom events during acquisition – see page 227
· Segment Labels – for creating custom append segment labels – see page 250
· Stimulator – for configuring all stimulator options – see page 183
· Trigger – for configuring all triggering setups see page 180
· Sound Feedback – for setting up audio output of channel data – see page 250
Clicking a listed item populates the Data Acquisition Settings window with the selected item’s setup dialog. At
the bottom right of the Data Acquisition Settings window is a “Save Graph Template” button. This enables
unique settings from any selected feature to be saved into a graph template for future use.
It’s also possible to save user-defined default settings for new graphs by selecting Display > Preferences >
Hardware and choosing “User-defined default channel setup.” Following this, each selected parameter change
must be accepted by clicking “Yes” to the resulting “save default settings” dialog. Once the settings are
accepted, this dialog does not reappear unless the settings are subsequently modified.
Acquisitions
Acquisition is defined as data collection from an external source (such as electrodes connected to an amplifier).
Ø Before starting an acquisition, make sure the data acquisition hardware is turned on and connected to
the computer. Please refer to the BIOPAC MP Hardware Guide for more information on connections
for the particular hardware type being used.
To begin collecting data and display data as it is being collected:

1. Launch the AcqKnowledge application (double click the AcqKnowledge icon).
2. Choose File > New and select document type “Graph Window.”

NOTE: If more than one hardware type has
been previously added via the “Connect to”
menu, these will also appear in the “Choose
Type” dialog (left).For details on connecting
additional hardware types, see page 169.

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3. Set up the specific channels to acquire before starting the acquisition.
· See the Set Up Channels chapter (page 112) for details.
4. Set up the acquisition parameters (such as sampling rate, acquisition length, and data storage options.
· See the Set Up Data Acquisition chapter (page 165) for details.
12

Edit menu functionality during acquisition
The following Edit menu functions may move or alter memory and cannot be performed during acquisition:
Undo, Cut, Clear, Clear All, Paste, Insert Waveform, Duplicate waveform, and Remove Waveform.

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Chapter 5

Set Up Channels

Set Up Channels—The Basics
Before collecting data, it’s necessary to specify how many channels data will be collected on, and at what rate
that data is to be collected. Both of these functions are accomplished through menu items and dialogues. To
enable collection on a given channel, select Set Up Data Acquisition > Channels from the hardware menu.
AcqKnowledge for MP160 and MP150 offers two methods of analog channel setup:
Module-based setup
View by Channels see page 114 for details

If using AcqKnowledge with BioHarness™ or B-Alert™, Analog channels can be turned
on/off but not changed.
Module-based analog channel setup
For MP160 and MP150 units, AcqKnowledge offers a module-oriented analog channel setup
option. In module mode, setup prompts the user to add modules/transducers and establish
parameters, plus it detects potential channel conflicts between software assignment and the
module channel switch setting and scales the signal to the correct value and units. Module
setup is supported in MP160 and MP150 hardware only.

The module setup is recommended for easier setup and automatic scaling. In module mode, setup prompts the
user to add individual modules based upon the module number. For modules with transducers, the unique
transducers are added. The user is then prompted to input the settings of all of the switches on the modules and
then perform any calibration steps, if required. Using this information, the module setup automatically sets the
scaling and initial visual range to match the physical input units from the module or transducer. Additionally,
module-based setup detects potential channel conflicts between software channel assignment and module
channel assignment (red switch position).
1. From MP160/150 > Setup Data Acquisition > Channels, select the analog tab and click Add New Module...
NOTE: Module setup mode is activated by default when the “Create/Record a new experiment” launch
option is selected in the Startup Wizard window. (The add module dialog shown in Step 3 is presented
first.)

2. Click Add New Module from the bottom of the dialog.

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3. Select a module, click Add and select the channel switch position.

4. If prompted, select a transducer and click Add.

5. Input the settings of the switch on the selected module and click OK. Set
the choose channel switch to the number set on the amplifier (some
amplifiers, such as the OXY100C, have a switch on the front of the
module).
§ Setup detects any potential channel conflicts between software
assignment and the module’s red channel switch position.
6. Establish the configuration parameters (gain and filters) and click OK. It
is important to set the Gain and Filter settings to correspond to the switch
settings on the amplifier. The software uses this information to scale the
signal to the correct units. If the Gain is not set to match, the signal will
be scaled incorrectly.
7. Perform calibration steps, if required. The software will automatically
scale certain signals, if they only require a zero setting. However, some
signals require a two-point calibration. In this case, the software will
generate additional prompts for the scale values.
The following examples show the dialogs for setting up a force
transducer.
a. The software prompts the user for pretension amount; enter “0” if
pretension is not required.

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b. Enter a low calibration value or “0” if calibrating between zero and a second weight, when OK is
clicked, the software will take a voltage reading.

c. Enter a high calibration value and click OK for the software will take a voltage reading.

When recording is started, the data may show an offset. This offset is the amount that was
entered in the pretension dialog. Adjust the tension applied to the transducer to center the signal
on zero.
Using this information, the module setup automatically sets the scaling and initial visual range to match
the physical input units from the module or transducer.
“Apply data alignment corrections” option (AcqKnowledge 4.4.2 and higher)
Note

This checkbox option is found at the bottom of the Channels > Add New Module screen and is recommended
when using the following hardware modules:
· NIBP100D (via DA100C general purpose amplifier) : adds 50 msec delay.
· NIBP100D-HD (via HLT100C high level transducer module): adds 50 msec delay
· When combining BioNomadix wireless signals with wired signals: adds 15.6 msec delay (+/- 0.5 ms
RMS)
Checking this box automatically adds appropriate delays, ensuring all data will be properly aligned when the
above combination of hardware is used. This avoids the need to use calculation channels to manually align data
when combining hardware types that apply varying amounts of fixed delay.
NOTE: If NIBP100D is not being used, or if BioNomadix is being used only with other BioNomadix receivers,
then checking this option is not necessary. (It is unchecked by default.)
View by Channels
Channel Type
To specify the channel type—Analog, Digital, or Calculation—click its tab at the top of the dialog.

For each channel, there are three options for channel setup: Acquire, Plot, and Value. These options appear as
boxes on the left side of the Input Channels dialog.
Acquire
This option dictates whether data will be collected on that channel. The default setup is not set to acquire any
channels. To collect data, position the cursor over the Acquire box (on the far left) and click the left mouse
button.

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To leave hardware connected to the data acquisition unit, but have the software essentially “ignore” the channel,
leave the Acquire box unchecked. For example, if an input device (such as an ECG100C amplifier) is set to
Channel 7, data from that channel will not be collected unless the Acquire box is checked.
Plot
The second option is for plotting data. The Plot option determines whether or not data will be plotted on the
screen for each channel. Checking this option instructs the software to plot data on the computer screen.
When this box is left unchecked, data will still be collected (assuming the Acquire box is checked) but will not
be displayed during the acquisition.
In most cases, checking this option is recommended. However, in large-scale acquisitions (i.e., many channels
and/or high sampling rates) unchecking this option for some channels allows for faster display rates or to
increase the display area for important channels (see Appendix B—Hints for working with large files).
Alternatively, use a separate data view and enable channels for as desired for optimum viewing.
The Plot state is applied only on initial acquisition into a graph or template. If data has been previously
acquired, use the channel buttons in the graph window to change channel visibility, OR use the Display > Set
Channel Visibility option to select/deselect the channels to be shown in the graph.
Values
The third option enables incoming data values to be displayed either numerically and/or in a “bar chart” format
in a separate window during an acquisition. Checking this option enables a bar graph (by selecting Show Input
Values... under the Hardware menu) that displays the numeric value for channels with this option checked. This
is especially useful for tracking slowly changing values such as heart rate, respiration rate, or concentrations of
chemicals in a substance. For more information on how input values are displayed, please turn to page 241.
Channel
Click in the channel number box (i.e. A1) to make that channel active (“selected”) so its settings can be
established or edited.
Label
Editable labels can be attached to each channel. To change the label for any channel, position the cursor in the
area to the right of the channel numbers (A1 through A16) under the label heading and enter a text label. Up to
38 characters are supported and these labels will appear next to the channel label boxes in the graph window.
To edit the label after setup, use the Set Up Channel dialog at any time, or right-click the active channel label in
the graph window to generate the Assign Channel Label dialog.
Calculation Channel Presets
When a new Calculation channel is enabled for the first time, a setup dialog is presented to assist in setting the
correct preset type, source channel and preset parameters.
To set an initial calculation channel preset:
1. Click the Calculation tab.
2. Enable the desired Calculation channel by
checking the “Acquire, Plot and Value”
checkboxes.
3. The following setup dialog will appear.
Select the desired Calculation preset and
analog source channel, and click OK.
4. After clicking OK, the setup dialog for the
selected preset will appear. Set the desired parameters and click OK. (For detailed information
about setting Calculation channel parameters, see Chapter 6 on page 133.)
Calculation Presets are like “templates” for calculation channels. Each Preset stores:
a) Calculation channel type
b) Parameters for that calculation
c) Channel name.

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Calculation Presets establish settings to target application-specific analysis. Presets exist for a broad range of
analysis functions, including Fourier Linear Combiners and Adaptive Filtering. Start with existing presets for a
specific species or protocol—for example, human vs. small animal, or stationary vs. exercising measurements.
The Channel Setup dialog contains a “Preset” pop-up menu by each channel that lists the current Preset or, if no
Preset has been selected for that channel, the Calculation type (Integrate, Difference, etc.). When a Preset is
selected for a particular channel, the channel is configured with the settings associated with that Preset.
The Setup dialog has a “Presets” pop-up menu that contains all of the Presets for the Calculation type being
configured. For instance, if a Difference Calculation channel is being configured, all Presets for the Difference
Calculation will be listed. Just click the Presets head and scroll to select the desired preset.

Calculation Presets
When a Preset is selected, the Setup dialog is updated with the corresponding information.
§ The Setup dialog reads “none” if the channel configuration doesn’t match any Preset. The menu will
flip to “none” when the settings for a channel are changed such that they no longer match a Preset.
§ Create a new Preset from existing Calculation channels. Click “Setup” to display the Calculation Setup
dialog and click the “New Preset” button. The settings will be applied to the current channel, and a
prompt will appear to enter a name for the new Preset. Preset names cannot be duplicated, nor can the
default name of a Calculation channel type be used (Integrate, Difference, etc.). The new Preset will be
included in the pop-up menus and saved with the file.
§ To reorder channel Presets (by type, use, etc.), choose Hardware > Organize Channel Presets and then
use the up/down buttons as appropriate (see page 257).
§ Presets are not applicable to and therefore not selectable on Analog or Digital channels.
Channel Sampling Rate
The Variable Sampling Rate feature allows different channels of data to be down-sampled from the acquisition
sampling rate; calculation channel must use sampling rate less than or equal to the source channel. Choosing
lower sampling rates for signals where meaningful data falls below the Nyquist frequency of the acquisition
sampling rate allows more data to be stored in memory or on disk.
§ Offline operations that involve multiple channels must use the same sampling rate for all Source and
Destination channels. These operations include waveform editing, Waveform math, Expression
calculations and Template functions; notable exceptions are “Off-line Averaging” under Find Cycle/Peak
and “Reset via a Control Channel” under Integrate.
§ When wave data is copied to the clipboard or journal, data values will be inserted at the highest sampling
rate.
§ There is no restriction on the acquisition length when using Variable Sampling Rates.
§ When Variable Sampling Rates are used in conjunction with the Append mode, and the mode is started
and stopped manually, it is statistically possible that, prior to the next pass of the Append, extra data
points may be inserted in various data channels to “line up” the data (see sample on page 116). These
extra data points simply replicate the last sample in any affected channel.
To minimize the impact of the extra data points:
a) Make sure the lowest sampling rate is on the order of 10 Hz or higher, or
b) Don’t use Variable Sampling Rates.
X

X

X

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Set Up Channels—Advanced
The previous section covered the basic options used in almost all acquisitions. In addition to the features
described above, a number of other options are available in terms of setting up channels. These advanced
features are also found under the Set Up Data Acquisition > Channels menu item.
Most acquisitions involve collecting analog signals and then displaying them on screen. It is frequently useful,
however, to collect other types of data (digital data, for instance) or to perform transformations on analog data
as it is being acquired. Channels containing digital signals and transformed analog signals can be collected in
addition to the 16 analog channels.
In the upper left corner of the Channels dialog, there are three tabs titled Analog, Digital, and Calculation.
These refer to the three respective channel types available in AcqKnowledge. The general features (acquiring,
plotting, and the like) are the same for each type of channel, although there are considerable differences
between the type of data each channel is designed to handle. Up to 16 channels each of analog, digital, and
Calculation channels are supported in MP160 and MP150 hardware, and 4 channels of analog, 8 channels of
digital and 16 Calculation channels are supported in MP36R hardware. Analog and digital channels may be
acquired in any combination, and the only requirement for Calculation channels is that at least one input
channel (either analog or digital) is enabled.
Analog channels
Analog channels are the most common type of acquired channel and should be used to acquire any data with
“continuous” values. Examples of this include nearly all physiological applications where input devices
(transducers and electrodes) produce a continuous stream of varying data. The range of values for analog
channels is ±10 Volts.
AcqKnowledge supports the rescaling of Analog channel signals to more meaningful numbers. As an example,
imagine a temperature transducer is connected to an SKT100C amplifier with a gain setting of 5°/Volt, and
output set to channel 1. Ordinarily, the values from the amplifier would be read in as Volts or millivolts. For
this acquisition, the signal from the transducer would need to be expressed in terms of degrees Fahrenheit. To
calibrate the transducer, bring it to two known temperatures. At the first temperature, take a voltage reading by
selecting “Show Input Values” from the Hardware menu. (See page 241 for a description of the Show Input
Values options). At 90° F, a reading of 0 Volts will be displayed. The transducer is then brought to a
temperature of 95° F, resulting in a reading of +1 Volts.
To scale the incoming signal to degrees F, click the Setup… button in the Input Channels dialog.
X241

X

Scaling dialog set to rescale Volts to degrees Fahrenheit and Use Mean Value Settings dialog

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The Input Volts and Map (Scale) Value boxes reflect the value of the incoming signal and how it will be plotted
on the screen, respectively. Thus, an incoming signal of +1 Volts would be plotted as 95° F, whereas a signal of
0 Volts would be plotted as 90° F. AcqKnowledge will perform linear extrapolation for signal levels falling
outside this range (i.e., -2 Volts will be scaled to 80 ° F), as well as perform similar interpolation for values
between this range. Enter these numbers in the scaling dialog, type in “degrees F” for Units, and click OK.
As a shortcut for scaling channels, use the Cal 1 and Cal 2 buttons. Click either of these buttons to read in the
current voltage for the selected channel. In the above example, the transducer could simply be set to a known
temperature, then Cal 1 could be clicked, and then the temperature could be entered in the Map (Scale) value
box for Cal 1.
Next, the transducer could be brought to another known temperature that is considerably higher or lower than
the first. Click Cal 2 and the new known temperature could then be entered in the Map (Scale) value box for Cal
2. AcqKnowledge calculates the slope and offset from the two points entered. Each data sample from channel 1
will now be scaled according to the slope and offset calculations previously made. When an acquisition is
performed, the amplitude scale (vertical axis) will reflect the rescaled units.
It is important to note that Cal 1 and Cal 2 cannot be used when data is being acquired. In other
words, a channel must be calibrated before it can be acquired. To set the calibration for a given
channel, connect the input device to the data acquisition unit, power up the Hardware, and then
perform the calibration before starting data acquisition.
The Calibrate all channels at the same time option is used when identical types of transducers or signals are
being simultaneously recorded on two or more channels.
If this option is selected, when Cal 1 or Cal 2 is pressed:
· Map (Scale) Value will be updated for all active channels
· Input Volts need to be updated for each channel individually.
The Use mean value option is useful if the input voltage signal is noisy around a mean value. The “Input Volts”
value returned will be the mean value over the specified number of readings. When this option is selected, a
Settings… button is activated and generates an “Analog Channel Calibration” prompt for the number of
readings.
The data is read the number of times indicated in the prompt and then the readings are averaged. The rate of
obtaining these readings is indeterminate because the rate depends on the actual hardware unit as well as the
communication type.
Increased Channel Count Support
Previous versions of AcqKnowledge software supported a total maximum of 60 analog, digital and calculation
channels per graph. In AcqKnowledge 4.3, channel count capability was extended to a theoretical maximum of
15,000 channels. While it is not generally feasible or useful to work with this many channels, it is now possible
to store and combine data derived from multiple hardware units, and perform complex specialized analysis with
data output to channels in the existing graph. (For example, advanced ICG analysis can potentially add up to 20
additional channels to the existing total.)
When a large number of channels are present, the channel buttons appear in rows of 20 and will extend the
height of the channel toolbar to accommodate any increase in channel count.

Clicking into the right pane of the channel toolbar opens a contextual menu listing all channel numbers and
channel labels.

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Analog channels MP36R
The MP36R analog channels may also be configured for gain and other parameters, but additionally allows the
channel gain to be configured directly with a variety of input ranges. Gain settings are accessible via a pop-up
menu in the Channel setup dialog. (MP36R > Set Up Data Acquisition > Channels > Setup) The Gain setting
specifies the extent to which an incoming signal is amplified. The Gain is automatically set when a data type is
selected from the available Presets. The preset Gain settings are only educated guesses and should be used as
initial starting values. It may be necessary to adjust the gain settings depending on how the amplified signal
appears once sample data is collected.

Offset
To correct the offset of an incoming analog signal, a constant can be added to or subtracted from the signal prior
to amplification. Offset can occur if a transducer or electrode has inherent offset. By default, Offset is set to
zero, and the allowable entry range will vary depending on the Gain and Scaling values.
To make inputting voltages easier, the analog channel scaling dialog for the MP36R displays the input voltages
in units that adapt to the gain setting. (x200 is the default)
The scaling units will adjust dependent upon the gain setting as follows:
·
·

If the gain is set to < x1000, the Scaling input units will display as millivolts (mV).
If the gain is set to > x1000, the Scaling input units will display as microvolts (μV).

µV

Channel gain set to < x1000 displays mV input units

Channel gain set to > x1000 displays μV input units

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Adjustable, user defined, digital IIR filters for MP36R
The MP36R Unit allows up to three user-configurable, sequential, biquadratic (second order) Infinite Impulse
Response (IIR) filters per MP unit channel. These filters are typically configured by choosing a Preset but can
be changed manually via the Input Channel Parameters dialog (MP36R > Set Up Data Acquisition > Channels
> Setup button). Each of these three filters can be uniquely set up as a low pass, band pass, high pass or notch
(band reject) filter.
In the “Digital Filters” section, select Filter 1, 2, and/or 3 and then adjust the Type, Freq, and Q.

The default setting is no filters applied.
High Pass Filters MP36R
These filters are implemented using resistors and capacitors in the front end circuitry of the MP36R unit. They
are set via the “High Pass” section of the Input Channel Parameters dialog (MP36R > Set Up Data Acquisition
> Channels > Setup”).

High Pass Filter
0.05 Hz HP
0.5 Hz HP

5 Hz HP

Appropriate use
ECG
Respiration data
ECG when there is a lot of motion artifact causing a shifting baseline
EEG
Pulse plethysmograph
Most other types of AC Coupled data
EMG
Heart Sounds

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Additional controls in MP36R Input Channel Parameters
Button
New Channel Preset
Advanced
Scaling

Explanation
Allows a custom Preset to be saved under a unique name
Opens Advanced dialog. The Advanced dialog may be used to specify additional settings,
requirements, and dependencies for the preset. See below for complete explanation of all
Advanced options.
Use to configure the value of the incoming signal and how it will be plotted on the screen.

MP36R Advanced Preset Settings
Click the Advanced button to open a dialog containing the following optional preset configuration options.

Acquisition Tab
Require minimum sampling rate

Transducer Tab

Explanation
When enabled, specifies that a minimum sampling rate must be selected
in order for acquisition to continue.

Explanation

Verify connected
transducer

When enabled, the software will check for a specific transducer according to the settings in this
group box prior to the start of each appended segment.

Title

Editable text field used to identify transducer name.

SSID

If checked, indicates which SmartSensor resistor ID should be validated for this channel prior to
each acquisition. The ID must be an integer between 1 and 23. See SSID table on page 122.

ISID Device Name

If checked, indicates that the internal transducer description should be validated for this channel
prior to each acquisition.

Use RegEx

Check this to treat the ISID device name as a regular expression to match against ISID device
names.

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Fallback on SSID if ISID check fails

If the ISID device name check is unsuccessful for a connected transducer, fall back
and check the SmartSensor resistor ID. See SSID table on page 122

Perform transducer verification on
first acquired segment only

When enabled, the software will check for a specific transducer according to the
settings in this group box prior to the start of first segment only.

MP36R Transducer SSID Table
Device Part #

Description

SSID

BSLCBL3A, BSLCBL4B

Recording cable

1

BSLCBL5

3.5mm phone plug adapter

6

BSLCBL8, BSLCBL9

High-impedance recording cable

1

BSLCBL14A

3.5mm phone plug adapter to MP35 Input.

6

BSLSTMB/A

10 V setting

18

BSLSTMB/A

100 V setting

19

BSL-TCI13

Piezo interface cable

1

BSL-TCI21

pH probe interface

12

SS1L, SS2L, SS2LA

Electrode lead set

1

SS2LB
SS3LA
SS4LA
SS5L, SS5LA, SS5LB
SS6L, SS7L, SS8L
SS9L, SS9LA
SS10L
SS11LA
SS11LB
SS12LA
SS13L
SS14L
SS17L
SS19L
SS19LA
SS19LB
SS20L, SS21L, SS22L,
SS23L, SS24L
SS25L, SS25LA
SS25LB
SS26L, SS26LB, SS27L
SS28L
SS29L
SS30L
SS31L
SS32L
SS33L
SS34L
SS35L
SS36L
SS39LA
SS40L, SS41L, SS42L
SS43L
SS56L
SS57L

Electrode lead set
EDA (GSR) finger electrodes
Pulse Plethysmograph finger transducer
Respiration Belt (for Chest)
Temperature transducer
BNC Adapter
Pushbutton switch
Airflow transducer
Airflow Transducer
Variable range force transducer
Blood Pressure (Arterial)
Displacement transducer
Piezo microphone
Blood Pressure cuff (with Gauge)
Blood Pressure cuff
Blood Pressure Cuff
Goniometer

N/A
2
3
4
5
6
7
8
N/A
9
10
11
14
10
N/A
N/A
16

Hand Dynamometer
Hand Dynamometer
Accelerometer
Heel Toe Strike assembly
Multilead ECG cable
Stethoscope, electronic
Non-Invasive Cardiac Output Module
Dissolved Oxygen probe
GAS – O2 (Used on GAS-System2)
GAS – CO2 (Used on GAS-System2)
Flow transducer
Reflex Hammer
MP3X Circuit Probe and Power Cable for Breadboard
Diff. Pressure transducer
Psychological response indicator
Clench Force (Bulb) transducer
EDA (GSR) with electrode pinch leads

9
N/A
17
9
1
14
15
20
21
22
18
9
6
10
11
N/A
2

SS57LA
SS59L

EDA (GSR)
Superlab Interface cable for MP35

N/A
6

SS61L

Finger Twitch transducer

16

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ISID Name

SS2LB

SS19LA
SS19LB

SS25LB

SS56L
SS57LA

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SS62L

Microphone

14

SS63L, SS64L, SS65L,
SS66L
SS67L

Fixed Range Force Transducer

9

Pneumogram transducer

10

SS68L

Ph Probe

12

SS70L

BNC Adapter (for MP35), Isolated version

6

Range + Grids Tab

Explanation

Apply initial visual range

The initial vertical axis range of plotted data will be set as indicated at acquisition start of the first
data segment.

Top

Indicates the maximum vertical visual range in destination channel units.

Bottom

Indicates the minimum vertical visual range in destination channel units.

Apply locked vertical
grid

Locked vertical grid settings are applied for the channel. For more details on grid setups, see
Grid Details on page 80.

First grid line

Provides the fixed location of the origin of the vertical grid.

Grid spacing

Sets the spacing interval between major vertical grid divisions.

Apply locked horizontal
grid

A channel-specific independent horizontal grid will be applied when the channel is added to a
graph.

First grid line

Sets the origin location of the horizontal grids.

Grid spacing

Sets spacing between major horizontal grid lines based on the time domain.

Apply grid appearance

Enables options for setting grid color/appearance of major and minor grid lines.

Major line color

Allows customization of major grid line color.

Minor line color

Allows customization of minor grid line color.

Show minor grid

Shows/hides minor gridlines

Vertical precision

Indicates number of digits displayed on vertical axis.

Num minor divisions

Sets the number of minor grid divisions for the channel.
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Calibration tab options are designed to assist in channel setup. They allow “custom” calibration prompts to be
used to guide users through the setup/calibration process. These prompts will appear in the main graph window
after clicking the graph’s Calibration
icon (or ‘Start’ button, if “Require calibration” is checked.) The
‘Calibrate’ button in the prompts are linked directly to the Cal 1 and Cal 2 input values found in the standard
“Scaling” dialog and offers an alternate method of setting these values. If multiple channels use the calibration
option, the calibration prompts will be presented in sequential channel order.
Calibration Tab Setup Example:

Resulting User Prompts:

Prompt 1:

Prompt 2:

See table for detailed explanation of calibration options.
Calibration Tab

Explanation

Use Calibration

Calibration procedure is applied after clicking the “Calibration’ icon in the graph
channel’s vertical scale region. One (if single point) or two (if double point)
custom prompts are presented in place of the usual ‘Scaling analog channel”
dialog. Each prompt has a ‘Calibrate’ and “Cancel’ button, one of which must be
responded to in order to continue.

Require calibration
prior to acquiring data

The above procedure is applied, except calibration prompts are presented as
follows when the ‘Start’ button is clicked.
·

Append mode: Calibration required at start of first segment recording
only.

·

Save Once or Autosave mode: Calibration required at start of first

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recording only. (Subsequent passes do not require re-calibration.)
NOTE: The "Require calibration prior to acquiring data" option has been
modified in AcqKnowledge 5.0.2 to improve usability when using transducers
that require calibration and the rewind mode. After initial calibration of the first
data segment, that calibration will be retained even after rewinding the data to
remove the segment. This allows users to perform a calibration and verification
acquisition, and then remove that verification segment prior to the next data
acquisition.
If recalibration is desired: Press the Shift key when clicking the Rewind
toolbar button, or right-click the rewind toolbar button and choose "Reset analog
calibration" from the contextual menu.

Calibration Type

Specifies calibration option to be performed. Two types are available:

·

Single point – Useful for quickly zeroing the baseline offset or
establishing a preload offset value. Presents a single prompt to the
user. Upon click of “Calibrate”, the input voltage is set as the new
“Cal2 Input voltage” in the Scaling dialog (equivalent to clicking “Cal2”).
It then calculates the difference between the old and new Cal2 Input
values then adds this to the Cal1 Input value. In other words, it
preserves the Scaling’s slope while shifting the offset.

·

Double point – records two independent voltages in a sequence of two
prompts and records the first as the input voltage for Cal2 and the
second for the input voltage in Cal1
For more details see examples below
Prompt

Use to input “custom” calibration prompt text. Up to 500 characters can be
entered and carriage returns can be used. The resulting prompts will be
dynamically sized according to the amount of text entered.
Note: The Scaling dialogs “map values” are displayed for reference to the left of
the Prompt field and can only be modified in the Scaling dialog. Any changes
will be dynamically updated in the Calibration dialog.

Apply using hardware
voltage offset

This option is available only for single point calibration. It is intended for single
point zeroing where, instead of adjusting the scaling values, the voltage offset of
the channel is changed to zero it in hardware. This is used for some transducers
that have additional correction that requires a hardware zero voltage, namely
the SS11LB and SS25LB.

Do not adjust “Cal 1”
offset.

This option is available only for single point calibration. When this option is
enabled, the Cal 1 voltage value will remain fixed

Examples of how to use the Calibration option
Example of “Double point” calibration for the SS12LA Force Transducer:
1. Connect the SS12LA to the MPs CH 1 input and choose MP > Set Up Data Acquisition >
Channels.
2. Select “Force 0-50 grams” from the Preset pull-down menu then click “Setup”.
3. From the “Input Channel Parameters” dialog, click “Advanced” then click on the “Calibration”
tab.
4. Check “Use calibration”, “Require calibration prior to acquiring data” and choose “Double
point” as the Calibration type.
5. Enter the desired “First prompt” text. For example,
“With only “S” hook attached to transducer, click “Calibrate”.
6. Enter the desired “Second prompt” text. For example,
“Attach 50 grams of weight, wait until swinging motion stops, then click “Calibrate”.
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7. Click OK and exit the “Input Channel Parameters” dialog.
8. Click the Start button. The first prompt will appear:

9. Follow the directions and click ‘Calibrate’. The second prompt will appear:

10. Follow the directions and click ‘Calibrate’. Calibration is complete and data recording will
start.
Note: The Scaling dialogs Map values (i.e. 0 and 50 grams) are assigned to the calibration prompts as follows:
Cal 2 Map value is assigned to Prompt 1 and Cal 1 Map value is assigned to Prompt 2.
“Calibrate” in Prompts

Correlates to Cal buttons in Scaling dialog

Prompt 1: “Calibrate” = “Cal 2” in Scaling.

Prompt 2: “Calibrate” = “Cal 1” in Scaling.

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Example of “Single point” calibration for the SS11LA Airflow Transducer:
1. Connect the SS11LA to the MPs CH 1 input and choose MP > Set Up Data Acquisition >
Channels.
2. Select “Airflow (SS11LA)” from the Preset menu then click “Setup”.
3. Click “Scaling” and change both the “Cal 2” Input and Map values to “0”, then click “Ok”.

4. From the “Input Channel Parameters” dialog, click “Advanced” then click on the “Calibration”
tab.
5. Check “Use calibration”, “Require calibration prior to acquiring data” and choose “Single
point” as the Calibration type.
6. Enter the desired “prompt” text. For example,
“Make sure no air is flowing through the transducer and click "Calibrate".”
7. Click OK and exit the “Input Channel Parameters” dialog.
8. With the SS11LA held upright, click the Start button. The single prompt will appear:

The recording should show 0 liters/second with no air flowing through the transducer.

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The Signal Types tab offers advanced options or “subtypes” to add to the selected preset or signal type. The
subtype options available are dependent upon the type of signal selected. For example, the ECG type contains a
variety of ECG lead configurations and common ECG signals, whereas Respiration offers various airflow
options. The subtypes are used for cases when users wish to retain specific information about lead configuration
or other details about the signal. Also see the Analysis Shortcuts section on page 260.

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Digital Channels
In contrast to analog channels, digital channels are designed to collect data from a signal source with only two
values (0 and 1). This type of data can be useful in recording whether a switch is open or closed, and
ascertaining if a device is on or off. Input values for digital channels have two values, +5 Volts and 0 Volts. The
hardware interprets +5 Volts as a digital 1 and interprets 0 Volts as a digital 0. Since digital channels have a
fixed value, the scaling option is disabled for these channels. The main function of digital channels is to track
on/off devices such as push-button switches and/or to receive digital signals output by timing devices.
Similarly, these channels are also used to log signals from devices that output auditory/visual stimulus for
examination of stimulus response patterns.
+5 volts
(binary "1")

0 volts
(binary "0")
Positive edge

Negative edge

Calculation Channels
Compared to either analog or digital channels, Calculation channels do not collect external data, but transform
incoming data in some way. These channels do not alter the original data, but create new channels (with
channel numbers starting at CH40) that contain the modified data.
Calculation channels can be used to compute a host of new variables by using transformations (including BPM,
integration calculations, and math functions). The channels are Set Up in much the same way (using
Acquire/Plot/Values boxes) as analog or digital channels, with the exception of the pull-down menu next to the
Calc button and the Setup dialog.
To enable a Calculation channel or channels, check the Acquire box for each channel to be added (the Plot and
Value boxes are optional). When a new Calculation channel is enabled, a dialog will appear enabling the
selection of the desired Preset type and Source channel. To change the Preset and Source channel types from the
defaults of Integrate and A1, click the
the desired option.

button to the right of the Preset and Source channel fields and choose

After clicking OK in the above dialog, an additional Setup dialog for the selected preset is presented. See
Chapter 6 for a detailed explanation of the various Calculation channel setup options.
Once the Calculation channel parameters are set, the options referenced above can be subsequently modified by
using the Setup button in the Channels dialog. (Highlight the desired channel in the list and click “Setup.”)

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Up to 16 Calculation channels can be acquired, and the output of one Calculation channel can be used as the
input for another channel, as long as the output channel has a higher channel number than the input channel. In
other words, it’s possible for Calculation channel 3 to include the result of Calculation channel 1, but not the
other way around. This allows for complex Calculations to be performed that involve two or more Calculation
channels such as filtering ECG data then computing BPM.
TIP: All of the operations (except Control and Metachannel) that can be
performed online can also be performed after an acquisition has been
completed. These options are available under the Transform and
Analysis menus.
Metachannel
Calculation metachannels provide a method for
expanding the 16 available calculation channels
to allow for more complex online analysis. The
metachannel calculation channel type combines
multiple steps into a single calculation channel
so that a chained computation can be
performed using a single calculation
metachannel.
· AcqKnowledge can display the results
of up to 16 metachannels, allowing for
a total of 256 intermediate subchannel
steps.

One metachannel can contain up to 16 subchannels, each of which can be individually configured. Subchannels
can perform any of the functions of top-level calculation channels.
Each metachannel has one user-defined output channel. The output subchannel is the only waveform data that
will be recorded in the graph for that metachannel. All other subchannels associated with that metachannel are
temporary; they do not display in the graph and require no extra space in the graph file to compute.
Metachannels alleviate the need to use top-level calculation channels for computing intermediate steps where
only the final computation is desired. Metachannels also can be used as the basis of presets, allowing multi-step
analyses to be applied with a single preset.
Computation takes place at the lowest waveform sampling rate of all of the referenced source channels, and all
subchannels are computed at this rate.
Metachannels labels display in the graph as C#.#
To have AcqKnowledge perform a Metachannel calculation:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the filtered data. If necessary, check the
Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Metachannel.
5. Click the Setup button in the Input Channels dialog to generate the Metachannel dialog.
Primary Source
The primary source for a metachannel can be set to any analog or digital enabled channel, or an enabled
calculation channel with a lower number.
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Set Up Subchannel
Click this button to display the calculation setup dialog for the
selected subchannel and then set the calculation parameters
and the source channel.
Source channel: Each subchannel can be set to use the primary source channel as its data source or another
channel (analog, digital, or lower-index calculation channel). When the primary source channel for the
metachannel is changed, the source channel of each subchannel will implicitly be changed.
Limitations on Subchannels
Subchannels are allowed to take on any of the main calculation channel types. All calculation types are
available, with some restrictions.
·
·
·

Output of reset events is not supported for Integrate and Rate subchannels.
For Expression subchannels, the expression language will be enhanced to allow for "PSC" to be
typed into the expression to refer to the data of the primary source channel.
Unlike regular calculation channels, the actual data for subchannels is not retained in memory.
Subchannels are only used as temporary data and the results discarded after the value of the
output subchannel has been computed.

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AcqKnowledge QUICK STARTS
U

U

Quick Start templates (.gtl graph template files) are installed to the Sample Data folder. Use Quick Start files to
establish the settings required for a particular application or as a good starting point for customized applications.
See Open As Graph Template on page 266 for details.
X

Q##
1
2
3
4
5
6
7
9
10
12
13

15
16
17
18A
18B
19
20

21
22
23
24
25
26
27
28
31
32
33
34
35
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52

Application(s)
EEG
Sleep Studies
EEG
EEG
Evoked Response
Evoked Response
Evoked Response
Evoked Response
Evoked Response
Evoked Response
Psychophysiology
Psychophysiology
EBI
Cardiovasc. Hemodynamics
Exercise Physiology
EOG
EOG
Plethsymography
Plethsymography
Plethsymography
Sleep Studies
Sleep Studies
ECG
Cardiovasc. Hemodynamics
Sleep Studies
ECG
ECG
ECG
Cardiovasc. Hemodynamics
Cardiovasc. Hemodynamics
Cardiovasc. Hemodynamics
Cardiovasc. Hemodynamics
NIBP
In vitro Pharmacology
In vitro Pharmacology
In vitro Pharmacology
In vitro Pharmacology
Pulmonary Function
Pulmonary Function
Exercise Physiology
EMG
EMG
Biomechanics
Remote Monitoring
Biomechanics
Vibromyography
Pressure Volume Loop
Heart Rate Alarm
Segment Timer Gauge
Mobita_Q01_ECG
Mobita_Q02_EEG
Mobita_Q03_EMG Facial
Mobita_Q04_EMG Leg

X

Feature
Real-time EEG Filtering
Real-time EEG Filtering
Evoked Responses
Event-related Potentials
Event-related Potentials
Nerve Conduction Studies
Auditory Evoked response & Jewett Sequence
Visual Evoked Response
Somatosensory Evoked Response
Extra-cellular Spike Recording
Autonomic Nervous System Studies
Sexual Arousal Studies
Cardiac Output
Noninvasive Cardiac Output Measurement
Noninvasive Cardiac Output
Nystagmus Investigation
Saccadic Eye Movements
Indirect Blood Pressure Recordings
Arousal - Female
Arousal - Male
Multiple-channel Sleep Recording
Online ECG Analysis
Online ECG Analysis
ECG Analysis
SpO2 Analysis
Einthoven’s Triangle & 6-lead ECG
12-lead ECG Recordings
Heart Sounds
Online Analysis
Blood Pressure
Blood Flow
LVP
Psychophysiology
Tissue Bath Monitoring
Pulsatile Tissue Studies
Langendorff & Working Heart Preparations
Isolated Lung Studies
Animal Studies
Lung Volume Measurement
Respiratory Exchange Ratio
Integrated (RMS) EMG
EMG and Force
Gait Analysis
Biomechanics Measurements
Range of Motion
Muscle Activity
Blood Pressure & Flow
Monitor heart rate with audible alarm
Record and display ECG with segment timer in the gauge window
ECG for Mobita, Lead I, Lead II, Lead II and more
EEG montage for Mobita
Facial EMG for Mobita, Corrugator and Zygomatics
Leg EMG for Mobita, multi-front and back references

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Chapter 6 Calculation
Channel Presets

§

Calculation Presets establish settings to target
application-specific analysis. Presets exist for a
broad range of analysis functions, including
Fourier Linear Combiners and Adaptive Filtering.
Start with existing presets for a specific species or
protocol—for example, human vs. small animal,
or stationary vs. exercising measurements.
The Channel Setup dialog contains a “Preset” popup menu by each channel that lists the current
Preset or, if no Preset has been selected for that
channel, the Calculation type (Integrate,
Difference, etc.). When selecting a Preset for a
particular channel, the channel is configured with
the settings associated with that Preset.
The Setup dialog has a “Presets” pop-up menu
that contains all of the Presets for the Calculation
type being configured. To enable the Preset popup menu, set at least one analog channel to
“Acquire” (calculation channels require a source
channel). For example, if a Difference Calculation
channel is being configured; all Presets for the
Difference Calculation will be listed. Just click the
Presets head and scroll to select the desired preset.
After selecting a Preset, the Setup dialog is
updated with the corresponding information.
§ The Setup dialog reads “none” if the
channel configuration doesn’t match any
Preset. The menu will flip to “none” when
the settings for a channel are changed
such that they no longer match a Preset.
§ To create a new Preset from existing
Calculation channels: Click “Setup” to
display the Calculation Setup dialog and
click the “New Preset” button. The settings will be applied to the current channel, and a prompt will be
generated to enter a name for the new Preset. Preset names cannot be duplicated, nor can the default
name of a Calculation channel type (Integrate, Difference, etc.). Newly-created Presets will be included
in the pop-up menus and saved with the file.
To reorder channel Presets (by type, use, etc.), choose Hardware > Organize Channel Presets and then
use the up/down buttons as appropriate (see page 257).
MP160/MP150 hardware: Presets are not applicable to and therefore not selectable on Analog or
Digital channels.
MP36R hardware: Presets are available on Analog channels but not Digital channels.
Watch the AcqKnowledge Preset Option video tutorial for a detailed demonstration of this feature.
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Integrate Calculation

The online Integrate Calculation offers three basic options:
Reset via channel. Perform a real-time integration of input data over a variable number of sample points.
This option is extremely useful for converting flow signals into volumetric equivalents. The integral of flow
is volume. For example, when recording airflow with a pneumotach, volume can be precisely calculated as
the flow varies in a cyclic fashion:
a) Real-time conversion of flow signals into volume signals (i.e., Blood flow à Blood volume; Air
flow à Air volume)
b) Any processing involving a need for a cyclic, continuous integral calculated in real time. For
example: Acceleration à Velocity; Velocity à Distance; Frequency à Number of cycles; Power
à Energy
Average over samples. Perform a moving average (mean) and associated processing (Rectify; Root mean
square) over the specified number of sample points. This option is useful to process EMG signals to:
a) Smooth noisy data
b) Display the real-time “integration” (rectified, then sample averaged) of the raw EMG data
c) Display the real-time “root mean square” calculation of the raw EMG data
d) Return real-time windowed standard deviation
Timed reset. This option is available in the Integrate calculation channel and transformation. This mode
computes a straight sum of the source data points and resets this sum after a fixed amount of time has
elapsed. This periodic integral is used in several types of analysis, such as EMG analysis where it can
generate an EMG signal or estimate the power in fixed time intervals. The time interval at which the
integral resets to zero may be specified in seconds or in samples. The timed integrate reset functionality
may also be used in calculation channel presets and by the Mac OS Integrate automator action.
To have AcqKnowledge perform an Integrate calculation in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels (click “View by Channels).
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the modified data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Integrate.
5. Click the Setup button in the Input Channels dialog to generate the Integrate dialog.
(Off-line Integrate is available under Transform > Integrate.)

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Destination
Determined by the calculation channel selected. (C0, C1, C2, etc.)

Source
Any Analog or Digital channel being acquired as well as any enabled Calculation channels with a lower
number.
Reset via channel (Integrate option)
This feature is used to integrate data over a data-dependent
interval. Either the source channel or a different channel
can control the integration process.
Control channel
Allows user to select any active channel as the integration
control channel. (Calculation channels must have a lower
number.)
Reset Thresholds
The threshold is to be set at points surrounding the flow
level. Typical values are:
LOW: a negative value close to 0.00
HIGH: a positive value close to 0.00
For airflow to volume conversion, the flow signal will vary
positively and negatively around zero flow.
Reset trigger
The Reset trigger polarity determines on which slope
(Positive - or Negative ¯) the integration process will begin
and end.
Mean Subtraction
This option will subtract the mean from the data evaluated during the integration period. If this option is
selected, the integration will only proceed after all the data in the integration period has been collected. When
collected, the mean value of all the data is subtracted from each data point in the integration period. In this
fashion, the integral of the corrected data points will result in the integral returning to exactly zero at the end of
the integration interval. Although this option will result in “well-behaved” integrations, the integrated data will
be delayed by a fixed amount of time, as specified by the max cycle period.
Online
Enabling mean subtraction delays the signal by the mean cycle length. It waits for that period of
time to pass so it can determine a mean value for the initial cycle, and it then tries to re-compute
this mean for each cycle. If the resets are too short or too long, the window expires and the
processing halts again until a new mean can be recomputed. Online processing may reset from
threshold crossing in the control channel or window expiration when it loses mean tracking.
Offline
Transformation version of this operation. Since all the data is available, the mean is computed
from the data in the channel and the signal is not delayed. Also, since it isn’t doing windowed
means, there are no window expiration events inserted. Offline processing may reset from
threshold crossing in the control channel.
Max cycle period
The Max cycle period should be longer than the maximum time expected from trigger event to trigger event in
the Control Channel. Typically, the default scale settings for cyclic integrated data will be fine.
Output reset events—not available for metachannels
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Add Events (markers) to show where Reset occurred and distinguish why the channel reached zero.
§ Threshold crossing on the
control channel
For example: Calculation
channel resetting on positive
crossings of 0V on CH 1.

§ Window expiry when mean
removal is enabled
For example: No threshold
crossing within “mean cycle
width” as specified in calc
channel setup. Settings of
calc channel: threshold
crossings positive, 3V, Mean
cycle subtraction, 1 second
period width. First reset is
due to threshold crossing;
second reset is due to
window expiry.
§ Zero value due to “true” zero
being achieved due to
mathematical results
For example: Mathematical
Source is sine wave, integral
is cosine. Input (10V) never
crosses threshold levels.
Signal reaches zero
mathematically; no reset
events appear on output.

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Average over samples (Integrate operation)
Online sample averaging can be useful when there
is a high degree of noise present in the data. At
least some of this noise can be “averaged out” by
pooling some number of adjacent data points
together, taking the average of these points, and
replacing the original values with the new averaged
values. This process creates a “window” of moving
averages that moves across the waveform
smoothing the data.
Integration used to smooth noisy data

Samples
To specify the number of data points to average across, enter a value in the Samples box. The number selected
will depend in large part on the selected sampling rate and the type of noise present. All things being equal, for
slower sampling rates it’s recommended to perform mean average across a smaller number of samples. As the
sampling rate is increased, integrate across more and more samples. As the number of samples specified in the
samples box increases, the amount of high frequency information contained in the data will decrease.
Parameters
Rectify —The Average over samples calculation
can also be used for producing an envelope of
modulated data. For instance, EMG waveforms
frequently contain high frequency information,
which is often of little interest compared to the low
frequency information also contained in the data.
When the Rectify option is checked,
AcqKnowledge will take the absolute value of the
input data prior to summing and a plot of the
waveform’s mean envelope over a specified
number of samples will be obtained.

Online “Average over samples” feature used as an
envelope detector

Typically, this option is only used for processing raw EMG and similar types of applications. The signal for
Rectify is normalized by a factor of (# samples averaged)/(Channel sampling rate).
Root mean square—provides the exact root mean square (RMS) of the input data (typically EMG) over the
specified number of samples.
Remove baseline—provides the exact standard deviation of the input data (typically EMG) over the specified
number of samples. When the mean of the input data equals 0-0, the standard deviation and the RMS will be
equivalent.
Scaling… button—Since the integration values are going to be on a different scale than the original units, it’s
necessary to change the scale of the integration channel to reflect the new units. Click the Scaling… button, to
generate the Change Scaling Parameters dialog.
The rescaling involves multiplying the “Input units” values by a factor determined by the sampling rate and
number of samples mean averaged across.
Map or Scale value = Input units x

Sampling rate
Number of samples to be mean averaged

As an example, if data was being acquired at 75 samples per second, and the integration is to be completed
across an interval of 10 samples, configure the Integrate Setup Scaling parameters so that +10 Volts
corresponded to a Map (Scale) value of 75 and a Map (Scale) value entry of –75 reflected an Input value of –10
Volts.

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Ø It is important to note that this rescaling should be performed independent of any rescaling performed
on analog channels themselves. Even if an analog channel is being rescaled to some other units, the
input values in the integration scaling should be set to +10 Volts (next to Cal 1) and –10 Volts (next to
Cal 2).

Integrate Calculation and Scaling dialogs for 10 point averaging
When data is averaged in this way, a portion of the data at the beginning of the record (equivalent to the number
of samples being integrated) should be ignored, as they will reflect a number of zero values being averaged in
with the first few samples of data.
Timed Reset (Integrate operation)

Timed Reset operation computes a straight sum of the source data points and resets this sum after a fixed
amount of time has elapsed. This periodic integral is used in several types of analysis, such as EMG analysis
where it can estimate the power in fixed time intervals.
The time interval at which the integral resets to zero may be specified in samples, milliseconds, seconds,
minutes or hours.
Timed reset functionality may also be used in calculation channel presets and by the Mac OS Integrate
automator action.

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Smoothing Calculation
The Smoothing Calculation is useful for removing noise of varying types from a data set.
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the
modified data. Check the Plot and Values boxes as appropriate
for each channel.
4. Click the Preset pull-down menu and select Smoothing.
5. Click the Setup button in the Input Channels dialog to generate
the Smoothing dialog.
(Off-line Smoothing is available under Transform > Smoothing.)
Source
Smoothing factor
Smoothing method
Mean value

Source is a pull-down menu of the available channels.
enter the number of samples to use as a smoothing factor.
This calculation channel provides real-time Mean (default) or Median smoothing.
The default is mean value smoothing. Use Mean value smoothing when noise appears in a
Gaussian distribution around the mean of the signal.
Use Median value Click in the box to activate Median value smoothing if some data points appear completely
aberrant and seem to be “wild flyers” in the data set.
For a given sequence of wave data, x = {x1, x2,...,xn}, Median value smoothing will sort the
sequence and extract the median equivalent to the recommended NIST (National Institute
of Standards and Technology) formula:
· n is odd: median is the center element of the sorted list of n items.
· n is even: median is the mean of the center pair of elements of the sorted list of n items.
The smoothing calculation channel is the primary method of computing real-time median
values using the definition of median as given above. The smoothing output at a sample
position is the median of the window of source channel samples including the current
sample and the previous samples in the window.
The size of the window is 1 at the start of acquisition and increases incrementally until
the final window size is reached. The median extraction method shifts between even and
odd definitions as the window size is incremented.
Scaling
Click the Scaling button to access options that allow modification of units or to linearly
scale the output.

Watch the AcqKnowledge Smoothing video tutorial for a detailed demonstration of this feature.

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Difference Calculation
The Difference calculation returns the difference between two data samples over a specified number of intervals
and divides the Difference by the time interval spanned by the data values. The Difference Calculation is useful
for calculating an approximation of the derivative of a data set in real time.
To have AcqKnowledge perform a Difference calculation in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the modified data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Difference.
5. Click the Setup button in the Input Channels dialog to generate the Difference dialog.
(Off-line Difference is available under Transform > Difference.)
Options in the Difference Calculation dialog specify the source channel and the number of intervals between
samples over which the difference is to be taken, and includes the option of rescaling the channel to reflect
different units.
Click the Setup button in the Input Channels dialog to generate the Difference dialog:

Source
Intervals

When the Source channel contains relatively high frequency data, the Difference Calculation
may result in a very noisy response, so it’s best to use Difference on relatively smooth data.
Difference is calculated with respect to the number of intervals between points (rather than the
number of sample points). For instance, two sample intervals span three sample points:
POINT POINT POINT
A 1-interval difference transformation applied to a blood pressure (or similar) waveform will
result in the widely used “dP/dT” waveform.

ü See page 321 for a complete description of the online Difference function.
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Rate Calculation

The Rate Calculation is used to extract information about the interval between a series of peaks in a waveform.
This interval can be scaled in terms of BPM (the default), frequency (Hz), or time interval between peaks.
Ø The BPM (or beats-per-minute) Rate function is used as a measure of peaks or events that occur in a
sixty-second period.
Ø The frequency rate function is commonly used to describe the periodicity of data, or the amount of
time it takes for data to complete a full cycle (from one peak to the next peak).
Ø The Interval Rate function returns the raw time interval between each adjacent pair of peaks, which is
essentially the inter-beat interval (IBI), frequently used in cardiology research.
These three functions essentially provide the same information in different formats, since a frequency of 2Hz is
equal to an inter-peak interval of 0.5 seconds, both of which are equivalent to a BPM of 120. Other options
allow for the recording of maximum or minimum value of all peaks (the peak max/min option), or to count the
aggregate number of peaks (the count peaks option).
In order to calculate Rate information, there is the option to specify the threshold manually or have
AcqKnowledge automatically compute the default threshold value. This section describes the basic parameter
settings for typical online Rate Calculations.
NOTE: Parallel functions can be performed after data has been acquired. A
detailed description of the Rate Calculation options can be found in the Find
Rate section on page 358.
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To perform a Rate Calculation in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the modified data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Rate.
5. Click the Setup button in the Input Channels dialog to generate the Rate dialog.
(Off-line Rate calculation is available under Analysis > Find Rate.)
Source—selected from the Source popup menu at the top of the dialog.
Label—Use to create a label for the Rate channel
Preset—Use to select from 17 pre-defined calculation channel presets. New presets affecting source channel,
label and output settings can be created and saved by clicking “New Channel Preset.”
Signal Parameters Tab
Signal Type—Contains parameters for specific human and animal waveform morphologies. Choose from six
pre-defined heart rate and respiration signal types, or click “New” to create and save custom setups. Unlike
channel presets, all pre-defined and custom signal types appear in both calculation channel Rate (online) and
analysis Rate (offline) dialogs. Signal type modifications affect settings in the Signal Parameters tab only. For
more details on Rate signal types, see page 361.
Peak Detect—Choose whether to look for positive or negative peaks in the signal.
Remove baseline—provides the exact standard deviation of the input data (typically EMG) over the specified
number of samples. When the mean of the input data equals 0-0, the standard deviation and the RMS will be
equivalent.
Baseline window width—Width of the window for the difference operation applied prior to peak detection.
(E.g. the value of the source x ms previously is subtracted from the current value to generate the signal that is
analyzed with the peak detection.)
Auto Threshold detect—The most convenient way to calculate a Rate channel online is to have
AcqKnowledge automatically compute the threshold value (the “cutoff” value used to discern peaks from the
baseline). This is done by checking the Auto Threshold detect box.
Noise rejection—AcqKnowledge constructs an interval around the threshold level when Noise rejection is
checked. The size of the interval is equal to the value in the noise rejection text box, which by default is equal to
5% of the peak-to-peak range. Check this option to help prevent noise “spikes” from being counted as peaks.
Cycle Interval Window—When “automatic” Rate Calculations are set, specify a minimum rate and a
maximum rate. These parameters define the range of expected values for the Rate Calculation. By default, these
are set to 40 BPM on the low end and 180 BPM on the high end.
The Rate Calculation will use these values to find and track the signal of interest, assuming the input BPM
range is reasonably well bracketed by these values. Depending on the shape of the input cycle waveform, the
Rate window settings may be closer or further from the expected rates.
Ø For ECG-type data (where the waveform peak is narrow with respect to the waveform period), the
Rate window values will closely bracket the expected values.
Ø For more sinusoidal data, with the waveform energy distributed over the waveform period (as with
blood pressure or respiration), the Rate window will closely bracket the expected rate on the high-end,
but can be up to twice the actual measured rate at the low-end.
One of the most frequent applications of the Rate Calculation is to compute BPM online for
ECG, pulse, or respiration data. For more information on optimizing ECG amplifiers for online
calculation of heart rate, see the ECG100C section of the Hardware Guide.
Windowing Units—Use to select the unit type to be used in the rate detection. The options are Hz, BPM and
seconds.

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Output Tab
Function —The popup menu includes options to scale the rate in terms of Hz, BPM, Interval, Peak Time,
Count Peaks, Peak Minimum/Maximum, Peak-to-Peak, Mean Value, Area or Sum.
Ø For more information on each of these functions, see the Calculation Channels section beginning on
page 129.
Ø Calculate systolic using the peak maximum Function, diastolic using the peak minimum Function, and
mean blood pressure using the mean value Function.
Ø NOTE: All of these Function options are available in the post-acquisition mode through
the Analysis > Find Rate function.
Use Averaging mode—Use to average the output of the selected function. Averages can be based upon a fixed
time window or a fixed number of cycles. The ‘Recompute on every cycle’ option will start the averaging
output after N numbers of cycles are detected and then remain fixed until the next N cycles are detected.
Output reset events (not available for metachannels)—When auto threshold detection is being used, the
minimum and maximum rates of the signal are specified in the Windowing controls. If the input signal falls out
of this range, the value of the rate function and automatic threshold level will be reset. By enabling “Output
reset events” a reset event will be placed on the output at the location of these window expirations. Rate
detector is set to “Peak function, default window of 40 BPM to 180 BPM, auto threshold detect for positive
peaks. The reset event occurs after the window expiration, approximately a full 40 BPM interval after the
“peak” transition from 0 to 5 volts in the source signal.
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Show Threshold—Plots the threshold used by the Rate calculation function.
Show Modified—Plots the modified data as processed by the Rate Detector. Typically, the modified data is a
differential version of the original input data. The data will be modified if the “remove baseline” feature is
checked.

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Math Calculation
The Math Calculation performs standard arithmetic calculations using two waveforms or one waveform and a
constant. Calculation channels with lower channel numbers may be also used as a waveform.
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the modified data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Math.
5. Click the Setup button in the Input Channels dialog to generate the Math dialog.
(Off-line Math calculation is available under Transform > Waveform Math.)
Use the pull-down Source menus to select the source channels (Source 1 and Source 2).
The Sample rate line provides the sample rate for the channel selected as Source; the channel sample rate may
be different than the acquisition sample rate.
Use the pull-down Operation menu to select a function. In the example below, analog channel 1 (Source: A1) is
added to analog channel 2 (Source: A2). To use this summed waveform as an input for another Math
Calculation channel. One useful application would be to divide this waveform (C0) by K, where K=2, thus
producing an arithmetic average of source channels A1 and A2.

The “Constant” entry is activated when “K” is selected as a Source.
As an alternative to creating an additional Calculation channel for dividing the summed waveform, use the
scaling function to perform the same task. To do this, click Scaling… button and then set the Map (Scale) value
for the summed waveform equal to +5 and –5 (to correspond to Input Volts values of +10 and –10 respectively).
This will effectively plot the sum of channels A1 and A2 as the arithmetic mean of the two waveforms.
For additional information, see the sections on Function Calculation channels (page 145) and online
Expression, page 148).
For complex calculations (such as squaring a waveform then adding it to the average of two other
waveforms,) Expression is a more efficient solution. These calculation channels allow more complex
operations. Metachannels (page 130) allow the user to chain multiple calculation channels together.
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Function Calculation
The Function calculation can be used to perform a variety of
mathematical functions to a single waveform. Like math
Calculation channels, function Calculations can be chained
together to produce complex functions (such as taking the absolute
value of a waveform on one channel and Calculating the square
root of the transformed waveform on another channel). These
same functions are also available under the transform menu in
AcqKnowledge for post-hoc operations. Many of these functions
can also found in the online Expression, see page 148 for details).
To have AcqKnowledge perform a Function Calculation in real
time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to
contain the modified data. If necessary, also check the Plot
and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Filter.
5. Click the Setup button in the Input Channels dialog to
generate the Function dialog.
(Off-line Function calculation is available under Transform >
Math Functions.)
Other mathematical Functions are available in the online
Expression (see page 148). Function Calculations can be chained
together to produce more complex Calculations, although it is
more efficient to program complex functions using the Expression
calculation.
The Sample rate line provides the sample rate for the selected
channel (may be different than the acquisition sample rate).
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Function
Abs
Atan
Exp
Limit
Ln
Log
Noise
Sin
Sqrt
Threshold

Returns the absolute value of each data point
Computes the arc tangent of each data point
Takes the ex power of each data point
Limits or “clips” data values that fall outside specified boundaries
Computes the base e logarithm for each data point
Returns the base 10 logarithm of each value
Creates a channel of random noise with a range of ± 1 Volt
Calculates the sine (in radians) of each data point
Takes the square root of each data point.
Converts above an upper threshold to +1 while converting data below a lower threshold to 0.

Thresholding Algorithm Assume a domain variable t Î {t start ,t start + 1,t start + 2,K

}

with tstart being an integer, a real-valued signal y(t) defined for all t, and two real valued levels ylow
and yhigh satisfying the relation y low £ y high .
Define the Threshold function thresh(t) function such that:
ì0
ì1 y(t start ) ³ y low
ï
thresh(t start ) = í
thresh(t) = í1
î0 y(t start ) < y low
ïthresh(t -1)
î

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y(t) < y low
y(t) > y high
y low £ y(t) £ y high

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Filter IIR Calculation
The Filter IIR Calculation channel performs real time digital filtering on analog, digital, or calculation channels.
To have AcqKnowledge apply a digital Filter IIR Calculation in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the filtered data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Filter.
5. Click the Setup button in the Input Channels dialog to generate the Filter dialog.

Filter Setup & Output Options
In the dialog above, the signal on analog channel one (A1) is run through a low-pass filter that attenuates data
above 50 Hz. The “Q” for this filter is 0.707, which is the default.
One possible application of the online filtering option is in conjunction with the Show Input
Values option (see page 241). Raw EEG data, for instance, can be filtered into distinct
bandwidths (alpha, theta, and so forth) using one source channel and multiple filter Calculation
channels. The filtered data can then be displayed in a bar chart format during the acquisition
using the Show Input Values option.
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Source
Set the source channel.
Sampling rate Select this to compute the frequency at the start of acquisition as a fraction of the channel
sample rate. (Unselected by default.)
Type (Output) Lists the filter options: low pass, high pass, band pass, band pass (low + high), band stop, and
comb band stop. See About Filters in this section for more details on filter types.
Frequency
Fixed value—Type a value in the entry box.
Sampling rate—Sets the frequency to a fraction of the sampling rate and automatically updates
when the sample rate is modified.
Line frequency—Uses the line frequency at which the data was recorded.
Q coefficient The online IIR have a variable Q coefficient. The Q value entered in the filter setup box
determines the frequency response patterns of the filter. This value ranges from zero to infinity,
and the “optimal” (critically damped) value is 0.707 for the Low pass and High pass filters, and
5.000 for the Band pass and Band stop filters. If desired, the Q can be changed. A more detailed
explanation of this parameter and digital filters in general, can be found in Appendix B.

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About Filters
While the technical aspects of digital filtering can be quite complex, the principle behind these types of filters is
relatively simple. Each of these filters allows a cutoff point to be set (for the low and high pass filters) or a
range of frequencies (for the band pass and band stop filters).
Ø A Low Pass filter allows specifies a frequency cutoff that will “pass” or retain all frequencies below
this point, while attenuating data with frequencies above the cutoff point.
Ø High Pass filters perform the opposite function, by retaining only data with frequencies above the
cutoff, and removing data that has a frequency below the specified cutoff.
Ø Each type of Band Pass filter is optimized for a slightly different type of task.
The Band Pass (low + high) filter is designed to allow a variable range of data to pass through the filter.
For this filter, it’s necessary to specify a low frequency cutoff as well as a high frequency cutoff. This
defines a range or “band” of data that will pass through the filter. Frequencies outside this range are
attenuated. The Band pass (low + high) is actually a combination of a low pass and a high pass filter,
which emulate the behavior of a band pass filter. This type of filter is best suited for applications where
a fairly broad range of data is to be passed through the filter. For example, this filter can be applied to
EEG data in order to retain only a particular band of data, such as alpha wave activity.
The alternative Band Pass filter requires only a single frequency setting, which specifies the center
frequency of the band to be passed through the filter. When this type of filter is selected, the “width” of
the band is determined by the Q setting of the filter (discussed in detail below). Larger values for q
result in narrower bandwidths, whereas smaller Q values are associated with a wider band of data that
will be passed through the filter. This filter has a bandwidth equal to Fo/Q, so the bandwidth of this
filter centered on 50 Hz (with the default Q=5) would be 10 Hz. This type of filter, although
functionally equivalent to the band pass (low + high) filter, is most effective when passing a single
frequency or narrow band of data, and to attenuate data around this center frequency.
Ø The Band Stop performs the opposite function of a band pass. A Band stop filter defines a range (or
band) of data and attenuates data within that band. In this case, the Band stop filter is implemented in
much the same way as the standard Band pass, whereby a center frequency is defined and the Q value
determines the width of the band of frequencies that will be attenuated.
Ø The Comb Band Stop removes interfering harmonics; resonance, aliasing, and other effects may
generate interference at multiples of a base frequency. It combines all the required filters instead of
requiring a separate filter for each interfering overharmonic. For setup details, see page 303.
Off-line filtering
Apart from these online filter options, similar filters can be applied after an acquisition is terminated via the
Transform > Digital Filters menu. Many of the biopotential amplifiers available from BIOPAC have selectable
filters, which allows for filtering of certain frequencies (including 50 Hz or 60 Hz electrical noise) and possibly
reduce the need for online filters.
Digital filtering can also be performed after an acquisition using the same types of filters. Choose from the
different filter types by selecting Digital filters from the Transform menu. The filters available after the
acquisition use a different algorithm but operate in essentially the same way.
For more information on digital filters and filters that can be applied after an
acquisition, turn to the Digital Filtering section on page 297 or Appendix B.
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Expression

The online Expression calculation channel is available for performing computations more complex than
possible in the Math and Function calculations, and is additionally available as an offline transformation and a
measurement. (Different attributes may apply to each available Expression type.) The Expression calculation
will symbolically evaluate complex equations involving multiple channels and multiple operations.
AcqKnowledge can perform conditional evaluation, data extraction, logical operations, expressions requiring a
range of samples or the results of the previous expression, and evaluation of generic formulas that can be
expressed in a closed, recursive form.
Unlike the Math and Function calculations—which can only operate on one or two channels at a time—the
Expression calculation can combine data from multiple analog channels, and can also specify other Calculation
channels as input channels for Equation channels. Also, computations performed by the Expression calculation
eliminate the need for “chaining” multiple channels together to produce a single output channel.
While the Expression calculation is more powerful than other Calculation channels, each Expression calculation
requires more system resources than other Calculations. This essentially means that acquisitions that utilize
Equation calculations are limited to a lower maximum sampling rate than acquisitions without online
Expression functions. When an expression is evaluated, it is actually evaluated multiple times. The expression
is computed starting at the first sample acquired, and is then evaluated once for each successive acquired
sample.
AcqKnowledge can accept the notations SC, MC, and CHn to reference the sample at the current evaluation
position or SC(x), MC(x), and CHn(x) for values at locations prior to the present evaluation location using
an offset expressed in sample intervals. For example, CH1(-1) will give the previous sample of Channel 1*.
The same features that are available in online Calculation channels are also available under the Transform menu
for evaluation of complex equations after acquisition. Thus, simple Calculations such as summing two channels
or finding the absolute value of a channel (and so forth) are best performed in either the Math calculation
channels or the Function calculation channels.
On the other hand, for complex Calculation channels, such as squaring one channel, multiplying it by the sum
of two other channels, and dividing the product by the absolute value of another waveform, a single Expression
calculation channel is more efficient than chaining five Math and Function calculation channels.
*Exception: Negative offsets are not defined when appending data to disk. Expressions making use of such
notation are invalid after the first segment of data has been acquired in this acquisition mode.
Save to Calculation Channel
To evaluate an expression and save the result to a Calculation channel in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.

2. Click the Calculation tab.

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3. Check an Acquire box for the Calculation channel to contain the modified data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.

4. Click the Preset pull-down menu and select Expression.
5. Click the Setup button in the Input Channels dialog. This will produce a dialog for entering the
expression to be evaluated.
(Off-line Expression is available under Transform > Expression or Measurements > Expression.)
The different components of each expression can be entered either by double-clicking buttons from the button
rows (sources, functions, and operators) in the setup expression dialog, or by typing commands directly into the
Equation box. The Expression calculation uses standard mathematical notation.
For each expression, it’s necessary specify at least one source, the function(s) to be performed, and any
operators to be used. Sources are typically analog channels, although Time may also be selected from the source
button row and AcqKnowledge will return the value of the horizontal axis (usually time) for each sample point.
When the horizontal axis is set to frequency (in the Display > Horizontal axis dialog), the “time” item in the
source button row will switch to “frequency.”
When using the online Expression calculation channel, it is important to keep in mind that while different
channels, functions, and operators can be referenced, the Calculation cannot reference future sample points. See
the section on post-acquisition expression commands (beginning on page 323) for ways around this limitation.
Functions
The arguments to each function are represented in the Functions table in italics and may
be replaced by any valid expression. Each argument is separated from its next argument
by a comma. Expressions can only contain commas within balanced parenthesis pairs. An
ellipsis (.”..”) at the end of a function description indicates that any number of arguments
may be present provided they are in a comma separated list. When a function is added to
an Expression, the cursor is placed between the parentheses.
Conditionals
Change output based upon a condition test. All of the conditionals treat the value zero as
false and any non-zero value as true. Expressions can only contain commas within
balanced parenthesis pairs.
Offset Notation
Offset notations take integer offsets in terms of the number of samples using the
formation CH#(P) where CH# is the channel number and P is the number of points. For
example, an offset of -1 will return the data point immediately to the left of the selected
point and an offset of +1 will return the data point immediately to the right of the selected
point.
To refer to previously acquired data, offsets must be negative. For notational
convenience, offsets that result in an invalid negative sample position (e.g. no data is
defined prior to the first sample in the graph) evaluate to zero. Any attempt to access a
sample beyond the end of the data will result in an error. Any attempt to use a positive
offset for an online Expression calculation channel will result in an error.
CHn(x) Returns the value of channel with index n x samples away from the current
evaluation position.
SC(x) Returns the value of the selected channel x samples away from the current
evaluation position. Only allowed for Transformations and Measurements; not
allowed for Calculations.
MC(x) When x is zero or positive, returns the value of the measurement channel x
samples away from the current evaluation position. When x is negative, returns
the result of the expression evaluation that occurred x steps previous to the
current evaluation position. Only allowed for Measurement Expressions (see
below); not allowed for Calculations or Transformations.

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Recursive notation

Expression
Measurement

Since transformations and calculation channels replace the source data of the channel
with the result of the expression evaluation in sequence, negative offsets are equivalent to
returning the final result of the expression that was evaluated a certain number of steps in
the past. The channel where the expression results are stored can be thought of as a
storage record of the previous evaluation steps. Negative sample offsets, therefore, can be
used to compute any formula that can be expressed in closed recursive form. For
example, the recursive definition of the Fibonacci sequence is:
Fn = Fn-1 + Fn-2
To evaluate this as an expression transformation, use the expression:
SC(-1)+SC(-2)
Note that to actually get the Fibonacci sequence; the selected channel would need to have
a constant value of one prior to the transformation.
Measurements are powerful tools for quick manual analysis and also for advanced
automated analysis when combined with the Cycle/Peak detector. Expression
measurements extend measurements to evaluate simple formulas or complex data
reduction. Each Expression measurement has an expression associated with it and the
measurement result is derived from computing the Expression(s) on the selected data.
Measurement expression dialog is
generated the first time a measurement is
set to Expression or when the
measurement preset button is clicked.
Preset menu allows access to pre-loaded
commonly used expressions and displays
user-defined custom presets, along with
a list of recently-used expressions.
OK invokes a syntax check. If there is an
error, the user will be prompted to
correct the error and the error will be
selected (highlighted) in the Expression
edit field.
Cancel discards any changes to the
Expression measurement and reverts
back to the previous Expression.
Clear erases the current contents of the
expression edit field.
Measurement Channel
Expression measurements can reference the “measurement channel” (MC), which refers
to either the selected channel or a specific channel as set in the measurement channel
selection box within the graph window.
Negative sample offsets to MC are interpreted as returning the result of the Expression
from a prior step. Transformations and calculation channels achieve this as they replace
the contents of their destination channels sequentially. Measurements, however, do not
actually replace the data of their source channels. Expression measurements are actually
executed on a temporary copy of the channel data in memory. This implies that negative
indicies to the measurement channel are interpreted exactly the same for measurements
as for transformations and calculation channels even though the “transformed” data of the
measurement is not visible. Negative sample offsets to MC that refer to the sample
position prior to the leftmost sample of the selected area will always return zero.

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Evaluation Rules
When a new selection is made, the first step in evaluation searches through the
Expression measurement for any MMT() invocations. Any measurement whose value is
needed by MMT() is computed at this time prior to the Expression evaluation. This
behavior is similar to calculation channels and successfully allows measurements to the
right and bottom of the Expression measurement to be used in the expression.
The expression is subsequently evaluated from the leftmost sample in the selection to the
rightmost sample. It is evaluated at the waveform sampling rate of its source channel,
with one expression evaluation per sample contained within the selected area.
Interpolation is not used at the boundaries to maintain a consistent sample interval for the
expression. After each expression evaluation, the result is cached in memory for potential
negative MC result references.
The value of the final expression, the rightmost sample, becomes the result of the
measurement.
Circularity Detection
Expression measurements may reference other expression measurements or calculation
measurements by using the MMT() function in the expression. This raises the possibility
of circular dependencies being formed by the user if a measurement expression either
directly or indirectly needs its own value to compute a MMT() invocation. Circular
dependency checking will be in place at execution time and will result in an error.
To refer an Expression measurement to its own value, use the MC notation.
Error Reporting
The Expression measurement result will display the text “Error” if there are syntax errors
in the Expression measurement, errors computing measurements referenced by MMT(),
or a circularity.
To function correctly, AcqKnowledge requires real-valued data. BIOPAC recommends
ensuring that all expression results are real-valued. To test if a floating point number x is
a real-valued number, use the expression:
NOT(OR(ISINF(x), ISNAN(x)))

Note for variable sample rate processing:
The Expression and Waveform Math functions will constrain operations between waves of different rates as
follows:
If an equation is operating on two or more waves of different sample rates, the result of the operation will
always be output at the lowest sampling rate from the waves (Flow). If the destination channel for the result has
an assigned rate other than (Flow), the operation will not be permitted. If the destination channel is set to a new
channel, the operation will always be permitted.
In AcqKnowledge 4 and higher, all sources for Expressions and Waveform Math operations must be sampled at
the same waveform sampling rate.
VSR data padding—If the channels are of unequal length (as a result of variable sampling rate or waveform
editing), they will be padded for Append acquisition. Digital and Analog channels are stored as short integers by
default; a waveform paste into a digital or analog channel, however, will result in its underlying data being
converted to floating point. This will generate the “Abort/Replace” warning for pastes to Digital or Analog
channels since the data format has changed since the last acquisition.
Additionally, if an Analog or Digital channel is used as the source waveform for a Copy, it will also be converted
to floating point and will result in the “Abort/Replace” warning being generated.
Since Calculation channels are already floating point, pasting into them or copying from them will not change
their data format. The channels will be padded with their last value and the append will commence.
Waveform Cut operations do not change the underlying data format for Analog, Calculation, or Digital channels.
If only Waveform Cut is used, no data format conversion will occur and channels will be padded with their last
value and subsequent appends are allowed.

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Source

Description

ACQLENGTH

Calculation only Acquisition length from
Set Up Acquisition; keeps Appended
segments the same whereas “Sample”
would increase with each segment.

+

Addition

-

Subtraction

*

Multiplication

CH

Value of the designated channel (CHn) at
the current evaluation step.

/

Division

^

Power

Primary Source
Channel
metachannels only

Appears as PSC in the dialog. Refers to
the data of the primary source channel of
a metachannel.

(

Open parentheses

)

Close parentheses

Time

Time (in sec) of current evaluation step

Sample

Sample index of evaluation step; the first
sample in the graph will always be
reported as a value of zero.

MC

Measurements only Value of the channel in
the measurement menu—either the
explicit channel or “SC”—at the current
evaluation step.

Pi

Value of pi (3.141592654…) to doubleprecision accuracy.

SC

Transformation and measurement only Value
of the selected channel at the current
evaluation step; can still back-reference
samples points.

True

Evaluates to the value 1 (non-zero values
are interpreted as True)

False

Evaluates to the value 0

Segment Timer

Used as a source for the onscreen
Stopwatch gauge view.

Random

Generates random white noise.

Gaussian
Random*

Generates Gaussian white noise for
startle responses. Returns a random
value from a Gaussian distribution.

Operator

*Standard Gaussian model; useful for peak fitting.
param(0)*EXP(-((TIME-param(1))/param(2))^2

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RESULT

ABS

Returns the absolute value of each data point.

ACOS

Computes the arc cosine of each data point in radians. (All trigonometric functions
use 'radians' as the unit of angle for input or output as appropriate.)

AND(x, y, …)

Computes a logical “and” operation for its arguments. Accepts up to eight (8)
arguments and evaluates to
1 if all of its arguments are non-zero values.
0 if one of its arguments is zero.

ASIN

Calculates the arc sine of each value in radians. (All trigonometric functions use
'radians' as the unit of angle for input or output as appropriate.)

ATAN

Computes the arc tangent of each sample point in radians. (All trigonometric
functions use 'radians' as the unit of angle for input or output as appropriate.)

CEIL(x)

Computes the ceiling function (the closest integer larger than the value x).

COND(T, A, B, C) Three-way conditional takes four arguments:
COND(test_expr, neg_test_value, zero_test_value, pos_test_value)
Evaluates test_expr and if
< 0, returns neg_test_value
= 0, returns zero_test_value
> 0, returns pos_test_value
COS

Returns the cosine of each data point in radians. (All trigonometric functions use
'radians' as the unit of angle for input or output as appropriate.)

COSH

Computes the hyperbolic cosine of each selected value

EQUAL(x, y, …)

Performs a Logical equal (numerical comparison) of its arguments. Accepts up to
eight (8) arguments and evaluates to
1 if all of its arguments are equal.
0 if one of its arguments is not equal to the others.

EXP

Takes the ex power of each data point..

FLOOR(x)

Computes the floor function (the closest integer less than the value x).

IF(T, A, B)

Two-way conditional takes three arguments:
IF(test_expr, true_value_expr, false_value_expr)
The conditional evaluates test_expr and if
non-zero, returns true_value_expr
0, returns false_value_expr

ISINF(x)

Filters out infinities and unrepresentable numbers from data; important because
such values can cause erratic behavior in autoscaling and other operations. Use to
test whether any expressions have resulted in floating point overflow and have
generated numbers too large to be represented in the computer. Evaluates to
1 if x is inf, the floating point representation of infinity.
0 if x is NaN or a real-valued floating point number.

ISNAN(x)

“Is not a number” can be used to test whether any expressions have resulted in
floating point errors such as division by zero. Use to ensure that the output of
transformations and equations does not produce numbers that AcqKnowledge
cannot display. Evaluates to
1 if x is NaN, the invalid floating point number.
0 if x is inf or a real-valued floating point number.

LESS(x, y)

Performs a numerical comparison of its arguments and evaluates to
1 if x is less than y.
0 if x is greater than or equal to y.
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FUNCTION

RESULT

LOG

Computes the natural logarithm of each value

LOG10

Returns the base 10 logarithm of each value

MAXIMUM

Returns the maximum value of all input arguments.

MINIMUM

Returns the minimum value of all input arguments.

MMT(x, y)

Indicates that “x” is the row and “y” is the column of the measurement being
referenced. x and y are zero-based meaning that the measurement at the top left is
"MMT(0, 0). MMT is available in Transform > Expression and in Measurement >
Expression but is not supported in the online Expression Calculation Channel
Functions.

NOT(x)

Computes a logical negation of its argument. Evaluates to
1 if x is zero.
0 if x is non-zero.

OR(x, y, …)

Evaluates multiple variables; true if any are true. Computes a logical “or” operation
for its arguments. Accepts up to eight (8) arguments and evaluates to
1 if any one of its arguments is non-zero.
0 if all of its arguments are zero.
Returns an integer closest in value to the argument. For example:
round (2.4) = 2 round(2.5) = 3 round(-1.5) = -1 round(-1.6) = -2
Calculates the sine (in radians) of each data point. (All trigonometric functions use
'radians' as the unit of angle for input or output as appropriate.)

ROUND(x)
SIN
SINH

Computes the hyperbolic sine for each sample point.

SGN

Performs the ‘sgn’ sign extraction function. Evaluates 1 if x > 0, -1 if x < 0, and 0 if
x = 0.

SQR

Squares each data point.

SQRT

Takes the square root of each data point.

TAN

Computes the tangent of each sample point in radians. (All trigonometric functions
use 'radians' as the unit of angle for input or output as appropriate.)

TANH
TRUNC(x)

Calculates the hyperbolic tangent of each sample point.
Removes the fractional part of the number and returns an integer. For example:
TRUNC(2.4)= 2 TRUNC(2.5)= 2 TRUNC(-1.5)= -1 TRUNC(-1.6)= -1

XOR(x, y, …)

Note When used with scientific notation, TRUNC(x) applies only to the fractional
portion after the exponential factor is taken into account: TRUNC(2.93E+4) =
TRUNC(29300) = “29300.” Since 2.93e+4 (29,300) has no fractional portion,
the number is returned unchanged. Similarly, TRUNC(2.931245E+4) =
TRUNC(29312.45) = “29312.”
Logical exclusive OR; true if an odd number is true. Computes a logical “exclusive
or” for its arguments (e.g. “one or the other, but not both”). Accepts up to eight (8)
arguments and evaluates to
1 if an odd number of its arguments are non-zero.
0 if an even number of its arguments are non-zero or
if none of its arguments are non-zero.

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Delay Calculation

Delay setup dialog and resulting graph showing a 20 sample delay
This option allows a Calculation channel to be used to plot another channel lagged (delayed) by an arbitrary
interval. To have AcqKnowledge apply a Delay Calculation in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the modified data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Delay.
5. Click the Setup button in the Input Channels dialog to generate the Delay dialog.
(Off-line Delay is available under Transform > Delay.)
The delay interval can be specified either in terms of samples or seconds. These types of plots are useful for
producing non-linear (“chaos”) plots in AcqKnowledge’s X/Y display mode (see page 34 for a description).
When a delay channel is recorded, there is a segment at the beginning of the Calculation channel (equal to the
value of the delay) that will read as 0 Volts. This is normal and occurs because the delay channel is waiting to
“catch up” with the original signal. AcqKnowledge fills this buffer with zeros until the delay channel begins to
plot actual data. In the example above, the delay channel contains a 0.25-second interval of zeros at the
beginning of data file.

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Control Calculation

The Control function is used to output a digital pulse when the value for a specified input channel exceeds a
certain level, falls inside a given range, or falls outside a given range. This feature is unique in that the output is
on a digital channel (which ranges from I/O 0 through I/O 15) rather than a Calculation channel. Also, unlike
other Calculation channels, this Control Calculation can only be performed in real time (i.e., while data is being
acquired) and cannot be performed in post acquisition mode.
In addition to outputting a signal on a digital channel, the Control Calculation will also plot an analog version of
the digital signal on the selected Calculation channel. In the example below, Calculation channel C0 is used to
perform a control function using analog channel 1 (A1) as an input and digital channel 0 (D0) as an output. In
addition to outputting a pulse on D0, the setup below will also produce a plot on channel 40 (the first
Calculation channel) that emulates the signal being output on digital channel 0. Since Calculations are analog
channels, the Calculation channel does not contain a “true” digital signal, but is a reasonably good
approximation. To retain the physical output generated by a Control channel, the output digital channel should
be looped back to another digital input channel of the Hardware unit and acquired as well as being connected to
any external devices. The calculation channel values are not guaranteed to precisely match the actual digital
output.
To configure AcqKnowledge to apply a Control Calculation in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the modified data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Control.
5. Click the Setup button in the Input Channels dialog to generate the Control dialog.
There are four parameters that need to be specified for each Control channel:
a) Source channel
c) Type of threshold function
b) Output channel
d) Threshold level values
“Source” refers to the input channel to be used for the Control function. As with other Calculation channels, the
Control function can use either an analog channel or another (lower) Calculation channel as an input. In the
previous example, analog channel 1 (A1) is used as the input channel. It is not possible to use a digital channel
as an input channel for a Control Calculation.

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The channel selected in the Output Channel section determines which digital channel the pulse will be sent to.
The digital channels range from 0 to 15 (D0 through D15) and external devices can be connected as described
in the section on HLT100C/UIM100C connections in the Hardware Guide. In the sample dialog shown, the
digital pulse is sent over I/O line D0.
Digital channels have two levels, 0 Volts and +5 Volts. When the signal transits from 0 Volts to 5 Volts, an
“edge” is created and since the signal is going from low to high, this is referred to as a positive edge. Similarly,
as the signal transits back from 5 Volts to 0, a negative edge is created. These transitions or edges can be used
to trigger external devices when an analog signal level meets certain threshold criteria.
The Threshold Function option sets the criteria for the Control channel. Threshold conditions can be configured
so that the digital I/O line goes to +5 Volts when the conditions are met, or it’s possible to program the digital
line to go to 0 Volts when the threshold conditions are met. Threshold conditions can be set so that either (a) the
digital line is switched when the value of an analog channel exceeds a specified value or (b) the digital line is
switched when an analog channel falls within a given range. AcqKnowledge also supports configuration of a
single level threshold or a “wide” threshold.
Tip To use test conditions more complicated than simple thresholding, combine the conditional tests of
Expression calculations with the Control channel to change digital output based on the Expression
result.
For example, suppose the user needs to set a Control channel to switch digital line 5 from low to high whenever
the signal for Calculation channel one (C0) exceeds 85 BPM. Set the source channel to C0 and the output to D5.
Select the upper right graph in the control dialog and set L2 and L1 to 85, as shown:

Control dialog and graph showing result of BPM control example
As observed in the preceding graph, there are a number of instances where C0 (heart rate) exceeds 85, usually
for a short period of time. When it does drop below 85, it appears to return to a value greater than 85 within a
second or two. In instances such as this, it might be useful to “widen” the threshold so that the digital line is
triggered whenever the input value is greater than 85, but the signal must drop significantly below the threshold
value before the threshold is reset.

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As another example, the upper threshold value (L2) is set to 85 and the lower threshold (L1) is set to 83, which
means that the threshold will not reset until the signal from the source channel drops below 83. In the following
example, the digital line is switched from low to high (from zero to +5 Volts) when the heart rate channel
exceeds 85, and stays at +5 Volts for several seconds even though the source channel drops below 85 (but
above 83). The digital line does not switch back to zero until the heart rate channel drops below 83 (toward the
end of the record). Once this occurs, the threshold is reset and the digital line will switch again the next time the
source channel exceeds 85 BPM.

Control dialog and graph showing control channel with “wide” threshold
It is also possible to have the digital line switch when the source channel drops below a certain value. In the
example below, a simple threshold is used to switch the digital line high each time the source channel drops
below 50 BPM. Since L2 and L1 are set to the same value, this is not a “wide” threshold (as above) and the
threshold resets each time the source channel goes above 50 BPM.

Control dialog and graph showing control channel detecting source channel levels less than 50 BPM
These examples are only a few of the possible applications of the control channel using the two threshold icons
on the left-hand side of the Control Setup dialog. It’s possible to construct variations of these (i.e., switching the
digital line from low to high using a wide threshold whenever the source channel drops below a given channel)
that are not discussed above. Moreover, each of the options can be construed somewhat differently than they
have been presented here. For example, the previous example switches the digital line from low to high each
time the signal on the source channel drops below 50 BPM. Conversely, it also switches from high to low each
time the source channel value is greater than 50 BPM. This allows the default setting for the digital channels to
be varied (whether the default is zero or +5 Volts) depending on what types of devices are connected.
(For a description of how to connect various digital devices, see the section on HLT100C/UIM100C
connections in the MP Hardware Guide.)

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In addition to setting “above and below” type thresholds, it’s also possible to program the Control channel such
that the digital line is switched whenever the source channel falls within a given range or outside a specified
range. In the example that follows, digital line 15 is set to switch from zero to +5 Volts whenever the source
channel signal falls between the values entered in the L1 and L2 boxes. In this case, I/O is switched to +5 Volts
whenever the heart rate is greater than 60 BPM but less than 80 BPM.

Control dialog and graph showing control channel switching from
low to high when source channel is between 60 BPM and 80 BPM
The digital line can be programmed to switch from high to low when the signal on the source channel falls
within a given range. This is equivalent to setting the digital line to shift from low to high when the source
channel values fall outside a given range (as shown below).

Control dialog and graph showing control channel switching from
high to low when source channel is between 60 BPM and 80 BPM
AcqKnowledge 5.0.3 and higher: In addition to digital pulses, the Control function can also be used to output
any supported Event marker type. To do this, select Events and Event type from the Output menu options.

Control Event markers can be inserted at positive or negative transitions or recorded for both directions.

For more information about Events, see the Chapter 11 “Set Up Event Marking” on page 224.

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Fourier Linear Combiners: FLC, WFLC, CWFLC Calculations
Fourier Linear Combiners are linear combinations of adaptable sinusoidal functions that are particularly well
suited to processing cyclic data. Sine and cosine are harmonics that are multiples of a base frequency that are
summed together, and the order is the fixed number of harmonics used in the model. Step size provides mu, the
gain factor used to adjust the weights of the harmonics at each processing step. Step sizes must be much less
than 1 for the system to converge. As step sizes decrease, relaxation time lengthens. The FLC model is adjusted
based on the source data using least means square (LMS) feedback and the bias compensates for DC offset.
To have AcqKnowledge apply an FLC Calculation in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the filtered data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select FLC, WFLC, or CWFLC.
5. Click the Setup button in the Input Channels dialog to generate the appropriate dialog.
Ü For offline calculation, see FLC Transform options, including Scaled FLC, on page 306.
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Basic FLC
Simple summation of fixed
numbers of sines and cosines;
uses harmonics of a fixed
frequency and adjusts weighting
coeffiicients of the mixture.

Weighted-Frequency FLC
Base frequency of the harmonics
is variable; adapts the frequency
in response to the input signal
using LMS feedback; the
frequencies are similarly adjusted
to the amplitudes.

Coupled WFLC/FLC
Runs a WFLC on the signal to
determine the harmonic frequency
and then runs the result through an
FLC using the computed harmonic.

Operates on a single channel at a
time.

Operates on a single channel at a
time.

The second FLC can be run on the
same or a different channel.

Well suited for extracting data of
a known frequency band from a
signal with a stable frequency.
§ Use as an adaptive noise filter
to remove non-periodic and
semi-periodic noise
uncorrelated to the base
harmonic frequency.

Well suited for modeling periodic
signals of an unknown and
potentially varying frequency
and/or amplitude.
§ No cycle boundaries or
frequencies need to be predetermined.

Well suited for real-time extraction of
information from one signal based
upon the frequencies contained in
another signal.
§ Use to remove movement noise
from ECG.
§ Unique configurations can be
established with two input signals,
one for frequency and one for
amplitude.

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Adaptive Filtering Calculation
Adaptive filtering is a signal processing technique that
processes two different signals in relation to one another
and can be used for noise estimation, noise reduction,
general-purpose filtering, and signal separation. Adaptive
filtering creates efficient high-quality filters with a
minimal number of terms, which can be very useful in
blocking mains interferences or other known periodic
disturbances.
§ Useful for noise filtering where it is possible to
acquire a signal that is correlated to the noise (similar
to the way noise-cancelling headphones detect and
remove outside noise). Applications include removing
EMG from ECG or EOG from EEG.
Ü See the Adaptive Filtering transform on
page 303.
To have AcqKnowledge apply an Adaptive Filtering Calculation in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the filtered data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Adaptive Filtering.
5. Click the Setup button in the Input Channels dialog to generate the Adaptive Filtering dialog.
The weights within an adaptive filter are modified on a step-by-step basis. AcqKnowledge uses the N-tap FIR
adaptive filter, with coefficients updated using least means squares (gradient) feedback.
Order
Specify a positive integer for the number of terms to be used in the internal FIR filter.
Step size
Provides mu, the rate of adaptation of the coefficients within the FIR filter.
Source channel
The source channel will be replaced by the adaptive filter results.
Noise channel
The noise channel is the signal that is correlated with the noise to be eliminated from
the Source; it is not modified by adaptive filtering.
Source and Noise channels must have the same channel sampling rate (under Channel Set Up).
Comb Band Stop Filter Calculation
To have AcqKnowledge apply a Control Calculation in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the filtered data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Comb Band Stop.
5. Click the Setup button in the Input Channels dialog to generate the Comb Band Stop dialog.
See page 146 for details.
(Off-line Comb Band Stop filter is available under Transform > Digital Filters > Comb Band Stop. See page
303.)
Metachannel
See Metchannel details on page 130.
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Rescale Calculation

Rescale applies two-point linear mapping and allows users to change the measurement units (for example, to
change temperature from Celsius to Fahrenheit). The text corresponding to the new units can be manually
entered.
To have AcqKnowledge apply a Rescale Calculation in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the filtered data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull-down menu and select Rescale.
5. Click the Setup button in the Input Channels dialog to generate the Rescale dialog.
(Off-line Rescale is available under Transform > Rescale.)
·
·

Use the Rescale transformation (after acquisition) to adjust forgotten calibration of analog channels or
reverse incorrect calibrations.
A "Rescale" Automator action has been added to allow rescaling to be performed in workflows. The
Automator function is accessed from the Workflow menu in the Mac version of AcqKnowledge. (Not
applicable to Windows.)

The rescale formula is:

Rescale Source
Old Units
New Units

Displays the label and number of the selected channel.
Displays the values of the current vertical units of the channel
Allows for manual entry of the new units to be used. The new units will be displayed in the
vertical units of the channel
Note Transform > Rescale: The units cannot be modified when transforming from the
selected area because it is not possible to display different vertical units for
different time ranges in the same channel.

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Slew Rate Limiter

Slew Rate Limiter is an effective tool for signal separating, denoising and removing motion artifact during and
after recording. The algorithm restricts the rate of change of a signal to a specific time window or sample width
window. The allowable amount of motion artifact over a given time/sample window can be precisely adjusted
from a minimum allowable change to a maximum allowable change, thereby eliminating artifacts that exceed
the selected amplitude range within a given time period.
The slew rate limiter algorithm restricts the rate of change of a signal to a specific window. If two different
types of signals with significantly differing rates of change are mixed together, limiting the allowable rate of
change of the mixed signal allows for signal separation by reducing the impact of a fast moving signal on a
slow one (and vice versa). The slew rate limiter formula is:
Assume a mixed signal y. Define a time window width w. Define the minimum allowable change in amplitude
K ≥ 0 where K max K min .
over the time window w as and a maximum allowable change in amplitude as max
The slew rate limiter function is then defined as:

where sgn is the standard mathematical sign function and is used to preserve the relative direction of the change
in the signal and random is a pseudorandom non-zero number used to avoid the singularity where sgn is zero,
enforcing that the rate of change will not drop below K min .
The slew rate limiter may be applied in real time as an online calculation channel, or in post-processing via the
Transform menu (see page 325). As with all online and offline transformations, signal type settings can be saved
as custom presets by clicking the “New…” button and naming the new preset.
To have AcqKnowledge apply the Slew Rate Limiter in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check an Acquire box for the Calculation channel to contain the filtered data. If necessary, also check
the Plot and Values boxes as appropriate for each channel.
4. Click the Preset pull down menu and select Slew Rate Limiter.
5. Click the Setup button in the Input Channels dialog to generate the Slew Rate Limiter setup dialog.
6. Set the desired time window to apply the slew rate limiter algorithm based on seconds or samples.
7. Set the minimum and maximum allowed change to adjust the sensitivity to motion artifact.
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8. Click OK and run the acquisition. Any artifact that falls outside the boundaries of the
maximum/minimum allowed change setting will be eliminated from the recorded data.
Watch the AcqKnowledge Slew Rate Limiter video tutorial for a detailed demonstration of this feature.

Filter - FIR
In AcqKnowledge 5, FIR Filters are available as an online calculation channel. Until recently, real-time FIR
filtering during acquisition wasn’t feasible due to processing power limitations, but these constraints are no
longer an issue for modern dual-core and quad-core processors.
Online FIR filters are similar to their offline transformation menu counterparts with the exception of the
following convention.
Delay at current settings: For FIR filtering in general, a delay is imposed on the output signal, and this
parameter shows the number of delay samples the current settings will introduce. If the number of coefficients
is fixed, the delay value will equal the number in the “Fixed” editable field. If the number of coefficients is set
to be optimized for sample rate and cutoff, the delay value will vary. The filter algorithm compensates for this
delay in order to assure proper alignment of filter output with the acquired signal.
When modifying the fixed number of coefficients or the frequency, the delay value is updated accordingly.
However, it should be noted that a close comparison between online and offline FIR filters will reveal that they
are not perfectly in phase, but out of phase by half of the imposed FIR calculation channel delay.
As in other AcqKnowledge calculation channel presets, any modified Filter – FIR setup can be saved as a
custom preset by selecting “New Preset.”
To have AcqKnowledge apply the Filter – FIR in real time:
1. Choose Hardware > Set Up Data Acquisition > Channels.
2. Click the Calculation tab.
3. Check the Acquire, Plot, and Values box for the Calculation channel to contain the filtered data.
4. Click the Preset pull down menu and select Filter – FIR.
5. Click the Setup button to generate the Filter – FIR settings dialog.
6. After starting acquisition, real time FIR filtering will appear in a dedicated calculation channel for the
duration of the recording.
For specific details on the various FIR filter types, windowing, and recommended settings, see the offline Filter
– FIR Transform option on page 300.

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Chapter 7

Data Acquisition

Data Acquisition—The Basics
Once the channels to be acquired have been selected (see Chapter 5 Channel Setup on page 112), the next
step is to set up the acquisition parameters. These options control the data collection rate, where data will be
stored during an acquisition, and the duration of each acquisition. Choose Hardware > Set Up Data Acquisition
> Length/Rate to generate the following options.
Storage Mode
At the top of the dialog are three popup menus that controls a number of aspects for storing the data from each
acquisition.
Record/Record last controls whether the software saves all the data or only the most recent segment of the
data.
§ Record—the hardware will store data for the amount of time specified in the acquisition length box. This
is the default and is appropriate for almost all types of acquisitions.
§ Record last—only available when acquisitions are set to “Save Once” using “Memory”—the hardware
will acquire data continuously, but will only store the most recent segment of data equivalent to the
duration in the acquisition length dialog. That is, if the value in the acquisition length box is 30 seconds
and record last is selected, the hardware will acquire data ad infinitum, but will only store the most recent
30 seconds of the data.
Save once/Autosave file/Append sets how the data is saved to a file. Append mode is the default setting..
§ Save once—AcqKnowledge will begin an acquisition after clicking the Start button, and will stop
recording automatically when the acquisition length has been reached or when the Stop button is clicked.
§ Autosave file — this mode performs several acquisitions one after another, and saves the data from each
acquisition to a separate file. When Autosave is selected, a File button will appear to the left of the
sample rate dialog. Click “File” to generate a standard Save dialog to enter the root file name for the data
from each acquisition. After clicking “Save,” another dialog is generated with options to append an
incrementing number, time (system clock), or date (system clock) to the filename: Media functionality
does not support the Autosave file acquisition mode.
§ Append —similar to ‘Save Once’, except that Append allows acquisitions to be started and stopped at
arbitrary intervals. Append mode is unique in that clicking on the Stop button only pauses the acquisition,
which can then be restarted by clicking the Start button.

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Each time an acquisition is restarted in
Append mode, an append event is inserted
into the recording. Append events can be
configured to include user-defined labels and
time/date stamps via the Segment Labels
setup (see page 250). Although acquisitions
can paused for any period of time, the
Hardware will only acquire data for the
amount of time indicated in the Acquisition
Length box. Data can be acquired in Append
mode while being saved to memory, disk, or
the MP hardware unit (but not in Averaging
mode).

Sample data Acquired in “Append” mode.
Events indicate where Acquisition was paused.

Appended segments can be stored to disk, memory, or MP160/150. (MP36R, BioHarness, Mobita, or BAlert do not support data storage to the hardware unit.)
Ø Append to Disk: In this mode, it is usually best to record all channels at the same rate. If the user
stops the acquisition, the length will be the same for all channels—so the next segment of appended
data will neatly link onto the end of the existing record.
§ Any existing AcqKnowledge 5 file can be appended. Change the acquisition mode to Append;
any of the storage options are applicable
Ø Append to Memory: In this mode, data is appended to the “uneven” waves in the same manner as
described for Append to Disk. When channels are sampled at different rates, this mode will respond
faster than Append to Disk because the data files are already in memory, so the software doesn’t need
to rewrite all the data files in the graph.
A Reset button is generated in the Set Up Acquisition dialog when Append is selected. Click
the Reset button to erase the acquired data file and start a fresh acquisition file (this is
essentially the same as clicking OK to an “Overwrite existing data?” prompt).
The Rewind button to the right of the Start/Stop button will delete the last recorded segment.
Ctrl-Rewind (Windows) or Option-Rewind (Mac OS) will delete all recorded segments (similar
to the Reset button).
Append plus external trigger
Appended segments can be started with an external or internal trigger. The experiment can be
tailored to start at points of interest by applying a trigger. See Triggering details on page 180.
Append plus Variable Sampling Rates
If the mode is started and stopped manually, it is statistically possible that, prior to the next pass
of the Append, extra data points may be inserted in various data channels to “line up” the data
(see sample on page 116). These extra data points simply replicate the last sample in any
affected channel. To minimize the impact of the extra data points, make sure the lowest
sampling rate is on the order of 10 Hz or higher, or don’t use VSR.
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Disk/Memory/MP/Averaging determines where to store data during an acquisition. Once data has been
acquired and is stored in a file, it is stored on a hard disk or other similar device. There are a number of options
for storing data during an acquisition. The best choice as to where data should be stored during an acquisition
depends in large part on the nature of the acquisition itself, and the type of computer being used.
§ Memory stores data in computer memory during an acquisition. After the acquisition is completed, it will
be necessary to select Save As... from the File menu to permanently save this to the computer’s hard disk.
This usually allows for faster acquisition rates, although most computers have less available RAM than disk
space.
§ Disk saves data directly to the computer’s hard disk during an acquisition. Disk mode is fast enough (in
terms of maximum sampling rate) for many applications, especially when only a few channels are being
acquired. Saving data to Disk also allows for longer acquisitions. A final advantage of saving data directly
to Disk is that if there is a system failure (including power outage), all the data collected up to that point is
saved on disk and can normally be recovered, whereas the data is deleted if it is being saved to computer
memory.
IMPORTANT—When saving files to Disk, always be sure to save files under a different name
BEFORE starting each acquisition. Otherwise, any previous data in that file will be overwritten.
In Memory mode, simply save the file after the acquisition.
§ MP160 and MP150 stores a small amount of data on the hardware itself. The MP160/150 is limited only by
internal memory, with storage estimated at 4 MB and 400 kHz aggregate sampling rate.
Obviously, data cannot be sampled this fast for a very long period of time if it is to be stored in the
hardware. Also, as more and more channels are acquired, the duration of acquisition to the hardware unit
will shorten. Data stored to the hardware is not plotted on the screen as it is being acquired, but will
automatically be plotted on the screen as soon as the acquisition is terminated.
§ Averaging is used exclusively for acquisitions involving repeated trials; see page 169.
Acquisition Sample Rate
The value in the box labeled “Sample rate” indicates how many samples the hardware should take per channel
during each second of data acquisition. The sample rate can be changed by clicking on the pull-down menu.
Individual channels can be down-sampled (variable sample rates), on the channel pane of the Data Acquisition
Settings dialog. The down-sampled or channel sample rates are limited to specific power of 2 less than the
acquisition sample rate; for example, If the acquisition sample rate is 100 samples/seconds, then the available
channel samples rate are 100, 50, 25, 12.5, etc.
Depending on the nature of the data being acquired, the “best” choice in terms of sampling rate will vary.
Technically speaking, the minimum sampling rate should be at least twice the highest frequency component of
interest. This means that if the observed phenomenon has frequency components of 100 Hz, the sample rate
should be at least 200 times per second. Fourier analysis (FFT) can be used to determine what frequency
components are present in the data (see page 333 for a more detailed description of the FFT function).
X

TIP: A good rule of thumb is to set the sampling rate to at least three to four times the highest
frequency component of interest.
In less technical terms, lower sampling rates can be used for data with slowly changing values (e.g. respiration,
EDA, GSR), whereas higher sampling rates should be set for data where values change markedly in magnitude
or direction (e.g. ECG, EEG, evoked response).
The maximum allowable sampling rate will automatically adjust itself according to the storage mode, how
many channels are being acquired in the channel setup window and the type of computer being used.
If data is being stored to disk or computer memory (RAM) during an acquisition set to a sample rate that is too
high, the acquisition will begin normally, but AcqKnowledge will stop the acquisition and display a message
indicating that the acquisition buffer has overflowed. The data up to this point has been saved, and acquisition
or channel settings should be adjusted; lower sampling rate; shorter length or fewer channels
The sample ECG waveforms below illustrate the effect of different sampling rates on quality of data. Each
black dot corresponds to a sample point.
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§
§

Top waveform: data is sampled relatively slowly; difficult to make out the shape of the waveform.
Bottom waveform: sampled at a relatively high rate; increased resolution of the waveform. Waveform
components that were obscured at slow sampling rates are now well defined, and measurements taken on
this waveform would be able to better establish the maximum amplitude, time between different ECG
complexes, etc.
Representation of ECG waveform sampled
with relatively few samples per second
“True” ECG wave is superimposed over dots
that indicate sample points.

Representation of same ECG waveform
sampled at a relatively higher sampling rate.

As shown, under-sampling completely misses the QRS complex of this waveform, although it might detect
components of the QRS in subsequent beats. Although this is an extreme example of how under-sampling can
affect digitally processed data, it is important to note that the rate at which data is sampled has important
implications for the interpretation and analysis of data.
Acquisition length
To set the duration of an acquisition, enter a number in the acquisition length box. By default, 8 hours of data
will be recorded for MP and Smart Center hardware. Select the length units from the popup menu to the right of
the length box. The units are milliseconds, seconds, minutes, hours, or samples. Changing this option will not
change the length of the acquisition, only the units used to describe it. Thus, the same acquisition can be
described as lasting 30 seconds, or 0.5 minutes, or 30,000 milliseconds. Scaling the duration of an acquisition in
terms of samples is essentially the same as the time scaling options, except the length of the acquisition will be
expressed in the total number of samples to be collected on one channel.
Regardless of units used to determine the length of acquisition, AcqKnowledge will end an acquisition when the
value in the total length box is reached. The acquisition can be halted at any time by clicking the “Stop” button.
Multiple Hardware
AcqKnowledge can be used with multiple data acquisition units to:
§ Control multiple, independent experiments on one computer.
§ Increase the total number of channels used for a single experiment (e.g., 32-channel EEG)
§ To synchronize the Start of multiple units, use the External Trigger function.
§ To combine nearly unlimited channels of data into one file, use the Merge Graphs feature (see page
290).
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Each graph window can
support a different Hardware
unit. To open a graph for a
separate hardware unit, select
File > New > Graph.

To show/hide the “Connect to:” information, go to Display > Show > and toggle the “Hardware” option, or
select this item from the “Show/Hide” popup menu
To switch the hardware unit
associated with a graph
window, click the “Connect
to” box and select an available
unit or choose Add New
Device. Different hardware
types may be added and
consolidated in the list by
selecting ‘Add New Device.’
The “Choose MP160” or
“Choose MP150” dialog
shows the MP160/150 units
residing on a local network.
(Network functionality is
limited to MP160/150
hardware only.)
Click the Help… button to
open a troubleshooting guide
for communication problems.

.

NOTE: When switching to a BioHarness BT device from another hardware
type, a new graph must be launched in order for the BioHarness settings to
take effect. (File > New > Graph Window)

Averaging (MP160 and MP150 Hardware only)
Overview
In some instances, the signal of interest does not stand out against the background or ambient noise (the level of
ambient noise exceeds the signal produced by the object of interest), and the only way to detect the signal of
interest is to perform repeated trials as part of one acquisition, and average the trials together. Since the “noise”
associated with the signal is assumed to be random, and the “signal” is assumed to be systematic, the noise
should approach zero as the individual trials are averaged together.
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Signal (top) measured in the presence of noise
(middle), which results in the bottom waveform
when measured in standard Acquisition mode

Same signal averaged in the presence of noise
over 2,000 trials to produce the lower waveform.

Typically, any averaging acquisition consists of three general components:
(a) the stimulus signal
(b) the duration of the acquired data, and
(c) a small amount of processing time (or overhead) that takes place between acquisitions.
The duration of the stimulus signal and the duration of data to be acquired can be set by the user. The amount of
overhead required is a function of the acquisition length, the sampling rate, and the number of channels being
averaged.
Acquisition length

Overhead

Stimulus signal

Latency

Stimulus signal
Acquisition length
Overhead
Latency

usually some sort of pure tone or pulse; occurs at the beginning or during
each trial.
refers to the amount of data to be acquired during each trial.
refers to a period of time after data has been acquired that is needed to
perform the mathematical averaging.
refers to the total time elapsed between the start of one trial and the start of
the subsequent trial.

Important usage notes
§ The maximum length of a single averaging pass is restricted to 2 seconds; if longer averaging passes
are required, use regular data acquisition and use the Ensemble Average offline analysis option to
generate averages in post-processing.
§ The preferred hardware setup for on-line averaging mode is direct connection to the
MP160/MP150 via cross-over cable. To improve stability, avoid interruptions during acquisition:
· Do not access top-level menus (File, Edit, Transform, etc.) or generate popup dialogs (Setup…).
· Avoid running other programs—helps ensure that required system resources (processor time,
memory, and network throughput) remain available.
· If the MP160/150 is connected over a network, avoid running applications that consume network traffic
(Internet Explorer, mail client, media player)—these may interrupt/delay communication to the
MP160/150.

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Averaging Setup
For Advanced Averaging, see page 172
To set up Averaging:
1. Choose MP160/150 > Set Up Data
Acquisition > Length/Rate and select
“using Averaging” option.
2. Click the Setup button to generate
the Averaging options dialog.
3. Set the Averaging options as detailed
below.
4. Click OK to close out of the dialog.
5. Set the Stimulus (see page 183).
6. Use the buttons in the graph window
to Start or Stop the averaging
acquisition.
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Online averaging progress bar

An online status bar is added to graph
windows when online averaging acquisitions
are in progress. The status bar displays the
number of averaging passes that have been
completed and the number of passes that
have been rejected by the MP160/150
firmware.
Averaging Options
Averages
Select the number of trials to perform from the pull-down menu, to a maximum of 10,000.
Latency
Latency is the total time from the start of one trial/average to the next; it includes the time for stimulus signal,
acquisition and overhead. As general rule, set latency to three times acquisition length plus any experimental
delays, for example allowing the subject's signal to return to the baseline. The default setting for latency is 100
msec.
If the latency is set to a value too short to allow for averaging to take place, an Acquisition Warning will be
generated:
§

§
§

Adj Latency: automatically adjust the latency
to the shortest possible value that still allows
for data to be acquired and processed.
Adj Length: reduce the amount of data
acquired without changing the latency.
Abort: return to the graph window without any
data being collected.

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External trigger
To initiate a trial from an External Trigger signal enable the Ext Trigger in the Averaging options dialog as well
as the Positive or Negative Edge. The trigger can be set up in the Trigger pane of the Data Acquisition Setting
dialog. See page 180.
Artifact rejection
Occasionally during an acquisition, extreme levels of unwanted signal artifact may be present. Checking artifact
rejection allows the determination of which signal levels constitute artifact, and has the MP System reject these
trials. When artifact rejection is enabled, the MP System will ignore any trials that contain signals exceeding the
artifact rejection thresholds, keep track of how many trials have been rejected, and add that number of trials to
the total number of trials to be acquired. This allows a user to “re-try” a trial that was rejected due to the
presence of artifact.
To set these parameters, it’s necessary to set a high threshold and a low threshold. Both thresholds refer to the
scale limits (normally ±10 Volts). If the high and low artifact rejection thresholds are set to 80% and 30%
(respectively), the MP System will reject any trial where the signal exceeds +8 Volts or –3 Volts.
When the channel scaling feature is used to change the range of Map (Scale) values to something other than ±10
Volts, the artifact rejection formula for symmetrical limits is: y = ((2·PV)/100)·x – PV
where
y = voltage threshold
PV = Peak Value
x = percent threshold (whole number)
If non-symmetrical limits are used, the following equation is used: y = ((V1-V2)/100)·x + V2
where
y = voltage threshold
V1 = Higher Peak Value
V2 = Lower Peak Value
x = percent threshold (whole number)
Enable Channels
X180

To add analog channels to the average, check
additional channels in the Enable list.
§ Channels must be set to “Acquire” under
Hardware > Set Up Data Acquisition >
Channels to be selectable here; otherwise the
channel box will be grayed out.

Stimulus Signal

Although AcqKnowledge does not require a stimulus signal to be output for Averaging trials, most applications
that use signal averaging make use of a stimulus signal. Digital stimuli (i.e., clicks) or analog stimuli (i.e., tones,
pulses, and arbitrary waveforms) may be output.
In almost all cases, the most convenient way to output a stimulus signal is to output a predefined wave on
analog output channel A0 and/or A1. It’s possible to create pulse waveforms, tone waveforms, ramp
waveforms, and arbitrarily shaped analog waveforms. Use MP160/150 menu > Set Up Data Acquisition >
Stimulator to set all of the stimulus output functions (see page 183).
After Averaging is started, the Start button turns to Averaging status and the green dot turns to “A” to indicate
that Averaging is in process.
Advanced Averaging—P300
Advanced averaging can be used to set up P300 protocols. A sample P300 setup, P300.avg, is included in the
Samples folder.
To set up Advanced Averaging:
1. Open two or more graph files.
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2. Use Set Up Data Acquisition > Length/Rate to set each graph file for Averaging (see page 169).
3. Click the Averaging Setup button and set Averaging Options as desired for each graph file.
§ Advanced Averaging uses the last entered settings for each Averaging graph. The number of
Averages is controlled by the Advanced Averaging Settings, not the settings for a single
Averaging graph.
4. Use Setup Stimulator to establish the desired stimulus output for each graph file (see page 183).
§ Set the Stimulator Output channel to the same channel (A1 or A0) for all graph files.
§ Set the Stimulator Output to During Averaging Pass (recommended).
5. Save each graph file with an appropriate name.
6. Choose MP160/150 > Set Up Advanced Averaging.
X

X

X

X

This menu option is only enabled if two or more open
graphs are set to Averaging.
7. Set the Advanced Averaging options:
a. Averages: Select the number of averages from the
pull-down menu (max 10,000).
b. Graph: Assign a Graph from the pull-down menu of
open graph files. Up to eight graph files can be used in
Advanced Averaging.
c. Trial distribution: Use the slider or type a value into
the text box.

8. Click the Start button in the Advanced Averaging setup dialog to begin acquisition. Status information
for each graph is displayed in the lower left corner of the graph.

9. Save the graph.

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Repeating
Use the Repeat mode to acquire data from repeated trials using the same parameters for each trial. Checking the
Repeat every box at the bottom of the acquisition setup dialog enables two additional popup menus at the
bottom of the dialog. These allow for control of how many times an acquisition will repeat as well as the
interval between trials. When this is unchecked, the acquisitions will repeat as soon as possible (usually
instantaneously, but slightly longer if data must be saved to a file between trials).

Interval

The entry to the right of the “Repeat every” checkbox tells AcqKnowledge how long to pause
between the start of one acquisition and the beginning of the next acquisition. This can be scaled in
terms of seconds, minutes, or hours using the first popup menu.
It is important to note that this value measures the interval between the start of two adjacent trials,
rather than the interval between the end of one trial and the start of the subsequent trial. If the repeat
interval is set for 15 minutes and the acquisition length is set to 60 seconds, then there will be a 14minute pause between the end of the one trial and the beginning of the next.
Trials
Set how many trials to acquire:
for
perform a finite number of trials; enter the number of trials to acquire in the “times” field.
forever perform an infinite number of trials. Trials will be repeated at the specified interval until
the acquisition is stopped either by clicking on the stop button in the graph window or if
there is not enough free memory on the target storage device.
Regardless of which options are checked, data for each trial is acquired according to the acquisition parameters
specified in the dialog. In the above example, each trial of data will be sampled at 50 Hz and will last 1 minute;
the trials will be repeated every 15 minutes for a total of 8 trials.
Selecting the option to Record and Save Once to Disk/Memory will overwrite the previous collected data.
However a warning will appear unless the “Warn on Overwrite” option is disabled. Another option is to select
Autosave file from the Save once/Autosave file/Append option. When the repeating option is checked and
Autosave is selected, AcqKnowledge will save the data from each trial using the file name and extension
indicated by the autosave feature. See page 165 for a more detailed description of Autosave.
Setup Channel Options
Channel

The Channel column contains the alpha-numeric channel numbers. “Analog” (or
continuous) input channels begin with “CH” and run from CH1-CH4 for MP36R and
A1-A16 for MP160/150. “Digital” input channels begin with “D” and run from D1-D8.
“Calculation” channels begin with “C” and run from C0-C15.
Use the scroll button

to set up additional Digital or Calculation channels.

Acquire

When the Acquire Data box is checked for a given channel, data will be collected on
that channel.

Plot

If Plot on Screen is also checked, data will be plotted on screen in real-time during the
acquisition. If the plot box is unchecked, data will still be recorded for that channel, but
the waveform display will be disabled. To display the waveform plot during or after
acquisition, show the channel. (Alt+click the channel box above the graph.)

Value

Checking the Value box allows for the display (numerically and/or graphically) of the
values for each channel in real time. To display the values, Show Input Values must be
selected via the Hardware menu. Input values are displayed in a separate bar graph

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Setup Channel Options
window.
Default

TIP

For MP36R, the default is to collect one channel of data on analog channel 1 (CH1), and
to plot and enable value display for this channel. For MP160/150, a channel must be
enabled by choosing “acquire” prior to recording, if “View by Channels” mode is used.
Normally, all three boxes should be checked for each data channel.

Label

The Label entry for each channel supports up to 49 characters to identify the channel.

Presets

Clicking on the Presets button will generate a menu of available presets for the channel.
Presets for common applications configure the hardware gain, filters, etc.
Ø For a detailed summary of Analog Input channel, Digital Input channel, and
Calculation channel options see the Presets section beginning on page 129.
X

Setup

X

To Change Parameters for a Preset, click the Setup… button. Changing parameters
presents the option of creating a New Channel Preset which makes the established
parameters available to other channels.

If a preset is changed a recording started in Append mode, the following prompt will appear. Choose Abort,
save the data, and then change the presets to acquire as a new data file.

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Starting an acquisition
After setting up the channels and defining the acquisition parameters, the next step is to start the acquisition. If a
file window is not already open, choose File > New to generate a graph window.
In the lower corner of the screen, next to the
button, there should be a button with a circle to the left
of it. The circle indicates the communication status between computer and hardware. If the unit is properly
connected to the computer and is turned on, the circle should be solid and green. If the unit is not properly
connected, a solid gray circle will appear.
Start the acquisition by clicking the
button or by selecting “Ctrl + Spacebar.” If there are no input
devices (e.g., electrodes or transducers) connected to the hardware, the system will collect a small value of
random signal “noise” with a mean of about 0.0 Volts.
Ø For information on how to connect measurement devices to the MP36R, see the BSL Hardware Guide.
Ø Acquisitions can also be started using a variety of “triggers,” which are discussed on page 180.
Once acquisition starts, the
button in the acquisition window changes to
. The two
opposing arrows to the right of the button indicate that data is being collected. The “Busy” status indicator light
on the front of the MP160/MP150/MP36R will then illuminate, indicating data is being collected.
Stopping an Acquisition
To stop an acquisition at any time, click the
button in the lower right corner of the screen or select
“Ctrl + Spacebar.” An acquisition will stop automatically when it has recorded an amount of data equal to the
Acquisition Length entry.
Rewind
The Rewind button to the right of the Start/Stop button allows the last recorded data segment to be erased
and subsequent appended data to be added to the existing data file. This function will erase the last segment
along with the Append Event for that segment; the application will keep track of Append Event labels, so
that the label always matches the segment number.

If the “Warn on Overwrite” option is active, a warning dialog will be generated before the segment is deleted.
Saving acquisition data
To save a data file, pull-down the File menu and choose the Save command.

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Timers (Stop watches and Elapsed timers)
The Timers function allows for easy visualization and measurement of elapsed time within the AcqKnowledge
user interface, and consists of a simple toolbar display. Timers can be helpful when actions need to be
performed at specific intervals prior to and during an experiment. The Timers function provides an easy-to-read
digital display in the toolbar region, and supports the creation of multiple timers, which can be added or
removed as needed.
Timer Types
There are two main types of timers, acquisition controlled (“elapsed” timers”) and independent timers (“stop
watches”). Manual “stop watch” timers can be used at any point for tracking time independently of acquisition,
while elapsed timers are tied to a recording in progress and unavailable unless an acquisition is running.
Independent Timers (Stop watches)
Independent timers are manually started and stopped, and have a countdown feature with an audible alarm and
flasher. Multiple timers can be added to the toolbar region, and can be started and stopped independently. Pause
mode is not supported. Although the timer can be stopped at any time, restarting it resets the timer back to
0:00:00.
Elapsed Timers (Acquisition controlled)
Elapsed timers start when the acquisition “Start” button is clicked and continue counting for the set duration of
the recording, or until the acquisition “Stop” button is clicked. When acquiring in Append mode, the elapsed
timer is reset at the beginning of each new segment. Any trigger or delay time applied between segments is not
included in the elapsed time. Multiple elapsed timers can be added to the toolbar region. This mode does not
support the countdown or alarm feature.
To set up a timer:
1. Display > Show > Timers or click the Show/Hide toolbar button
2. The timer toolbar will appear as shown below:

and choose “Timers,”

3. The elapsed timer option is enabled by default. If only a single elapsed timer (acquisition
controlled) is desired, simply start the acquisition and the timer will start automatically.
4. If an independent timer (stop watch) is desired, right click on the numbers portion of the timer
toolbar and choose “Settings.” In the Timer Settings, choose “Independent start” and click OK.
To start/stop independent timers: Click on the toolbar number display to toggle start/stop, or right click on
the toolbar number display and choose “Start timer” or “Stop timer” (see figure below).
To set up multiple timers:
Click the Timers toolbar icon and choose the desired timer type. Repeated clicking on a timer
option will create additional timers of that type, which will appear in the timer toolbar region.

To set an alarm:
1. Click the Timers toolbar icon and choose “Create alarm.”
2. Right click on the numbers display portion of the new alarm
and choose “Settings.”
3. Set the desired time in the “Countdown timer” field.
4. Check “Sound alarm” and “Blink upon alarm.”
NOTE: These settings will remain the default for subsequent alarms until the settings are changed.
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Overview of Timer Settings

CONTROL

DESCRIPTION
Field for assigning name to timer.

Timer name:
Start timer with acquisition:
Independent start
Countdown timer
Sound alarm
Blink upon alarm
Display > Font family: > Font size >
change color
Include fractional seconds

Timer will start and stop with data recording only.
Timer is started and stopped manually, independent of acquisition
status.
Sets the countdown time duration.
Selects the audible alarm option and specifies the number of times
the alarm will sound.
Enables the timer numbers to flash on and off when the countdown
is complete.
Selects timer font style, size and color.
Sets option to display 1/100ths of a second in timer display.

All parameters established in the Timer Settings are retained in saved graphs and graph templates.

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Electrode Checker

The Electrode Checker, in conjunction with the MP36R unit, measures how well electrodes are making
contact with the surface of the skin. To use this feature:
1) Attach the electrodes to subject.
2) Connect the electrodes to an electrode lead set (such as the SS2LB).
3) Instead of connecting the electrodes to one of the four analog inputs, connect the Simple Sensor end
of the electrode lead to the Electrode Check port on the front of the MP36R acquisition unit.
4) Click the MP36 menu and scroll down to select Electrode Checker.
This will generate a small “thermometer-like” display. At the bottom of the display, a number with a kW
(Kohms) symbol should be visible. This value describes the impedance of the electrode/skin contact, with lower
numbers being associated with better conductivity. The better the conductivity, the “cleaner” the signal
displayed on the screen. If the MP36R is off or no nothing is connected to the “Electrode Checker” on the
MP36R unit, the Electrode Checker display will say “OFF.”

Poor contact

Good contact

Off

TIP While there are few absolutes as to what constitutes “good” contact, one rule of thumb is that this
number should be below 10 kW, and the lower the better.
TIP To decrease the impedance of an electrode connection, it’s recommended to “abrade” the surface of
the skin with an abrasive pad (such as ELPAD). This removes a thin layer of dead skin cells and
should result in a signal that has relatively little noise. EXCEPTION: Do not abrade the skin if
collecting EDA (Electrodermal Activity) data.

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Chapter 8

Set Up Triggering

During a normal acquisition, the MP hardware will begin collecting data as soon as the Start button is clicked. It
is also possible to begin an acquisition in a delayed fashion using a trigger. This feature enables an acquisition
to start “on cue” from a variety of different trigger sources. All trigger options are configured in the Triggering
dialog, which is accessed via MP menu > Set Up Data Acquisition > Trigger. By default, the trigger is Off.
Other options can be selected from the popup menu in the Trigger Setup dialog. To begin an acquisition with a
trigger, first choose the trigger options most appropriate for the experiment and click the AcqKnowledge graph
Start button. After the Start button has been clicked, data will be acquired as soon as the trigger is activated.
There are two general types of trigger sources: digital channels and analog channels.
Digital Triggers (MP160 and MP150)
Digital channels are channels that contain binary
(either/or) data as typified by a switch being either open
or closed. This type of data can be acquired from a pushbutton switch or other device that produces an on/off
pulse. For example, it is sometimes useful to set up an
acquisition to start when a subject presses a button or
when a signal generator sends a pulse. These are typical
digital signals and the external trigger devices that emit
them must be connected to a BIOPAC STP100C Isolated
Digital Interface (shown interfaced with the MP160
System on right*).
In a simple trigger design, the external switch is
connected to the STP100C BNC “TRIG” input. Since the
switch will be either open or closed, the resulting digital
data will consist of two levels, +5 Volts and 0 Volts. A
value of +5 Volts is interpreted as a binary 1, and a level
of 0 Volts is interpreted as a binary 0.
When the switch is closed (i.e., the button is pressed), the
signal changes from +5 Volts to 0 Volts, creating a
transition or “edge.”
External trigger example:
1. Connect the external BNC trigger to the STP100C “TRIG” input.
2. In AcqKnowledge, choose MP160 menu > Set Up
Data Acquisition > Trigger.
3. Set the Trigger parameters to “External” and “Pos
Edge.” Close the dialog.
4. Click “Start” in the AcqKnowledge graph. Note that
the acquisition does not start. The “Start” button will
toggle to “Stop” with a trigger status icon indicating
that a trigger is pending. A trigger notification will also appear in the graph window.

5. Push the button on the external trigger connected to the STP100C module. The acquisition will then start.
*The earlier-version MP150 System uses the “TRIG” and “GND D” inputs on the back of the UIM100C
(Universal Interface Module) for external trigger connection.
For MP36R hardware: The external trigger is connected to the “Trigger” input on the back of the unit. The
software setup is the same as that shown above.

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MP36R note: Due to processor limitations at sampling rates of 25 kHz and higher there may be an occasional
delay of up to 40 milliseconds between detection of an External Trigger and the start of data acquisition.
Use either an analog or digital channel as a trigger when acquiring data at 25 kHz, 50 kHz or 100 kHz, if
accurate timing of the start of acquisition is required.
Analog Triggers
Initiate an acquisition when an analog channel reaches a certain voltage level. To enable the analog trigger
feature, data must be acquired to either memory or disk, and a value must be entered in the Delay box (although
the delay may be set to zero). The channel containing the data to be used as a trigger requires that the
acquire/plot/values boxes be checked in the Set Up Data Acquisition > Analog Channels dialog. Leaving these
boxes unchecked will allow the incoming data to trigger an acquisition but will not allow the trigger channel to
be acquired or plotted.
Select Hardware > Set Up Data Acquisition > Trigger to generate the Trigger dialog:

MP160/150 Triggering options

MP36R Triggering options

Level
Edge

External: Select for Digital Trigger.
CH #: Select for Analog Trigger; must be acquiring to Memory or Disk. Specify the analog
channel that contains the trigger data and then specify a voltage Level to initiate the trigger.
Acquisition will begin when the data on the specified channel reaches the specified Level.
§ To trigger an acquisition when an ECG wave on analog channel 1 reaches a certain voltage
or value, set “Source” to CH 1 and then set the Level when the entry box is enabled.
§ Triggering from an analog channel requires oversampling by a factor of 4, which ensures
that the trigger signal will not be missed. The sampling rate can be adjusted in the Set Up
Data Acquisition > Length/Rate dialog.
o For example, an initial sampling rate of 1,000 samples/second should be increased to
4,000.
The Level option is activated when a Source CH is selected. Set a level to initiate the trigger (e.g.,
if the ECG wave peaks at 2 mV, set the trigger level just under 2 mV).
Triggers can have a positive or negative edge, defined as follows:
Edge

Digital

Analog

Pos

Signal changes from 0 to 1

Signal changes direction from downward
to upward. Once the trigger level is
crossed, the acquisition will start.

Neg

Signal changes from 1 to 0

Signal changes direction from upward to
downward. Once the trigger level is
crossed, the acquisition will start.

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§

Mode

Delay

Pretrigger

For ECG data (and other types of data with peaks of relatively short duration) there will be
only minor time differences between one edge and the next, although the positive and
negative edges can be widely separated in time for data with slowly changing values (such
as EDA or skin temperature data).
Once the trigger channel and level have been specified, the final parameter is the delay. Delay can
be measured in terms of samples, milliseconds, seconds, or minutes, and may be set to zero if
desired. The delay option instructs the hardware to wait a specified period after the trigger level is
reached before beginning the acquisition.
When using a trigger, the default setting is for the acquisition to begin immediately after the
trigger pulse or level occurs. This default can be modified by using the Delay option in the Trigger
Setup dialog. This feature allows an acquisition to begin a specified period after the trigger level is
reached. To start an acquisition one second after a switch closes, set the trigger to external and
enter 1.00 in the box next to Delay. The default scale for Delay is seconds, meaning that the
acquisition will begin a specified number of seconds after the trigger has been initiated. The scale
of the delay can be changed from seconds to samples, milliseconds, or minutes.
NOTE: Delay option not available in MP36R hardware.
During normal triggered acquisitions, data is collected only after the trigger has been activated (or
after some delay). For some applications, it is useful to collect data on events that occur just prior
to the trigger event. As an example, if an acquisition was set to begin when a device (such as a
tone generator or flash) sends an output pulse, it might also be important to collect information on
the subject’s state just before the stimulus.
Pretrigger functionality is not supported in all acquisition modes (MP160/150 > Set Up Data
Acquisition > Length/Rate): NOTE: Pretrigger option is not available in MP36R hardware.
Mode

Source: EXTERNAL

Source: CH #

Disk

Pretrigger supported

Pretrigger supported

Memory

Pretrigger supported

Pretrigger supported

MP160/150

Pretrigger supported

not available

Averaging

not available

not available

When the Pretrigger function is enabled, start an acquisition by clicking the Start button. When the
internal memory in the data acquisition hardware is full, the hardware will start replacing the
oldest data with the newest data (similar to the record last feature). This process continues until the
trigger event occurs. Following the trigger, the hardware will collect data until the total length is
reached. The acquisition now contains data from both before and after the trigger.
The amount of data collected before the trigger event is determined by the value in the box next to
the Pretrigger popup menu. As with Delay, scaling can be set in terms of samples, milliseconds,
seconds, or minutes. The duration of the Pretrigger may also be adjusted using the scroll box to the
right of the Pretrigger dialog.
When Pretrigger is selected, it is important to note…
§
The total length of the acquisition includes the duration of the Pretrigger. If the acquisition
length is set to 120 seconds and the Pretrigger is set to 20 seconds, only 100 seconds of data
will be collected after the trigger event occurs.
§
Since the total length of the acquisition includes the duration of the Pretrigger, the duration of
the Pretrigger may not exceed the length of the acquisition.
Hysteresis window (MP160 hardware only)
This feature helps compensate for potentially noisy input signals that may occur when Analog channels are
used as the triggering source. The window field is editable, allowing a user-defined hysteresis threshold to
be entered. The window units will match the units reflected in the Analog triggering source channel.
Hysteresis does not apply to Digital triggering. This option will not be available in the Trigger setup window
if External is selected.

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Chapter 9

Set Up Stimulator

Note This chapter refers to stimulator setup for MP160 and MP150 hardware only. For

MP36R, see the next chapter, ‘Output Control.’

Although data acquisition is the primary function of the MP System, AcqKnowledge supports output of a signal
through one or two analog channels while data is being acquired. This type of signal output is configured in the
Stimulator setup window.
Four types of signals can be output:
Square waveforms—page 189
Ramp waveforms—190
Tone waveforms—190
Arbitrary waveforms—191
Each of these waveform types can be set to repeat signal output either Once or Continuously, and parameters
can be set to either Relative or Absolute time scales. To set the type of waveform to be output, select
MP160/150 > Set Up Data Acquisition > Stimulator. Like the standard graph window, the Stimulator setup
window plots time on the horizontal axis and amplitude on the vertical axis.
Use the Stimulator window to create and shape waveforms for output. Adjust the Stimulator Sample Rate
(described below) to further control the parameters of the Stimulator Output design.
For any waveform (or stimulus) to be output, the following parameters must be specified; the type of stimulus,
the “shape” of the signal, the output channel to be used, and how many times the stimulus should be output.
All the above parameters are set up from within the Stimulator Setup dialog. Regardless of the type of
waveform selected, stimulus signals will normally be output when an acquisition is initiated, either as a result of
clicking the “Start” button, using the “manual stimulator control” or via a trigger being activated.
Stimulator Sample Rate
A powerful feature intrinsic to the MP160 or MP150 unit is the ability to set a stimulation signal output rate that
varies from the acquisition rate, thus permitting considerable flexibility for a variety of physiological
applications. For a full explanation of MP160/150 Stimulator sample rates, see page 192.
Use the “Stimulation sample rate” pull-down menu to select a unique sample rate for the stimulator.
See also: Application Note AH162 - Using the Stimulation Features of the MP System.
X

X189

X

X

H

H

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Stimulator Parameters
The Stimulator parameters are set by using the buttons in the right pane of the setup window.
Reset
Refresh the display; use after the time scale has been adjusted.

Scaling

Scaling button—Rescale stimulus signals to units other than
Volts according to the Change Scaling Parameters.
This type of rescaling does not change the amplification of the
signal, it is useful for recalibrating the output signal to more
meaningful units. In the example shown here, an output signal of
+10 Volts is rescaled to +128 dB, while an output signal of –10
Volts is rescaled to reflect 0 dB.

Relative

Set the duration of each segment of the output waveform in Seg # Width. In the sample dialog
shown below left, a 5000 msec output is created by entering individual segment widths: 500 + 400 +
250 +200 + 3650 = 5000 msec.
Note The segment level fields are hidden by default and must be expanded by clicking the Segment
Configuration “+” button (below).

For details about stimulator segment and width configuration, see page 189.

Output
Analog Output 0/Analog Output 1: Signals can be output on one or two analog output channels. The
output channels are listed as A0 and A1 and correspond to Analog Output 0 and Analog Output 1 on the
HLT100C (MP160) or UIM100C (MP150) module.

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For MP160/HLT100C: Use a CBL100 3.5 mm cable with two CBL122 RJ11 adapters to connect Analog
Outputs A0 or A1 to Analog Channels 1 or 2.
For MP150/UMI100C: Use a CBL100 3.5 mm cable to connect Analog Outputs A0 or A1 to Analog
Channels 1 or 2.
§ For dual stimulation and independent control, connect an output device to A0 and A1.
§ See Analog Output for MP160/150 Users notes on page 187.
The maximum resolution of a stimulus signal output through an analog channel is 22 µsec; this means
that the shortest segment in the stimulus signal must be at least 22 µsec in duration.
Duration
X

X

Set independently for A0 and A1.

Off: Turn Output OFF (no stimulus signal output).
Output once: Output the stimulus signal once.
Output continuously: Output the stimulus signal for the duration of the acquisition (forever).
When Output continuously is selected, a vertical line is generated at the end of the first section of the
waveform in the stimulator window to indicate where the first output signal ends and the second begins.
The line can be dragged left or right like a vertical segment in a stimulus waveform to control the duration
of the waveform as it is continuously output. Maximum continuous waveform output is 20 kHz.

Use to choose the Stimulator sample rate for the generated signal. (The Stimulator sample rate is independent of
the acquisition sample rate. See page 192 for sample rate details.)

Control timing of output by aligning it with the Start button, waiting until a trigger is initiated before generating
the signal, or manually toggle the selected stimulator on or off. Click the “lock” button
to synchronize both
stimulator outputs to the On/Off buttons.
Note “Wait until trigger” option is only active if Triggering is enabled in the “MP160/150 > Set Up Data
Acquisition > Trigger” menu.
Trigger
When a trigger option is selected (in the Trigger Setup window), AcqKnowledge allows selection of
additional options with respect to when the signal is output. By default, the stimulus signal will be output
when the Start button is clicked. When a trigger is enabled, however, there’s an option of either outputting
the signal when the Start button is clicked or when the trigger is initiated. The trigger option is added to the
stimulator window when a trigger is enabled in the Trigger setup dialog (described on page 181).

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Manual Stimulator Control
When an MP160/150 unit is being used, the manual stimulator controls at the bottom of the Stimulator
Setup dialog can be used to start and stop stimulators independently of the acquisition. If changes are made
to the stimulus wave while a stimulator is running, the stimulator will need to be turned off and then back
on to apply the changes to the settings.
The manual stimulator controls cannot be used if the MP160/150 is set to acquire in averaging mode.
· The stimulator output will start simultaneously with the acquisition.
· The On/Off buttons will start and stop the stimulator output.
If Dual Stimulator settings are active, “Start with” applies to both stimulators.
A “lock” between the two sets of controls can be used to turn both stimulators on or off at
the same time. This lock is useful for two-channel stimuli delivery, such as stereo sound.
UNLOCKED

LOCKED—Both channels Start/Stop together

Stimulator Output Type

If an averaging acquisition is selected in the MP hardware setup, the timing can be set to delay the averaging
pass until after the signal is generated, or to include the signal output in the averaging pass. Note that the signals
cannot exceed the duration of the averaging pass.
The “Digital” setting will generate a true digital pulse (0 Volts and +5 Volts) prior to the averaging pass on
digital I/O Channel 15.
§ For Averaging details, see page 169.
X

Finish all output, then start averaging pass

X

Include output in averaging pass

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Analog Output for MP160 and MP150 Users
The two MP160/150 Analog Output channels can independently output static or dynamic values:
· Static output:

Use “Manual Control” (page 242) to set the output level for each channel in the range -10V to
+10V.
· Dynamic output: Use “Stimulator Setup” (page 183) to define the output level and pattern.
The MP160/150 will automatically use the “Manual Control” value if:
· No acquisition is in progress OR
· Acquisition is in progress but the Stimulator is disabled via the “Setup Stimulator” dialog.
The MP160/150 will only use the “Stimulator Setup” value if:
· Acquisition is in progress (or before Averaging pass) AND
· Stimulator is enabled via the “Stimulator Setup” dialog.
When the stimulator is in use:
1. Any Stimulator Output starts (from before Time = 0) with the value established for “Manual Control.”
2. If Segment # Width = 0 the stimulator ignores the associated Segment # Level.
3. If the stimulator is in 1x mode, after the output waveform is sent, the value of the last segment is fixed until
acquisition stops.
4. When acquisition stops, the stimulator resets to the “Manual Control” value.
The following dialogs and output illustrations demonstrate how the “Manual Control” value influences Analog Output
for the Stimulator when an MP160/150 is used:
X

X

X

Acquisition parameters:

X

Stimulator parameters:

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Manual Control list box:

Stimulator Output pattern (using MP160/150)

:

For details on Manual Control, see page 242.

Dual Stimulation
For independent control of two stimuli (such as sound and electrical output), set stimulator functions for Output
to A0 and A1 for each MP160/150 unit. Click the tab for each output at the top of the Stimulator Setup dialog
and complete independent settings.

§

For additional stimulus paradigms, add MP160/150 units (see Multiple Hardware, page 168).
X

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Square waves
Square waveforms are useful for
generating pulse waveforms, which can be
used as stimuli or to trigger a stimulusgenerating device (such as a flash device or
a tone generator).
To output a square wave, choose the
“Output Once” in the “Duration” section.
A rectangular wave should be visible in the
window. The shape of the can be controlled
by manipulating the wave’s various
segments. A square wave has five
segments, and AcqKnowledge allows
flexible configuration of the level
(amplitude) and width (duration) of each
segment.
NOTE: The segment level fields are
hidden by default and must be expanded by
clicking the Segment Configuration “+”
button (below).

In a square wave, each of the editable segments is oriented horizontally, with vertical segments connecting the
adjacent sections of the wave. The first segment of a pulse waveform is the segment that appears at the far left
of the waveform section. By positioning the cursor on this segment of the waveform, observe that Segment #1
level (vertical offset) is 0 Volts, and the Segment #1 width is 500 msec. (See segment boxes in center of
Stimulator window.
To adjust the level of a segment, either:
a) Enter the desired level in the Seg # Level box; or
b) Position the cursor on the first segment of the waveform and drag it up or down using the mouse
(segment 2 is selected in the preceding dialog, and appears in red).
To change the duration of a segment, either:
a) Enter a value in the Seg # Width box at the bottom of the Stimulator Setup dialog; or
b) Position the cursor on the first vertical segment in the setup dialog, click the mouse button, and drag the
vertical segment left or right. Moving the first vertical segment left shortens the duration of the first
segment, whereas moving the first vertical segment right lengthens it.
Each of the segments in the wave can be “edited” in this way.

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Tone Stimuli
Tone waveforms allow for the creation of pure tone signals of any duration, magnitude, and frequency.
This option outputs a pure sine wave, which is useful for audiological and stimulus response testing.
A tone waveform is comprised of two segments,
with only the second segment being the actual tone
itself. This allows for inclusion of a pre-signal
delay (by setting the level for Segment #1 to 0
Volts and the duration to a desired value).
To set the duration of the tone, adjust the length of
segment #2 (by changing the Seg #2 Width value
box or by clicking and dragging the segments
within the window). As shown, there is an
additional (uneditable) section of the waveform
after the second section. This segment returns the
last value from segment two, and continues to
output that signal level until the acquisition is
terminated (if the stimulator is set to output once)
or until another signal is output (if the MP System
is set to output continuously).
There are three additional parameters for Tone
waveforms: frequency; magnitude; and tone phase.
§ Tone frequency refers to the frequency of the second segment of the waveform. This can be set to any
value, although the most common settings are between 20 Hz and 20,000 Hz.
§ Magnitude refers to the peak-to-peak range of the signal, which can range from ± 0 to ± 10 Volts.
§ Phase of the stimulus signal can be any value equal to or greater than 0 degrees. Phase settings of more
than 359 degrees will be rescaled to fit the 0°-359° range. In other words, setting the phase to 360° or
720° has the same effect as setting the phase to zero degrees.
Ramp Waves
Ramp waveforms are useful for constructing a
monotonically increasing or decreasing stimulus
signal.
Ramp waves are comprised of three segments and
the amplitude and duration can be set discretely for
all three sections.

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Arbitrary Waveform
The Arbitrary waveform option is used to set a
waveform’s shape and length using standard
AcqKnowledge editing functions.
§ The length of an arbitrary waveform is
only limited by the available memory.
§ Unlike the other types of waveforms,
Arbitrary waveforms have no segments, so
the “shape” of the waveform is determined
by selecting an existing waveform and the
only parameters that can be set are Scaling,
Repeats, and Trigger.
§ Maximum continuous output is 20 kHz.
To create an arbitrary waveform:
A. Copy waveform segment
1. Open a waveform in a standard graph
window.
2. Select the section of the waveform to be outputted.

Return to the Stimulator Setup dialog—the selected area will automatically be pasted into the dialog.

Stimulator Icons
Waveforms:

Square wave
Tone (sine) wave
Ramp wave
Arbitrary wave

Parameters:

Reset the display (use after adjusting the time scale)
Scaling (rescale Stimulus signals to different units)
Set time base to relative

Output:

Tab to output to Analog Output channel 0 (default)
Tab to output to Analog Output channel 1
Manually start and stop stimulator output by clicking the On/Off
buttons. When the padlock is engaged, both stimulator outputs can
be controlled simultaneously.

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MP160/150 Stimulator Sample Rates
The MP160 or MP150 is the most common data acquisition device used with AcqKnowledge, and when
combined with the HLT100C/UIM100C and STM100C modules, capable of outputting various waves at
different rates, durations and types. As explained earlier in this chapter, there are four basic Stimulator signal
types: Square, Sine, Triangle and Arbitrary waves. Square, Sine, and Triangle waves are limited to 4096
samples, which may be outputted once or continuously. 4096 samples also define the upper limit of a short
burst wave. Arbitrary waves, like the other types, can be outputted once or continuously, but are not subject to
the 4096 sample upper limit.
The Stimulator output sample rate may be the same, lower, or higher than the acquisition sample rate. The
output signal can be redirected to an analog input channel.
The Stimulator output sample rate is configured in AcqKnowledge via a dropdown menu in the stimulator setup
dialog box (the window is opened by choosing MP160/150 > Set Up Data Acquisition…” and choosing
“Stimulator” in the left pane.

This rate specifies the frequency at which the analog output changes. This frequency has no necessary
relationship to the sample rate of the source graph or the sample rate of the graph window associated with this
data acquisition setup. By adjusting this frequency, the stimulator may be made to produce an output that varies
more quickly, more slowly, or at exactly the same rate as that of the signal in the source graph. To have the
timing match that of the source, set the stimulator sample rate equal to the graph sample rate of the source
graph, even if the channel selected in the source graph has been downsampled relative to its graph sample rate.
For example, here the source graph contains a 5 Hz sine wave in a channel with a waveform sample rate of 250
Hz in a window with a graph sample rate of 2000 Hz: (See following page.)

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Sine wave acquired at 2000 Hz downsampled to 250 Hz

In another window, this graph window is used as the source for arbitrary waveforms from both of the two
analog output channels:

Using a pair of CBL100s, ANALOG OUTPUT 0 and ANALOG OUTPUT 1 were redirected to ANALOG
CHANNELS 1 and 2 respectively. The graph sample rate for this acquisition was 2000 samples/second. The
calculation channel used to create the sine wave in the source graph was also a part of this graph; this channel
(Channel 40) was downsampled to 250 Hz.

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Note that Channel 1, containing the recording of the output at 2000 samples/second, matches the timing of the
original channel overall, but the original data have been upsampled to that sample rate with no interpolation to
generate the output voltages. This is more easily seen by overlaying the two waveforms and zooming in:

Arbitrary wave sources are derived from any waveform within a saved data file or from a newly created
waveform. Calculation channels, Transform and Edit operations may also be used to create unique waveforms.

Example source wave

The Expression calculation channel, Absolute value transformation and Edit Copy/Paste operations were used
to create the example waveform shown above. The highlighted portion was used as the source wave.
The MP160/150 supports an aggregate (combined channel) sample rate of 400 K samples and has an internal
memory of 512 K samples.
Aggregate Sample Rate = # analog channels * Acquisition Sample Rate
Any down sampling of channels is applied in AcqKnowledge, and does not affect the sampling rate generated in
the MP160/150.

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Up to 512,000 samples can be uploaded into the MP160/150 memory and then outputted as a stimulator signal.
Longer source waves will upload the first 512,000 samples, and the remaining waveform data as memory
becomes available.
The following components affect the limits for the stimulus output:
- Acquisition setup
o mode
§ MP160/150 Memory
§ Save to disk or memory
o sampling rate
- Stimulator setup
o Duration
§ Output Once
§ Output Continuously
o Stimulator sample rate
o Analog Output: one or two analog output enabled
- Source graph/wave length
o Short burst wave ≤ 4096
o Long waves > 4096 and ≤ 512 K samples
§ Within the limits of the MP160/150 internal memory
o Longer waves > 512 K samples
There are two basic AcqKnowledge acquisition modes, “Save to MP160/150 Memory” and “Save to
Memory/Disk.” On-line Averaging also uses the MP160/150 memory.
Save to MP160/150 Memory: This acquisition mode was designed for short burst signals at high acquisition
sample rates with short duration. While longer acquisition can be acquired in this mode, the system may be
slow to respond. Depending on the computer resources, it may take several seconds for the screen to update.
Should this become an issue, adjust the CPU allocation in the AcqKnowledge Preferences. In the Preferences,
select “Performance” and move the slider to the right toward Better data transfer for high speed acquisition.
AcqKnowledge Preferences are accessed from the Main Toolbar
or via Display > Preferences.
Analog Output Upper Limits Summary
The upper limits for short burst, long, and longer waves are provided below.
Note: At high or maximum aggregate acquisition sample rates, the display may become sluggish and data may
take several seconds to be displayed. Additional user actions may overwhelm the system.
Short Burst Wave (≤
4096 samples)

Long Wave (> 4096
samples but ≤ 512 K
samples)

Longer Waves (≤
512 K samples)

Stimulator Sample Rate:

100 K max
(sample rate not
adjustable for
averaging)

100 K max

20 K max

Acquisition Modes:

Save to MP160/150
Memory
Save to Averaging

Save to MP160/150 Memory
Save to Memory or Disk

Source Output Maximum
per Analog Output:

4096 samples

512 K samples (256 K if dual stimulators are
used via outputs A0 and A1)

Maximum Aggregate
Acquisition Sample
Rate:

400 K

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Chapter 10

Output Control

Note Output Control chapter refers to MP36R hardware only.

For MP160 or MP150, see the previous chapter, ‘Set Up Stimulator.’
The MP36R hardware can output pulses or analog voltages via the Analog Out
port; this port is also used to connect to BIOPAC’s external stimulators. The
MP36R has an additional I/O Port which is used to output digital (TTL Level)
signals.
Parameters for output signals are set via Output Control. Access to a specific
Output Control is via the MP36R > Output Control submenu.
There are three basic Output Control categories:
·

Pulse – Pulses, Stimulator-BSLSTM, Low Voltage Stimulator and Human Stimulator-STMHUM

·

Pulse trains – Pulse Sequence, Sound Sequence and Visual Stim Controllable LED-OUT4

·

Other – CH to Output, Digital Outputs, Arbitrary Wave Output

There are a total of ten Output Controls for the MP36R:
MP36R Functionality

Output Control

See…

CH# to Output

page 198

Digital Outputs

page 200

Control 8 digital outputs

Pulses

page 186

Use with third-party devices; software can control
pulse width and repetition.

Stimulator - BSLSTM

page 201

Low Voltage Stimulator

page 201

MP36R: Use OUT3 adapter for MP36R built-in low
voltage stimulator. Software can control pulse
amplitude, width and repetition (-10 to +10 V)

Pulse Sequence

page 188

Direct analog CH1-4 or digital D1-8 output. Allows
for output of customized pulse trains.

Human Stimulator – STMHUM

page 202

Hand-held stimulator, allowing the subject to control
the stimulus delivery. Configurable from 1-100 V.

Visual Controllable LED – OUT4

page 207

Direct analog CH1-4 or digital D1-8 output. Allows
for output of customized pulse trains to an LED
transducer for visual stimulus studies (OUT4).

Arbitrary Wave Output

page 208

Sound Sequence

page 207

Direct analog CH1-4 to output listen to signals

X

X

X

X

X

X

X

X

X

Use with BSL Stimulator

Arbitrary wave output is very similar to the stimulator
in the MP160/150, allowing for generation of square,
sine
or ramp signals, or arbitrary signals from
another open
graph window.
Outputs customized sounds assignable to a user
configurable pulse train.

To open an Output Control, select it from the MP 36R > Output Control submenu. A checkmark appears next
to the submenu selection and an Output Control panel is displayed, bordered in red in the active data window.
To close an Output Control, select from the menu again (toggles between display and hide) or right-click in the
open control panel and choose Close.
Only one Output Control panel per graph may be open at any time. Switching between different data files may
display different output control panels, which operate differently.

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Because some output devices can be used for stimulation on humans and can achieve voltages up to 100 Volts,
built-in software logic makes output control as safe as possible. See page 222 for safety notes regarding human
subjects. The following applies to all Output Controls.
X

X

The output will not operate unless its software control panel is open.
When an Output Control panel is closed, or the AcqKnowledge application is closed, MP36R output goes to 0
Volts, preventing the output device from sending pulses.
When an Output Control panel is opened, output is always OFF until activated by a click of the ON/OFF switch
in the control panel or, if parameters allow, a click of the Start button in the data acquisition window.
(Exceptions are the Digital Outputs Control when set to the preference “Set each output immediately.”)
If desired, custom Output preference parameters can be saved as a preset for a current graph (file preset) or for
all graphs (global preset) by using the “Save Settings” button in the Output Preferences window. A saved
Output preference can be selected from the Output Settings pop-up menu in the Output Control’s panel.
Output Control Preferences dialogs establish the parameters for output. Preferences dialogs are only available
when the corresponding Output Control panel is open and active.
To generate the Preferences dialog:
Open an Output Control panel and then right-click over it to generate a pop-up menu. Choose
Preferences to open the dialog (Close will close the control panel).

If a control panel entry box is grayed, its values may be already be established or limited by settings in the
Preferences dialog. If Preferences parameters allow, enter values directly in the Output Control panel.

Key into the entry boxes and then enter the value by pressing the Enter key.
Use the Tab key or mouse to move to another entry box.
Click the OK button if in the preference dialog.
Values entered into a control panel or its Preferences dialog that are outside the specifications of the output
device, or outside the limits defined by the Preferences dialog, may change automatically to reflect either the
closest value to that requested that the hardware can achieve, or the closest increment defined by the limits in
Preferences.
For example, if a Pulse width of 5 ms is entered into the Pulses Output Control panel entry box, but Preferences
defines a range limit of .5 to 2 ms for Pulse width, the system will automatically change the new entry to 2 ms.
Saving Panel settings:
Output Control panel settings will be retained until a file is closed or saved. If a file is closed but not saved,
settings will be lost (defaults established); if a file is saved, panel settings will be saved.

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CH# to Output

The CH# to Output Output Control redirects an analog input signal to the Analog Out port on the back of the
MP36R UNIT. The signal from the assigned channel will continue to be record and plot data.
This Output Control is used commonly when attaching headphones to the MP36R unit to listen to signals
coming in on an analog input channel; for example listing to the Electromyogram.
To display this control panel:
Choose MP 36R > Output Control > CH# to Output to open the control panel.
MP36R users may use analog input CH1-CH4. Channel 3 is the default setting. If another channel N has been
designated, the menu will read “CH.”
Use the control panel ON/OFF Switch to start and stop output. OFF grounds the output so no signal (or sound)
should be present.
Set Preferences to designate which channel to redirect to output.
Open the Preferences dialog by right-clicking the control panel.
Use the pull-down menu to select the desired channel CH 1-4 to use for the output.
Click OK to set the output channel and return to the control panel.
Note

Only the Hardware settings (Gain, Offset, Input Coupling)
from the Input Channel Parameters dialog (MP36R > Set Up
Data Acquisition > Channels > Setup) will be applied since
output is established prior to the processing of Digital Filters.

See MP36R Input > Output Scaling values on the next page.

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MP36R Input > Output Scaling
The MP36R hardware can pipe signals from any channel input to the output using the “CHX to Output” control
panel in the AcqKnowledge software—due to the difference between the input and output range, there will be a
change in signal level (scaling). The output range depends on the output pin used as shown in the following
table.
Output Pin
(Analog Out port)

Pin Description

Pin 1

Headphones,
A.C. Coupled
Low Voltage Stimulator,
D.C. Coupled

Pin 2

Output Range
(Volts)
-2.048 to +2.048
-10 to +10

The input range is gain-dependent. The table below shows the scaling (multiplying) factors to use for each gain
setting.
Gain

Input Range
+- millivolts

Output Scale**—accurate to ±10%
Factor 1
Factor 2
Pin 1 (Headphone out)

x5
x10
x20
x50
x100
x200
x500
x1,000
x2,000
x5,000
x10.000
x20,000
x50,000

±2V
±1V
± 500 mV
± 200 mV
± 100 mV
± 50 mV
± 20 mV
± 10 mV
± 5 mV
± 2 mV
± 1 mV
± 0.5 mV
± 0.2 mV

Pin 2 (Low Voltage
Stimulator)

1.024
2.048
4.095
10.238
20.475
40.950
102.375
204.750
409.500
1023.750
2047.500
4095.000
10238.000

5
10
20
50
100
200
500
1,000
2,000
5,000
10,000
20,000
50,000

Notes
*

1: To properly measure the output signal, at least a 2K Ohm load is necessary.

**

2. Input to Output scaling is accurate to within 10%.

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Digital Outputs Control

The Digital Output Control manages the signal output for each of the eight digital lines via the I/O Port located
on the back of the MP36R. Digital lines are used to control external devices.
The digital output uses standard TTL levels which correspond to the control panel setting as follows:
Control Panel setting

Output Voltage level (Volts)

0

0

1

+5

To display this control panel:
Choose MP36R > Output Control > Digital Outputs to open the Digital Outputs Control panel
Click each digital output line to set its digital state to 0 (off) or 1 (on).
To set Preferences for Digital Outputs, open the
Preferences dialog by right-clicking the control panel.
Select from the following two options:
Set each output immediately (default) allows the state of
each digital output line to be toggled between 0 and 1, and
changes the state immediately. In this mode, no Set button
is available in the control panel. Output for each line is set
upon clicking its toggle button.
Set all outputs when Set button is pressed allows the state of each digital output line to be toggled, but the
states will not physically be changed until the Set button is clicked on the control panel. In this mode, a Set
button is available in the control panel. When the Set button is clicked, all eight digital lines will update
simultaneously.

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Pulses Output Control
Stimulator – BSLSTM Output Control
Stimulator – Low Voltage Output Control
Stimulator Human Stimulator (STMHUM) Output Control

Control panel options for Pulses, Stimulator – BSLSTM and Stimulator – Low Voltage

Additional control panel options for Low Voltage Stimulator
A variety of pulse output options are available. Exercise caution when using any of the options with human
subjects—see the Safety Note on page 222.
X

X

Pulses Output Control
Select this Output Control for general pulse output, or when synchronizing to 3rd-party devices.
Use for reaction time measurements, where a subject listens with headphones for a series of “clicks” (pulses)
and responds as quickly as possible with a button press. Determine reaction times by calculating the time
between the start of the pulses and the responses.
Use with the BIOPAC STP30W Stimulus Presentation System (SuperLab) to measure responses to visual or
auditory stimuli. To perform sophisticated evoked response averaging tests (e.g. P300), pair triggers with
different visual or auditory stimuli.
Use to trigger another device (automatically send a pulse from the MP36R UNIT when acquisition starts).
Use to control a 3rd-party stimulator. BIOPAC recommends use of the BIOPAC BSLSTM Stimulator with the
MP UNIT and BIOPAC software. If using the BSLSTM Stimulator, use the Stimulator - BSLSTM Output
Control instead of this Pulses Output Control.
Stimulator – BSLSTM
Select this Output Control when using the Biopac Student Lab stimulator
(BSLSTM)
Use with stimulation electrode HSTM01 for safe stimulation of human
subjects (0 – 100 Volts), as well as lower voltage (0 - +10 Volt) generalpurpose stimulation, such is used with amphibian muscle or nerve
preparations.
Set up note Placing the BSLSTMA/B unit too close to MP36R hardware can result in data distortion of the
BSLSTMA/B pulse width signal; distortion is more apparent at higher sampling rates.
·
·

NEVER set the BSLSTMA/B atop MP36R hardware
Position the BSLSTMA/B away from the MP36R hardware to reduce the signal distortion
Low Voltage Stimulator
Select this Output Control for low-voltage (-10 - +10 Volt), direct drive
stimulation via MP36RAnalog Out port (with or without OUT3 BNC
adapter).

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Use with stimulator electrode HSTM01 for safe, stimulation of human subjects (0 – 100 Volts), as well as lower
voltage (0 - +10 Volt) general-purpose stimulation, such is used with amphibian muscle or nerve preparations.
Outputs through a BNC connector so it can be used with most stimulation cables (such as those that terminate in
a needle probe).
Stimulator Human Stimulator – STMHUM
Select this Output Control to conduct stimulation studies that enable subjects to control the stimulus delivery.
This hand-held stimulator connects directly to the MP36 Analog Out port
and has a red button for delivering the stimulus signal. The electrodes on
the bottom of the unit are placed directly onto the subject. The STMHUM
functions much like the BSLSTM but with no additional hardware required.
The voltage range is 0 – 100 volts and can be limited or locked to a user
defined level in the STMHUM Output Control panel, which resembles that
of the Low Voltage Stimulator.
To use one of these control panels:
Choose MP 36R > Output Control and then select Pulses, Stimulator – BSLSTM, Low Voltage Stimulator, or
Human Stimulator (STMHUM).
Right-click the Output Control panel to generate the Output Preferences dialog.

Set the Preferences.
General: ON/OFF, Number of pulses, Event options — see page 214
Advanced: Pulse width, Pulse repetition (rate) and Verify Transducer (STMHUM) — see page 217
Level (Low Voltage Stimulator and STMHUM only): Pulse level — see page 219
Reference Channel (Low Voltage Stimulator, Pulse Sequence and STMHUM only): The Reference Channel is
the channel on which the pulse is outputted, and configurable as Analog channels CH1-CH4, or Digital
channels D1-D8.
Once configured, Preferences may be saved using the Save Settings command, activated by pressing the saved
settings from the pop-up menu in the control panel (see page 213).
Confirm the settings in the control panel. Adjust as desired within the parameters established in Preferences.
Entry limits: Settings entered into the Preferences dialog may establish, or limit, the values in the Output
Control panel entry boxes. Enter pulse settings directly into the control panel only if the Preference settings are
not locked to a specified value. A grayed or disabled entry box indicates that the values are locked.
Initiate the pulse sequence as defined in Preferences (see page 214).
X

X

X

X

X

X

X

X

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X

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ON/OFF Button in Output Control Panel uses the switch in the Control panel.
Recording uses the Start /Stop button in the data acquisition window.
To close an Output Control panel:
Right-click anywhere in the Output Control panel to generate a pop-up menu and then choose Close, or select it
(or another output control) from the MP36R > Output Control submenu.

Pulse Sequence Output Control
This Output Control allows sequences of pulse configurations and delays to be sent to the MP36R unit, making
it possible to create more complex stimulus setups.
Enabling the pulse sequence output control option will display the following control panel at the top of the
graph window:

Pulse sequence configuration is performed in the Preferences dialog of this output control panel. (Accessible via
right-click on panel shown above.) When a pulse train element is selected in the configuration, the controls will
become visible in the right hand portion of the preferences dialog. The configuration makes use of three basic
building blocks:
A sequence consisting of a number of delay and pulse train elements. The final configuration consists of one or
more sequences that are outputted in order. Normally the entire configuration is outputted. There is a special
operational mode on ‘Start with Recording’ that will take only the indexed sequence matching the current
recording segment.
A pulse train element consists of Pulse count, Width and Pulse repetition, These elements can be fixed or
randomly generated.
A delay element that allows for the introduction of time during which no pulses will be generated.
Each one of these building blocks also has a “repeat” count associated with it that will perform the action a set
number of times. (Adjust by selecting the desired ‘Repeat’ and inputting a new value) Individual sequences,
pulse trains and delays can be added, deleted, repeated and reordered as desired. In the right pane of the
Preference dialog (shown below), fixed or random pulse counts, widths and repetitions can be configured and
combined. As in other Output Controls, custom settings can be saved and organized in a list view. (See below
for additional setup dialogs)
For a full explanation of preferences and tabs common to all Output Control panels, see the “Pulse Definition”
section on page 212 and the “Output Control” section on page 212.

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Add:

Preferences available in Pulse Sequence tab
Displays pop-up menu for adding Sequences, Pulse Trains or Delays.

Output:

Displays the configured sequences and sequence elements for the current or saved session.

Repeat:

Editable field for setting the number of times the pulse train or pulse train element is repeated

Pulse count:

Fixed – a set number of pulses is generated per sequence.
Random – set a random number of pulses to be generated per sequence.

Width:

Fixed – each pulse width will be of a set duration, in units of microseconds, milliseconds, or
seconds.
Random – sets the pulse width duration to fall between two set time ranges.
Pulse repetition: Fixed – sets a fixed interval between the start of one pulse to the start of the next pulse
Random – sets a random interval between two set values for the start of one pulse to the start
of the next pulse.
Move Up/Down Delete: Selectively reorders or deletes the various pulse train elements.
Save Settings: Saves modified settings as a custom preset for the current graph, or for all graphs.
Organize List: Orders custom presets into a list and categorizes the custom presets for the current file or
globally across the application.

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Preferences available in Options tab

Preferences available in Reference Channel tab

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Delay Preferences
About Delay between Pulse Trains:
The amount of actual Delay between pulse trains will vary from the set value depending upon the pulse
repetition value that is used. In the example sequence below, a Delay of 100 milliseconds between pulse trains
has been set up, combined with a pulse repetition rate of 20 milliseconds. Because the pulse repetition rate is
applied before the Delay occurs, the actual Delay between pulse trains in this case will be 120 milliseconds. If it
is critical that a Delay reflect an exact value, it is advisable to subtract the selected pulse repetition value when
setting up the Delay parameters.

Delay between pulse trains

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Visual Stim Controllable LED – OUT4 Output Control
This Output Control is used to set up parameters for the OUT4 LED transducer used for conducting visual
stimulus studies, in which flashes of light of varying intensities and intervals are presented to a subject. The
OUT4 LED transducer is connected directly to the MP36 Analog Out port.
To use this Output Control choose MP Unit > Output Control > Visual Stim Controllable LED.

The Visual Stim Controllable LED Output Control panel is identical to the Pulse Sequence control panel, but
with the addition of an intensity control for controlling the LED brightness level. The preferences operate
identically to those of the Pulse Sequence Output Control covered in the previous section.

Pulse Sequence Tab for Visual Stim Controllable LED

Options Tab for Visual Stim Controllable LED

Reference Channel Tab for Visual Stim Controllable LED
For specifics on the Visual Stim LED preferences set up, see the Pulse Sequence Output Control section on
page 203.

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Arbitrary Wave Output
AcqKnowledge with MP36R supports signal output through one analog channel while data is being acquired.
This is configured by using the Arbitrary Wave Output option. In general, the Arbitrary Wave Output is used in
conjunction with an OUT3 Low Voltage Stimulator connected to the Analog Out port (rear panel of MP36R).
Four types of signals can be output:
Square waveforms—page 189 X189
Ramp waveforms—X190
Tone waveforms—X190X
Arbitrary waveforms—191
Each of these waveform types can be set to repeat signal output either Once or Continuously, and parameters
can be set to either Relative or Absolute time scales. Like the standard graph window, the Stimulator setup
window plots time on the horizontal axis and amplitude on the vertical axis.
Use the Stimulator window (see following page) to create and shape waveforms for output. Adjust the
Stimulator Sample Rate to further control the parameters of the Stimulator Output design.
For any waveform (or stimulus) to be output, the following parameters must be specified; the type of stimulus,
the “shape” of the signal, the output channel to be used, and how many times the stimulus should be output.
The above parameters are set up from within the Stimulator Setup dialog. Regardless of the type of waveform
selected, stimulus signals will normally be by clicking the AcqKnowledge graph’s “Start” button or by using the
On/Off Output Control panel button.
To set up the Arbitrary Wave Output:
1. Select MP36R > Output Control > Arbitrary Wave Output.
2. Right click the Arbitrary Wave Output Control panel and choose “Preferences” to launch the Stimulator
setup window.

3. Set the desired waveform type and stimulator options in the Stimulator window.
The MP36R Stimulator setup window (see following page) is nearly identical to the MP160/150 setup window
detailed in the previous Stimulator chapter (page 183, with the following exceptions:
· The signal output is limited to one analog channel (vs. two in MP160/150 hardware).
· The pulse sequence is initiated by starting the acquisition or by toggling the On/Off button on
the Output Control panel (vs. the Timing or Trigger controls in MP160/150 hardware).
· Stimulator averaging output is not supported in MP36R hardware.

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Stimulator Icons
Waveforms:

Square wave
Tone (sine) wave
Ramp wave
Arbitrary wave

Parameters:

Reset the display (use after adjusting the time scale)
Scaling (rescale Stimulus signals to different units)
Set time base to relative

Output:

Sets Stimulator to be active when “Start” button is
clicked OR when toggled via the ON/OFF button on
the Arbitrary Wave Output control panel.

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Duration

Off: Turn Output OFF (no stimulus signal output).
Output once: Output the stimulus signal once.
Output continuously: Output the stimulus signal for the duration of the acquisition (forever).
When Output continuously is selected, a vertical line is generated at the end of the first section of the
waveform in the stimulator window to indicate where the first output signal ends and the second begins.
The line can be dragged left or right like a vertical segment in a stimulus waveform to control the duration
of the waveform as it is continuously output. Maximum continuous waveform output is 20 kHz.
Stimulator Sample Rate
Use to select the Stimulator sample rate for the generated signal. (The Stimulator sample rate is independent of
the acquisition sample rate. See page 192 for sample rate details.)
For more details on all other MP36R Stimulator parameters and functionality, see the previous MP160/150
Stimulator chapter on page 183.
See also: Application Note AH162 - Using the Stimulation Features of the MP System.
H

H

Sound Sequence Output Control
Sound Sequence Output Control offers users the option of configuring and customizing sounds to be outputted
for aural stimulus experiments. The control panel and Preferences dialogs used for Sound Sequence closely
resemble that of Pulse Sequence. The built-in sound resource (a default “click”) may be used or any other file in
*.WAV format can be substituted via the “File” and “Browse” button. The “Width” and “Pulse Repetition”
values are dependent upon the duration of the sound file selected for output. The “Test” button will output an
audio sample of the selected sound resource.

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The option all sequences means that each configured sound sequence (regardless of number) will be outputted
within the same segment. If "Once" is selected in the "Output entire pulse sequence" option, a configured
sequence will be heard one time only. If "Continuously" is selected, the first Sound Sequence will be repeated
after the last one has completed, looping the pattern repeatedly until the recording is stopped.
The option each sequence means that each sound sequence will be outputted on a segment-by segment-basis
only. For example, if one Sound Sequence is configured, it will only be heard during the first recording
segment, but not during the second recording segment). If two Sound Sequences are set up, the first one will be
heard during the first segment and the second one during the following segment. If no additional Sound
Sequences have been configured, nothing will be heard during the third segments and beyond. (Exception: If
"Save Once" acquisition mode is used, the Sound Sequence will be repeated when the recording is overwritten
during subsequent passes).

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Pulse Definitions
The following terms are used in the Output Control panels, Preferences, and guidelines for Pulses, Stimulator –
BSLSTM, Low Voltage Stimulator and Human Stimulator-STMHUM.

Delay before first
Pulse

Initial delay from start of acquisition to start of first pulse.

Number of pulses

Number of successive pulses that will be sent out at the specified Pulse Width,
Repetition and Level. Set for Single (1), Multiple, or Continuous (Cont).

Pulse Level

Amplitude of the pulse, expressed in Volts.
Note: The output of the BSLSTM is 0 Volts when the pulse is not active.

Pulse Repetition

Can be expressed as Period (ms) or Rate (Hz).

Also called —
Events per second
Pulse frequency Pulse
sequence
Pulse train
Repetition rate
Sample train

Period: Time between pulses; measured in milliseconds from the start of one pulse to
the start of the next pulse.

Pulse Width

Time that the pulse is in the non-zero or active state.

Rate:

Number of pulses that occur in a one-second interval; measured in Hertz.

Rate relates to Period as: Rate (Hz) = 1000 / Period (ms)

Output Control Panel Descriptions
The Output Control panels for Pulses, Stimulator – BSLSTM, Low Voltage Stimulator and Human StimulatorSTMHUM work in conjunction with Preferences to control pulse output. Control panel functions are detailed
here:
OUTPUT CONTROL PANELS
General Notes

Pulse parameters can interact with each other.
For example, the pulse repetition period cannot be set to a value less than the pulse
width.

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OUTPUT CONTROL PANELS

Preferences

Output Settings

In order to simplify the interaction, the Pulse width entry overrides other entries as
required; it is the priority parameter.
For example, if the pulse width is changed such that it exceeds the pulse repetition
period, the pulse repetition period will be automatically adjusted to accommodate the
new pulse width entry. If, however, the pulse repetition period is changed such that
it is less than the pulse width, the repetition period will be changed, upon attempted
entry, to the closest value that can be achieved without changing the pulse width.
Entries are checked and rounded (not truncated) as necessary to meet limitations of
the hardware or the Preferences.
When a file is opened, the output device will not turn ON automatically. A user must
manually press either the “Record” button or the “Start” button.
The exceptions are the “Voltage Output” control panel and the “Digital Outputs”
control panel if “Set each Output immediately” is selected; these settings will output
values immediately.
Output control settings are “local,” which means that they are stored at the data file
level, not the program level. Use the save as graph template (File > Save As) option
to use existing Preferences in new data files.
If a file is saved with an Output Control panel visible and then closed, the panel will
be visible when that file is re-opened.
Right-click a control panel to generate the Preferences dialog, and then select a tab
for the settings to be adjusted.

Displays the name of the current Preferences setting. The pull-down menu lists the
names of all output Preferences saved using the Save Settings button (see page 213).
The pull-down menu is not accessible when an output pulse train is in progress.
If no settings configurations have yet been saved when the Output Control panel is
first opened and no parameters are changed, the Output Settings box displays
“Default.”
X

X

When output settings are saved, the Output Settings box displays the name of the last
selected setting. Use Organize List to change the display order of the menu, rename,
or delete items (see page 214).
When a saved setting is selected from the pull-down menu, the Output Control panel
and all Preferences dialog options will be updated.
X

X

For Reference Channel—Low Voltage Stimulator; Human Stimulator; Visual Stim
Controllable LED (OUT4) and Pulse Sequence only. All Output Settings must use
the same reference channel assignment; other parameters can be unique for each
setting.

Once configured, Preferences may be saved using the Save Settings button at the
bottom of the Preferences dialog. Save Settings generates a dialog to name and save
a defined configuration of Stimulator output settings. Saved configurations are
accessible via the Output Settings pull-down menu in the Output Control panel.
When a setting is selected from the menu, all current output parameters are updated
to reflect the saved settings.
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OUTPUT CONTROL PANELS
Multiple configurations can be saved as long as each has a unique name; the Save
button will be inactive if the entered name is not unique.
Settings can be saved locally (to a specific file) or globally. The data file or template
file holds the output parameters as established when the file was saved plus any other
named configurations of Output Settings.

Use the Organize List button at the bottom of the Preferences dialog to order,
rename or delete saved Preferences settings. The up or down arrows are only
available if two or more settings have been saved. Select a setting and then click the
up and down arrows to set the position, or choose rename or delete. Selecting
“Delete All,” removes all saved settings will be deleted and the default options will
be reactivated.
General Tab
The General tab is
available when using
Pulses, Low Voltage
Stimulator,
Stimulator-BSLSTM
and Human
StimulatorSTMHUM.

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Number of Pulses

215

Indicates the number of pulses to be output. When the Output Control panel is
closed, the pulse output will be immediately stopped.
Single will establish a single pulse for outputting. All pulse repetition options, entry
boxes and scroll bars in both the control panel and preferences windows will be
disabled (grayed).
Multiple will establish a specific number of pulses for outputting. The selection
activates an box where 1-254 pulses can be entered. When this option is selected, the
Pulse Repetition scroll bar is activated in the Output Control panel.
Continuous will establish a continuous pulse train for outputting. When this option
is selected, the Pulse Repetition scroll bar is activated in the Output Control panel.
If “Initiate pulse sequence with ON/OFF button in Output control panel” is set, the
pulse sequence will be stopped prior to acquisition and will have to be manually
turned back on after the recording.

Initiate pulse
sequence with…
ON/OFF Button

OFF (red)

ON (green)

Controls the start and stop of pulses. Changes to Pulse Width and Repetition Rate
can be made in the Output Control panel entry boxes during a pulse sequence, and
during a recording, if all other Preferences parameters allow it. Any change in the
pulse output will occur immediately. This allows the stimulator output to be
changed “on the fly.”
When “Initiate pulse sequence with ON/OFF button” is selected:
The ON/OFF button controls pulse output independent of the acquisition status.
OFF is always available.
The ON/OFF button reflects the current output state, with one exception: if the pulse
sequence lasts less than 0.5 seconds, the button will remain in the “ON” state for at
least 0.5 seconds to indicate that the ON state occurred.
When the Number of Pulses selected is Multiple, ON/OFF acts as a momentary
switch. Press the ON (green) button to start pulses;
it will automatically turn OFF (red) at the end of the specified pulse train.

AUTOMATIC
START (yellow)

The switch defaults to OFF. Saving a data file or saving as a Graph Template will
save all stimulator preferences except the status of the pulse switch, which will
always be saved in the OFF position.

Recording

When “Initiate pulse sequence with Recording” is selected:
If the preference setting “Initiate pulse sequence with: ON/OFF button” is active, the
control panel changes will take effect immediately. If settings are changed during a
pulse train, changes do not take effect until the next time the stimulator starts.
Pulse output turns ON and OFF corresponding to the Start and Stop of the recording.

Start button

Stop button

When in this mode, and not recording, the ON button will display as yellow,
indicating that pulse output will automatically begin at the “Start” of the recording.
Pulse outputting can be turned OFF during a recording, but it cannot be turned back
ON until the end of the recording.
When a Repeat sequence is running, pressing the OFF button will turn OFF the
output for the entire recording sequence and the button will display as OFF until after
the last sequence, when the switch will display as yellow ON (automatic start)
indicating that pulse output will begin again at the “Start” of the next recording
sequence. It is not possible to turn pulse outputting back ON during a repeated
recording sequence.

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When the acquisition stops, all stimulator pulses will cease, regardless of the Output
Control panel settings.
The pulse output will stop concurrent with the end of the acquisition, even if the
specified pulse output is not completed before the acquisition ends. When a new
acquisition is started, the pulse output will start from the beginning.
In this mode, no changes can be made in the Output Control panel until the recording
stops. Changes made after recording stops will take effect when a new recording is
started.
When a pulse is sent out, the event label and indicator arrow will be generated (if the
event preference is turned ON and events are displayed).
After initial delay
(Applicable to Pulses,
Stimulator BSLSTM, Low
Voltage Stimulator
and Human
StimulatorSTMHUM only)

After initial delay of … is enabled only when “Initiate pulse sequence with
Recording” is chosen. Specify a delay interval from the start of recording to the start
of the first pulse. This is useful for viewing data prior to the stimulus pulse. The
BIOPAC output device determines the delay range.
INITIAL PULSE DELAY MP36R or BSLSTM
Range 0 - 100 milliseconds
Resolution

0 or .5 - 100 milliseconds*

10 microseconds

1.953 microseconds

*Entries greater than 0 milliseconds must be at least 0.5 milliseconds.
Pulse Events

An advantage of using the AcqKnowledge software for output signals is that
information regarding the pulse is automatically recorded along with the data. The
amplitude reflects the output pulse level.
§

Events can be automatically inserted and labeled for each Reference pulse or
change in pulse train. The label will contain the Pulse width and Pulse rate (and
system time stamp if selected).

§

Events reflect setting changes made during an acquisition.

§

All output pulse information is automatically recorded and archived with the
saved data.

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Set the event option by clicking in the box to “Create event when output is changed.”
Set the “Include time/date” option in the global Preferences (MP36R > Set Up Data
Acquisition > Event Marking)

The event label accurately captures pulse data, but the event arrow may not always
line up exactly with the leading edge of the pulse; this typically is not a problem
because the recording will include the actual stimulus pulse which can be used for
timing measurements. Depending on the acquisition Sample Rate, the leading edge
of the pulse in the recording may not correspond to the exact time the pulse was
sent—it may be off by as much as one sample period. If the event precision is critical
for the recording, increase the Sample Rate.
To display events, use the toolbar icon or Display > Show > Events.
The Range switch on the front of the BSLSTM stimulator should be set to 10 V or
100 V prior to recording and should not be changed during recording; if using a
Preset, the corresponding Preset should also be selected prior to recording. The pulse
level can then be determined by moving the decimal to the right or left depending on
how the range was switched.

ADVANCED TAB (OUTPUT PREFERENCES)
Advanced Tab
(Applicable only to
Pulses, Stimulator BSLSTM, Low
Voltage Stimulator
and Human
StimulatorSTMHUM)

Pulse Width

Indicates the Pulse Width setting, which determines the maximum Pulse Rate
frequency. The Pulse Width value is limited by the Preference setting.
The entry is activated when the value is changed and the Tab or Enter key is pressed;
it does not require a stimulator restart to take effect.
The Pulse width entry overrides other entries as required.
An entry may be automatically changed if any of the following conditions apply, in
which case the closest possible value will be selected:
It falls outside the allowable range.
It is rounded to .01 millisecond increments (MP36R resolution).
Width has been limited by the Pulse Width: Limit Entry settings of Preferences.
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Allow any entry

Pulse width is limited to the output capabilities of the BIOPAC MP36R unit. This
option allows any entry within the allowable range specified below:
PULSE WIDTH RANGE MP36R hardware
Range

Lock entry to
Pulse Repetition

.050 – 100 milliseconds

Resolution
10 microseconds
This entry locks the width to a single, specified value (within the allowable range). No
other value can be entered.
Indicates the Pulse Repetition period (Hz or ms).
The Pulse period must be greater than the Pulse width. See “TBPMIN” in the
Output Preference > Advanced Tab Limits table on the next page.
The full range of acceptable Pulse Rate values is from .2 to 6,667 Hz (MP36R).
The maximum Pulse rate (PRPMAX) depends on the Pulse width setting:
Pulse width 100 ms à maximum Pulse rate = 9 Hz
Pulse width .020 ms à maximum Pulse rate = 3333 Hz
The formula for pulse width vs. pulse repetition is PRPMIN = PW + TBPMIN
Where: PRPMIN = the MINimum Pulse Repetition Period allowed.
PW = Pulse Width setting
TBPMIN = MINinum Time (in ms) between successive pulses
for the output device (see device specifications)
If “Limit changes from ___ to ____” is selected in Advanced preferences, then
PRPMAX will be determined by the formula above or the specified limit, whichever
is greater.
An entry may be automatically changed:
· If it falls outside the allowable range.
· To round it to .01 Hz increments (resolution of system).
· To make it at least 0.1 millisecond greater than the Pulse width.
· By the Pulse Repetition Rate: Limit entry Preference.
· By the Pulse Repetition: Adjust entry increments Preference.
Any pulse width value can be manually entered, but when using the scroll bar or
arrows, entries will be constrained by the “Adjust entry increments” Preference
setting.

Pulse Repetition
Scroll Bar

The Pulse Repetition Scroll Bar adjusts rate or period by the increment of change and
limits established in Preferences. With each click of the scroll bar arrows, the rate will
be increase by the specified increment.
When “Initiate pulse sequence with ON/OFF button in Control Panel” is selected,
changes take effect upon release of the scroll box as long as the stimulator is running.
The scroll bar is disabled when Number of Pulses is set to “Single” or Pulse
Repetition is set to Lock Entry to...”

Display as

Pulse repetition can be displayed as
Pulse Rate (expressed in Hz), or
Pulse Period (inverse of Pulse Rate, expressed in milliseconds).
Pulse Repetition Rate relates to the Pulse Repetition Period as:
Pulse Rate (Hz) = 1000 / Pulse Period (milliseconds)

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The “Display as” units selection is also used for:
Pulse repetition entries in the control panel.
Scroll bar increments.
The Pulse Repetition Rate: Limit entry Preference.
The Pulse Repetition: Lock entry Preference.
The Pulse Repetition: Adjust entry increments Preference.
When units are changed from Rate in Hertz (Hz) or Period in milliseconds (ms), the limits
of the Pulse Repetition range will be converted by the formula:
Period increment in ms = Round to nearest whole number [Period Range * (Rate
increment in Hz /Rate Range in Hz)]

For example, if the Range was 1Hz to 10 Hz with an adjustment increment of 1Hz,
the proportional calculation would be Period increment = 900 ms (1Hz / 9 Hz) = 100
ms
Allow any entry

Pulse width is limited to support the output capabilities of the BIOPAC output device.
See Output Preference > Advanced Tab Limits table for allowable range.

Limit entry

Establishes minimum and maximum values that can be manually entered or changed
with the scroll bar.

Lock entry

Locks the Repetition to a single, specified value (within the allowable range). No
other value can be entered in the control panel.

Adjust entry

Controls the scroll bar or scroll arrow increment; does not apply to manual entry.

Advanced Tab Limits

Pulses

BSLSTM

Pulse width
Range (ms):

.050 – 100

.049 – 100

.050 – 100

.049 – 100

Resolution (ms):

.010

.001953

.010

.001953

Rate range (Hz):

.2 – 16,667

.2 – 10,204

.2 - 2,000

.2 – 2,004

Period range (ms):

.060 – 5,000

.098 - 5,000

.500 – 5,000

.499 – 5,000

TBPMIN Minimum time
between Pulses (ms):

.010

.049

.450

.450

Resolution (ms):

.010

.001953

.010

.001953

Time range (ms):

0 – 100

0 or .5 - 100

0 – 100

0 or .5 - 100

Resolution (ms):

.010

.001953

.010

.001953

Pulse Repetition

Initial Pulse Delay

LEVEL TAB (OUTPUT PREFERENCES)
About Level

Low Voltage Stimulator and Human Stimulator-STMHUM allows the software to
specify the pulse amplitude. The amplitude can be set to any value within the
limits of the stimulator; the range is -10 to +10 Volts for the Low Voltage
Stimulator and 0-+100 V for the Human Stimulator-STMHUM
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Pulse Level
Low Voltage only

The Level entry box allows the user to
manually enter any value within the limits
of the system or within the limits of the
Preference settings from the Level tab.
The Level entry box will be inactive
(grayed) if:
The Level preference “Lock entry to” is
active.
If “Initiate pulse sequence with Recording” is active (from the General tab) and a
pulse sequence is in progress or “wait for trigger” is in progress.
Use the entry box or the scroll bar to set the Pulse level. When a value is entered
which is out of range, the value will be rounded to the closest value obtainable
after the “Enter” or “Tab” key is pressed.
If “Initiate pulse sequence with ON/OFF button in control panel” is active (from
the General tab), then values entered during a pulse sequence will take place
immediately.
If “Initiate pulse sequence with Recording” is active (from the General tab), any
entry made between acquisitions will take place on the next “Start” of acquisition.

Allow any entry

The level is limited to the output capabilities of the stimulator. This option allows
any entry within that range.

Limit entry

This entry reduces the range within the limits of the stimulator’s output
capabilities.

Lock entry

This entry locks the level to a single specified value.

Adjust entry

This setting affects the scroll bar or scroll arrow increment only; it does not apply
to manual entry.
The smallest increment is 5 mV, as limited by the MP36R. The specified
increment is used to round manual entries to the closest obtainable value.

REFERENCE CHANNEL TAB (OUTPUT PREFERENCES)
Reference Channel

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This option allows monitoring of the output signal on one of the analog or digital
input channels without making any physical connections. This is an internal,
hardware/firmware, feature that recreates the output signal and allows recording
in “real time.” The assigned reference channel will override any “real” input
signal.
The reference signal is not the real signal, but is a very accurate “estimate” of the
real signal. The pulse timing accuracy will be within 100 microseconds. If an
analog input channel is used as the reference channel, the pulse level will be
accurate within 5%. If the stimulation encounters a load that reduces or distorts
the pulse output, the reference signal will not reflect this amplitude distortion.
If a digital input channel is used as the reference channel, only a digital
representation of the pulse will be generated; 0 to 5 volts.
Channel Assignment

Use the pull-down menu to choose which analog or digital input channel will be
used as the output reference channel.
When a new reference channel is assigned, a warning will be displayed indicating
this setting will overwrite the existing Channel Setup parameters for the selected
channel.

For example, if CH1 is set up for ECG data and then selected as the Reference
Channel, the ECG parameters will be replaced. If another channel is then selected,
CH1 will be reestablished with the default analog input parameters, and the ECG
settings would need to be recreated via presets or manual entry.
The reference Channel label should read: “(Selected Output) - Reference Out.”
When an Analog Input Channel is assigned as the Reference channel, that channel
(as viewed from MP36R > Set Up Data Acquisition > Channels) will be in a
locked mode and the Preset pull-down menu will be disabled. The assigned
reference channel will be inactive for “real” inputs until the Reference Channel
Preference is changed to “None” or another channel.
Once the control panel with an assigned Reference channel is closed, the data
Acquisition Settings > Channels will automatically update to the default settings.
Generate using

Specifies how the Reference signal should be shown.
If using analog input from CH1 - CH4, the selectable options are actual or fixed
(max) amplitude and actual pulse or fixed pulse width. Fixed pulse widths are
useful when the pulse width is much smaller than the sample interval (1/sample
rate) is used.
For example, Frog muscle stimulation uses a 1 ms pulse width and a sample rate
of 2000 samples/second to capture the muscle response. At this sample rate, the
stimulus pulse cannot be reliably recorded. By using the fixed width of 15 ms, the
pulse should be recorded.
If using digital input from D1 - D8, select actual or fixed (15ms) pulse width.

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Usage Guidelines & Setup Summary for BSLSTM Output Control
HUMAN SUBJECT SAFETY
· Before using the stimulator on human subjects, it is very important to limit the
energy the stimulator outputs. For optimal safety:
· Before powering on the BSLSTM stimulator, set the voltage level to zero by
rotating the LEVEL knob on the front of the BSLSTM fully counterclockwise.
· Use BIOPAC HSTM Series Probes. These probes MUST be used in order to
limit the energy the stimulator can output.
· Never create an electrical path across the heart.
· Never use on subjects with pacemakers.
· Read this manual and the BSL Hardware Guide to become familiar with
Stimulator operation.
1. Connect the BSLSTM Stimulator to the MP36R and power on both units. (For instructions on how to
connect the BSLSTM to the MP36R Acquisition Unit, refer to the BSL or MP Hardware Guides.)
2. Connect the Stimulator Trigger cable to the Analog Out port of the back of the MP36R hardware.
3. Connect the Stimulator Reference Output cable to an Input Channel on the front of the MP36R
hardware. This channel will be set up in Step 8 below as the Stimulator Reference Channel.
4. The Reference pulse has a fixed Pulse width of 15 milliseconds, so chosen so that the Sample Rate of
the recording may be as low as 100 samples/second and still capture the Reference pulse.
5. Before powering on the BSLSTM stimulator, set the voltage level to zero by rotating the LEVEL knob
on the front of the BSLSTM counterclockwise all the way to the left.
6. Open a new data acquisition graph.
7. Confirm that Events are activated. Events are activated by default. If not activated for a given
recording, choose Display > Show > Events.
8. Set up the Stimulator Reference Channel. This is the Analog Input Channel on the front of the
MP36R that receives the Stimulator Reference Output cable from the back of the BSLSTM. Remember,
the reference channel is generated from the stimulator and not the software.
9. Choose MP36R > Set Up Data Acquisition > Channels. This will generate a Set up Channels dialog.
10. Select the Acquire, Plot and Enable options for the analog channel to use as the Stimulator Reference
Channel.
11. Click Presets and scroll to select “Stimulator (0-10V)” or “Stimulator (0-100V)” to match the Range
switch setting on front of the BSLSTM.
12. Click Setup to view or change the analog channel parameters. Review the BSLSTM Stimulator section
(page 201) and Analog Channel Setup section (page 119) before modifying channel/preset parameters.
13. Set the Gain and other input parameters as desired.
14. Click OK to accept the parameters.
15. Close the Set up Channels window.
16. Adjust the voltage output of the stimulator by using the Level control on the front of the BSLSTM.
17. Rotate the Level knob clockwise to increase and counterclockwise to decrease, reading the voltage in
the BSLSTM’s digital display.

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Stimulator Safety Features
The stimulator cannot operate unless its Output Control panel is open.
The Pulse ON/OFF Switch on the Stimulator Output Control panel must be OFF in order to open and configure
Stimulator Preferences.
If the Stimulator Output Control panel (or the AcqKnowledge application) is closed in the middle of a pulse
train while the stimulator is running, the stimulator will shut down and the pulses will stop.
If another data acquisition window is activated, the stimulator will stop and remain OFF unless restarted using
the parameters associated with the new data window. The only exception is that if the stimulator is ON and the
data window corresponding to current stimulator parameters is acquiring data, then the stimulator will continue
to run until the end of the acquisition.

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Chapter 11

Set Up Event Marking

Events (Markers)

Event Toolbar

Event Insertion

Event Control

X

Event (Marker) Overview
For detailed analysis, it can be useful for waveforms to have extra information associated with them. This
information might include waveform boundaries from ECG analyzers, spike classifications from a spike sorter,
heartbeat classifications, or even detailed user notes. AcqKnowledge 4 uses “event” functionality to store and
manage this information.
An event is a piece of information associated with a specific time in a waveform. An event can capture points of
interest within a file (i.e. subject moved, dose added) or on a particular channel (i.e. T-wave onset). Once events
are marked in the file, AcqKnowledge can use the event information for analysis, including measurement (page
240) and cycle detection (page 341).
§ An event has the following pieces of information associated with it:
o Event type
o Sample location: the time position in hardware samples where the event is defined.
o Channel: the channel for which the event is relevant.
o Some events, such as the time of the start of an appended segment, may be relevant to all of the
channels of a graph—these are “Global” events.
o Label: a string of text that can be entered either automatically or by the user to provide more
information about an event. Labels can be fixed or sequential in order.
§ Different event types can be entered automatically or manually. These different event types allow
events to be filtered and also support analysis routines that key off of these events.
o Event insertion tool
o Set up Event Marking (see page 227) to manually insert events during acquisitions
o Copy/paste measurements and Copy/paste wave data operations can insert events at the
selection boundaries; choose “Mark with events” under Preferences (see page 225)
o Cycle Detector Output Events option (see page 341)
o Contextual menu in Event region
X

X

X

X27

X

X

o

X

X

Specialized Analysis (see page 365) to automatically insert events according to complex
analysis algorithms

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Event Toolbar
The event toolbar displays the visible events in the graph and provides a quick editing area for event
descriptions. The right button toggles visibility of the Event Palette for detailed control (see page 228). The
palette will “refresh” when events change the event configuration, such as horizontal scrolling, scale changes,
changes in the selected event via clicking in the graph window, editing of the event label by using the event bar,
transformations that define new events for the graph, waveform editing operations, and additions of new events
by clicking the event bar at the top of the graph window. The right/left arrow buttons are for navigating through
events. If events are placed in the waveform, the arrow navigation will locate events in the selected channel
only.
X

X

Event Tooltips
If events are being displayed within the plotting area and tooltips are enabled, a tooltip will be associated with
every event in the plotting area. The tooltip includes the event type description, the user-defined label (if
present), the time location of the event, and the amplitude of the waveform at the event location. While this
information can be drawn directly on the graph, event tooltips assist in browsing event information when the
screen becomes too crowded and there is not enough room to display all of the times, amplitudes, and labels.
Event tooltips are displayed under the event icon.
§ If the event is being plotted directly on the waveform, this will be the point on the waveform associated
with the event.
§ If there is an indicator and the event icon is at the top of the indicator, the tooltip will be anchored at the
top of the indicator.
§ If the events are being plotted at the top of each track, the tooltip is anchored at the top of the plotting
area directly underneath the event icon.
Event tooltips will not be displayed if tooltips are disabled, if events are only being displayed in the events bar
at the top of the screen, if X/Y mode is in use, or if events are not currently visible.
Preferences for Events

Preferences > Event Summary and Waveform

Use the “Event Summary” section of the Preferences dialog to set options for pasting summaries of events into
the journal.
§ Group events
Sorted by type
sorted by event type descriptions first
Sorted by channel
grouped based upon where they are defined (Global events appear first, followed
by groups for each individual channel).

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Sort Grouped events
Sorted by time
sorted in order by increasing time
Sorted by label
sorted alphabetically by label
§ Include only events visible on the screen
Determine if the summary is generated for all of the events that are in a graph, or only for those events
that are currently visible on the screen. If there are thousands of events in a file, this feature allows the
list to be pared down to those of interest.
Event summary options will be saved with the graph if the graph has a graph journal, and can be pasted into the
journal using “Summary in Journal” Event Palette Actions command (see page 232).
Other event preferences are available under Preferences > Waveforms
X

·
·

X

Mark waveform edits with events
Mark selection with events in graph—enabling this preference automatically brackets the edges of
selected data areas with “selection begin” and “selection end” events when measurements or
waveform data are pasted to the Journal. (This option is also available under Preferences >
Measurements.)

“Selection Begin” and “Selection End” events

“Selection begin” and “selection end” events may also be applied manually by selecting an area of data
and choosing the “Mark Selection” button in the Selection Palette.
· Include time value— include the time value (relative to start = 0) for the paste.
· Include timestamp—Include time and date stamps for when the paste occurred; this timestamp will
match any timestamp pasted into the journal. When selected, any selection events added to the graph
will have their labels set to match the timestamp.
· Auto-paste results in independent journal (Preferences > Journal)—Selection events and time
stamp events can be automatically inserted to an independent Journal.
Combine these options to retain enough information to reproduce measurement results and correlate
measurement results with specific areas of the graph; this helps verify the accuracy of measurement results
made through manually constructed graph selections.
Any change to these settings will be retained within a saved graph file and will become the default for newly
constructed graphs.

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Event Marking Setup Options
Events of different types
can be inserted during
acquisition, regardless of
whether events are visible
in the graph. When a
hotkey is pressed during
acquisition, an event will
be inserted into the graph
at the end of the most
recently acquired data.
Each hotkey can have a
different configuration,
adjustable through a
dialog accessible via the
“Hardware > Set Up Data
Acquisition > Event
Marking...” menu item.

Hotkey
Action
Event type

Channel

Label

Assign Escape or F1 through F9. When a different hotkey is chosen, the other controls of the
dialog change to reflect the configuration of the new hotkey.
Choose whether the Hotkey assignment creates an event or a focus area.
Lists the standard hierarchical menu of available event types; Types are detailed on page 233.
Choosing a new type from the pull-down menu will change the type of event inserted when the
hotkey is pressed during acquisitions.
Contains a “Global” entry and all of the channels (analog, digital, or calculation) set to
“Acquire” in Set Up Channels.
§ “Global” will define global events drawn in the event bar above the graph data
§ Choosing a new channel from this menu will cause events to be inserted on the appropriate
channel of the graph when the hotkey is pressed.
Edit field for label text and toggle optional inclusion of time stamp and/or date stamp. Stamps
correspond to the time of the system clock when the key was pressed, that is, the time of the
event insertion in “real clock time.”
§ Fixed - Provides a fixed label from text entered into the label field to the right. This label is
used every time the assigned hotkey is pressed.
§ Sequential - Labels for events will iterate sequentially through the entries in the table index
when the assigned hotkey(s) is pressed. The area under ‘Label’ is editable for entering text.
X

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Additional Hotkey Setup Controls
Add
Rename
Delete
Delete All
Up
Down
Top
Bottom
Include time
Include date

Function
Adds an editable label field to the list.
Allows renaming of the existing segment label.
Deletes a selected custom label.
Deletes all custom labels.
Incrementally moves a selected label up the list.
Incrementally moves a label down the list.
Moves a selected label to the top of the list.
Moves a selected label to the bottom of the list.
Adds timestamp to labels when checked
Adds current date to labels when checked

Create/Toggle Focus Area Action
Selecting the ‘Create/Toggle Focus Area’ action presents a similar setup dialog, but dictates that hotkeys setups
will be assigned to defining Focus Areas instead of inserting events.

When this option is chosen, pressing an associated hotkey during a recording will initiate a focus area in the
graph. Toggling the same hotkey will conclude the focus area. The focus area will appear highlighted and
outlined in the graph following the second (termination) keystroke. As with events, multiple hotkeys and labels
can be assigned.
Example for setting up a Focus Area Hotkey:
1. Choose the desired hotkey from the Hotkey list.
2. Under Action, select ‘Create/toggle focus area.’
3. Assign the focus area a label by typing it into the ‘Base focus area label’ field.
4. If additional focus area hotkey assignments are desired, choose another hotkey
from the list, and repeat steps 2 and 3.
5. When focus area hotkey assignments are completed, click OK.
§ If the same hotkey combination is repeated to create subsequent focus areas, the base focus area
label will remain the same but with incrementing numbers appended to the title.
§ If a different hotkey combination is used for subsequent focus areas, unique base focus area names
will be used as assigned.
§ Starting a focus area assigned to one hotkey and then starting another focus area assigned to a
different hotkey will terminate the original focus area and start a new one.
§ Focus areas can be created and toggled while a recording is in progress.
§ Focus areas can be shown/hidden by choosing the Show/Hide toolbar
function (right) and checking or unchecking the “Focus Areas” option.

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Event Palette
The event palette is a floating window that
provides a quick summary of events for the
top most graph and can used to examine,
search, and modify events. Events can be
extracted in a time range for a specific
event type and specific channels.
There is only one visible event palette for
the entire application. The palette consists
of four sections: event list, selected event,
display, and event actions. Each section
can be shown or hidden by toggling the
disclosure button next to its title.
Ü Event List, see page 229.
Ü Selected event, see page 230.
Ü Display, see page 230
Ü Actions, see page 232.
o See the Event Journal
Summary enhancements.
X

X

X

X

X

X

X

Event List
The event list provides an expandable, scrollable,
hierarchical view of the events in the topmost graph.
Events are grouped by their channel on the top level.
The event list has three columns of information:
§ Events: the readable type for each event
§ Location (Time): the time location for each event
§ Label: the user defined description for the event.

Sort the contents in ascending or descending order on each column by clicking the column header. Events and
Description will sort in standard alphabetical order, Location will sort based on the horizontal axis location of
each event.
Select a single event from the event list by clicking on a single event. The event will be selected in the graph
window and made visible if it is not currently displayed.
List visible events only toggles the checkbox to switch between the two display modes.
§ When enabled, the event list will display only those events that are being displayed on the plotted portions
of the graph. As the user navigates through the graph with the scrollbars, horizontal scale, or other means of
changing the amount of visible data, the event list will continually refresh to contain the new set of visible
events.
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§

When disabled, the event list will display all of the events for the entire graph. This can allow for easier
navigation through graphs with hundreds of events, such as PhysioBank files.

Selected Event
Event type options are
detailed on page 233.
X

X

When a single event is selected, the type, channel (or “General” for global events), user-defined label, and
location of the event will be filled in and can be edited. The controls can display information about only one
event at a time; if no event is selected, the controls will be grayed out.
Event Location
“Location defines the position where the selected event occurs, relative to the first sample in the file. To change
the location of an event, change the position entered in the Location box. Precision matches the horizontal axis
setting.
Events (with the exception of Append events) may be repositioned if desired. Alt-click (Windows) or
Option+click (Mac) over the event icon and hold down the mouse button. Then simply drag the event to the
desired location on the event bar and release the mouse button.
Display

Event display location
Event display detail
Display controls determine the location and detail of events to be drawn in the frontmost graph.
Ü Location—Choose one of the five display methods (described on page 231).
Ü Detail—the three checkboxes to establish how much information to include with events.
Ü Indicator length—Set the slider to shorten or lengthen the indicator line. This option is only active if
the display mode is “On waveform, with indicator” or “At top, with indicator.”
Ü Font – Align – Selects font style and alignment of Event labels.
X

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Ü
Ü

231

Angle – Determines the angle in degrees that the Event text can be displayed in the graph. Value can
be positive or negative.
Set as Defaults – Saves any modified event palette settings as the default for newly inserted events and
subsequent graphs. Applying this option has no effect on previously existing events.

Location & Display

Description

In event bar

Event icons are displayed in the global events bar located on top of the plot area in the
graph window. This does not allow for distinguishing what channel a specific event
belongs to.
§ To select the event, click the icon in the events bar.

On waveform

Event icons are displayed above or below the actual sample in the source channel
corresponding to the location of the event.
§ To select the event, click the event icon on top of the waveform.

Top of plot

Event icons are displayed at the top of the channel track, either on top of the grid or in
a channel-specific events bar.
§ To select the event, click the icon at the top of the channel track.

On waveform, with
indicators

Event icons are displayed above the data with a vertical line of configurable length
running through the data sample of the source channel at the event’s location.
§ To select the event, click the event icon or the indicator line.

Top of plot, with
indicators

Event icons are displayed at the top of the channel track with a vertical line of
configurable length running through the data sample of the source channel at the
event’s location.
§ To select the event, click the event icon or the indicator line.

Detail

When an event is being plotted within a graph, either on the top of a channel or
floating above the data, the event's location, description, and amplitude of the
waveform at that location can optionally be displayed along with the event icon.
Plotting of additional information can be used for graphical annotations on the data
and for clarifying event location for hardcopy or presentation.

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Actions

Actions Button

Description

Find

It is easy to create many more events then one can easily scroll through and locate
in a list. Find controls the automatic location of events based on established search
criteria.
Click the Find button to generate the Event search criteria dialog, and then
combine or restrict information to define desired events: event type, specific
channel location, or label search.
Click “Find First” to search for the first event in the graph that matches the
criteria. If found, the event will be selected and made visible in the graph window.

Find Next

Finds the next single event that matches the established search criteria until no
remaining events match the search criteria.

Cut Selected Event

Active only when an event is selected, removes the selected event from the graph.

Clear
Clear all

Generates a search criteria dialog (similar to the Find dialog) and removes all
matching events from the graph. There is also an option to clear events defined
within a focus area without affecting the remaining events, or to clear events
defined outside of a focus area while leaving events within the focus area intact.

Summarize in
Journal

Displays a dialog with controls that affect which events are included in the
summary.
Events can be filtered by visibility on the screen. Creates a textual summary of all
of the events in the journal.
§ See “Event Preferences” on page 225 for more information about
modifications to the traditional events summary.
X

X

Event Journal Summary Enhancements

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Events to be included in the summary can be filtered using the same criteria as
Find... in the Event Palette. By adding the ability to summarize only events
matching specific criteria, textual reports of arrhythmias or other infrequently
occurring events of interest can be generated with ease. Events defined within or
outside of focus areas can also be included or excluded from the summary.
When “Summarize in Journal” is clicked on the event palette, a dialog will be
displayed with controls that affect which events are included in the summary.
If there is no journal for the current graph, the following prompt will appear.

Mark Selection

Defines two new Global events in the graph at the precise time locations of the
currently selected area (the highlighted wave data section). If there is no selection
in the graph, this button has no effect. The events that are inserted will have the
“Selection Begin” and “Selection End” event types.

Restore from
Snapshot

Enables deleted events to
be restored from events
present in a Data Snapshot.
This option becomes active
only if a Data Snapshot of
the main graph is
displayed. The following
prompt will be displayed
when Restore from
Snapshot is selected. For information on Data Snapshots, see page 51.

Audio

This option allows audio (such as verbal observations) to be recorded and
linked to selected events in the event list. The controls are very simple to
use, and the audio is recorded via computer microphone or selected audio
capture device.
To set up a recording, select an event in the Event list and click “Record.”
This opens the “Record Audio” setup dialog (see right).
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Record Audio
buttons

Description

Input device:

Select the onboard audio capture device to be used for the recording. Use the default or
select another from the list of supported devices.

Record

Click to start the recording.

Stop

Click to end the recording.

Preview

Listen to the recording before linking it to an event. If recording is acceptable, click OK. To
repeat recording, click Record again.

Once a recording is accepted, it can be played back by clicking “Play” in the Audio controls or by selecting the
audio-linked event in the Event list. Selecting the linked event in the graph’s event bar will also play the
recording. Recordings can be erased by clicking the “Remove” button. One a recording is removed, it cannot be
recalled.

Event Type Options
Event Types are pre-defined options for assigning event information. The Event Type is for marking purposes
only and does not imply any analysis has or will occur for the event (unless Specialized Analysis was
performed, see page 365).
Once Event Types are defined, some analysis functions can be automated, including measurement (page 240)
and cycle detection (page 341).
X

X

X

X

X

X

Event classifications:

Event classifications group similar event types together into a logical
category. Event classifications present event types in a hierarchical
fashion and allow other event classifications to be contained within
them.
For example, the “Hemodynamic” event classification includes a
“Beats” sub-class with pre-ventricular contraction and escape beat
event types.

Event type

Classification

Global

This is the same as ‘untyped’ markers from AcqKnowledge 3.6 or earlier.

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Unrecognized event types will be classified as global events.
Append

Automatically inserted by the program on append operations. Custom Append
labels can be created in Hardware > Set Up Segment Labels. (See page 250.)

Notes

Annotation event to add notes on the data.

User-defined

Hotkey insertion for user-specific events; 9 types can be inserted via the
keyboard during acquisition.

Pharmacology

Basic pharmacological events: baseline, washing, and dosing.

Waveform Edits

Automatically inserted by the program on cut or paste operations in a graph file.
The description consists of the edit operation performed and a timestamp.
Insertion of waveform edit events is off by default, but can be turned on for GLP
purposes.

Selections

Used to mark boundaries of selected areas.

Classification

Pre-defined Event Type Options

Default

“Esc” key inserts global event.

General

Waveform onset or end
Change in signal quality or rhythm
Recovery

Maximum and minimum
Reset
Append

Hemodynamic
> Beats

Normal
Paced
Fusion of paced and normal
contraction
Unclassifiable
contraction
Left bundle branch block
Right bundle branch block
Bundle branch block
Atrial premature
Aberrated atrial premature

Nodal premature
Supraventricular premature
Premature ventricular
R-on-T premature ventricular
Fusion of ventricular and normal
Atrial escape
Nodal escape
Supraventricular escape
Ventricular escape

Hemodynamic
> Blood Pressure

Systole
Diastole

End Systolic pressure
End Diastolic pressure

Hemodynamic
> ECG Complexes

QRS onset, peak, and end
T-wave onset, peak, and end
P-wave onset, peak, and end
Q-wave peak
S-wave peak

U-wave peak
PQ junction
J-point
ST segment change
T-wave change

Hemodynamic
> Impedance

A-point
B-point
C-point

O-point
X-point
Y-point

Hemodynamic
> Monophasic AP

Plateau

Upstroke

Hemodynamic
> Other

Start of ventricular flutter
Ventricular flutter wave
End of ventricular flutter

Pacemaker artifact
Isolated QRS-like artifact
Non-conducted P wave

Notes

Arrow—short, medium, or long
Flag

Star

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Pharmacology

Baseline
Dose

Wash

Neurophysiology

Spike Episode Begin

Spike Episode End

Respiration

Inspire Start
Apnea Start

Inspire End

Stim/Response

Stimulus Delivery

Response

EDA

Skin Conductance Response

Specific SCR

Clustering

Cluster 1-9
End Cluster
Training Set

Cluster n
Outlier

User-defined

User Type 1-9

Classification

Pre-defined Event Type Options

Waveform Edits

Cut
Paste begin

Paste end

Selections

Selection begin

Selection end

B-Alert

Start of Eye Blink Artifact
Start of Excursion Artifact
Start of Saturation Artifact
Start of Spike Artifact
Start of EMG Artifact
Workload – EMG Start
Workload – Invalid PSD Start
Dummy Data Start
Misaligned Data

End of Eye Blink Artifact
End of Excursion Artifact
End of Saturation Artifact
End of Spike Artifact
End of EMG Artifact
Workload – EMG End
Workload – Invalid PSD End
Dummy Data End

BioHarness

Button Pressed

SMI Import

Left eye hit object
Right eye hit object
SMI stimulus image has been presented to the subject

Mobita

Start out of range

End out of range

Sleep Scoring

Wake Onset
REM Onset
Sleep Stage 1 Onset
Sleep Stage 2 Onset
Sleep Stage 3 Onset
Sleep Stage 4 Onset
Unscored Onset
Sleep Spindle Onset

Wake End
REM End
Sleep Stage 1 End
Sleep Stage 2 End
Sleep Stage 3 End
Sleep Stage 4 Ebd
Unscored End
Sleep Spindle End

Event Measurements
Measurements are a quick way to extract information from a graph. Three measurements extract information
from events. When combined with the Cycle/Peak Detector (page 341), they are also powerful data reduction
tools. These event measurements can provide quick summaries of event information, compute mean intervals
between event types, and detail other operations.
§ evt_ampl Event Amplitude Measurement (see below)
§ evt_count Event Count Measurement (see page 237)
§ evt_loc
Event Location Measurement (see page 238)
X

X

X

X

X

X

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Event Amplitude Measurement
evt_amp – Extracts measurement results where events are
defined. Note that the amplitude is always taken from the
measurement channel, which may be different from the
channel on which the events are defined. Useful for
extracting information such as the average T wave height
within the selected interval. The measurement result is
displayed without units (matching Value and other
amplitude events).
Select Event Amplitude or click the measurement info
button to generate the settings dialog.
Event Type
Location

Determines the type of events that will be processed; Types are detailed on page 233.
Determines where the processed events need to be defined. The menu options are:
§ Measurement channel only—Only extracts amplitude values for events that are defined on
the channel specified in the measurement channel pull-down menu. Global events and other
channel events are not included.
§ Global events only—Only extracts amplitude values for events that are defined as global
events appearing in the events bar; changing the measurement channel will not affect the
measurement result. Channel events are not included.
§ Anywhere—Extracts amplitude values for events defined on any channel and also global
events; changing the measurement channel will not affect the result
Extract
Determines what processing will be performed on the amplitude values extracted from events that
match the Type and Location settings. The processing options are:
§ Amplitude at first event only—The value of the measurement channel at the time of the first
matching event in the selected area.
§ Amplitude at last event only—The value of the measurement channel at the time of the final
matching event in the selected area.
§ Sum of amplitudes at all events—Computes the sum of the value of the measurement channel
from each matching event within the selected area.
§ Mean amplitude from all events—Computes the average amplitude value of the measurement
channel from all of the event locations within the selected area.
§ Minimum amplitude from all event —Computes the minimum amplitude value of the
measurement channel from all of the event locations within the selected area.
§ Maximum amplitude from all events—Computes the maximum amplitude value of the
measurement channel from all of the event locations within the selected area.
§ Median value of amplitude from all events—Computes the median of the set of measurement
channel amplitudes at all events.
§ Peak to peak interval of the set of amplitudes from all events—Takes the peak-to-peak
difference from the set of measurement amplitudes at all events (max - min).
§ Standard deviation of amplitudes from all events—Computes the standard deviation of the set
of measurement channel amplitudes at all events.
If there are no matching events of the selected type in the selection, the measurement result will be zero.
Event Count Measurement
X

X

evt_count – evaluates the number of events within the
selected area. The measurement result is unitless.
Select Event Count or click the measurement info button to
generate the settings dialog.
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Event Type
Location

Determines the type of events that will be counted; Types are detailed on page 233.
Determines where the counted events need to be defined: the pull-down menu options are:
§ Measurement channel only—Only includes events that are defined on the channel specified
in the measurement channel pull-down menu; global events and other channel events are not
included.
§ Global events only—Only includes events that are defined as global events appearing in the
events bar; channel events are not included. Changing the measurement channel will not
affect the measurement result.
§ Anywhere—Includes events defined on any channel and also global events. Changing the
measurement channel will not affect the measurement result.
If there are no matching events of the selected type in the selection, the measurement result will be zero.
X

X

Event Location Measurement
evt_loc – extracts information about the times of events.
The measurement result will take on the units of the
horizontal axis; if specific units were set for time or
frequency via Preferences, those units will be used.
Select Event Location or click the measurement info button
to generate the settings dialog.
Event Type
Location

Determines the type of events that will be processed; Types are detailed on page 233.
Determines where the processed events need to be defined. The menu options are:
§ Measurement channel only—Only extracts the time of events that are defined on the channel
specified in the measurement channel pull-down menu; global events and other channel
events are not included.
§ Global events only—Only extracts the time of events that are defined as global events
appearing in the events bar; channel events are not included. Changing the measurement
channel will not affect the measurement result.
§ Anywhere—Extracts the time of events defined on any channel and also global events.
Changing the measurement channel will not affect the measurement result
Extract
Determines what will be extracted from events that match the Type and Location settings:
§ First event location only—The measurement will equal the time at which the first matching
event in the selected area is defined.
§ Last event location only—The measurement will equal the time at which the final event
within the selected area is defined.
§ Sum of all event locations—The times at which all matching events are defined are added
together to produce the measurement result. This sum of times can be combined with Event
Count measurements to compute average intervals over the selected area.
If there are no matching events of the selected type in the selection, the measurement result will be zero.
X

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Printing Events
When a graph is printed and events are displayed onscreen for the graph, event icons will print as they are
displayed. Event icons will be scaled, depending on the printer's DPI, to be proportional to the vertical scale
plotted on the screen. If events are located at linearly interpolated positions, event icons will be dimmed on the
printout (see the Variable Sample Rate section).
Event display setting

Printed result

Global events

Global events are drawn above and outside of the data plotting rectangle in the
printout. If the event labels are close together, their alignment will be staggered to
show separate lines of label text.

In event bar

All events are drawn above the data area of the printout. Only labels may be drawn
with the events.

Top of plot or
Top of plot, with
indicator

Channel-specific events are drawn at the top edge of their channel’s track. No
indicator lines are drawn. Depending on the display settings of the graph, the event
label, amplitude of waveform at the event location, and Time of the event may be
printed below the event icon

On waveform or
On waveform, with
indicator

Channel-specific events are drawn immediately above the position of the
waveform sample at their location and will appear to be printed immediately above
the data of the waveform. No indicator lines are drawn. The vertical printing
position of an event icon will be identical for “On waveform” and “On waveform,
with indicator” displays. Depending on the display settings of the graph, the event
label, amplitude of the waveform at the event location, and time of the event may
be printed above the event icon.

“Draw vertical divider at event locations” option in the Print Setup dialog.
§ Enabled: draws a dashed vertical line at the precise time location of each event. Vertical divider lines for
the event type will extend
Global
Through all channels of data
In event bar
Through all channels of data
Top of plot
From the top to the bottom of the relevant channel track
On waveform
From the top to the bottom of the relevant channel track
§ Disabled: prints only the event icon, label, amplitude, and time. No indicator lines will be printed for the
event display. The vertical divider can be used in place of indicator line drawing.
Events and Waveform Editing
Waveform editing will adjust event locations for channel-specific events. Waveform editing will never alter the
time values for Global events (not associated with any specific channel, such as append events).
Copy When a portion of a waveform is copied the channel events will also be copied to the clipboard.
Cut
When a portion of a waveform is cut, events within that selected area will be removed and channel
events to the right of the removed area will be shifted to the left.
§ If waveform editing event insertion is active, a waveform edit event will be inserted at the location
of the edit operation indicating a “Cut” operation in its description.
Paste When the waveform is pasted from the clipboard, the channel events will appear at their same locations
and any channel events to the right of the end of the pasted segment will be shifted by the length of the
pasted segment.
§ If waveform event insertion is active, a waveform event marker will be inserted at the beginning
and at the end of the pasted segment.
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Constructing Graph Selections from Events
Graph selections can be defined from events (in addition to the I-beam tool).
1. Click the first event to select it.
2. Hold down the Control key (Windows) or Command key (Mac) and click the second event. A selected
area will be created in the data between the two events.
Event Plotting and Variable Sampling Rate
Event positions are defined in terms of the hardware sampling rate. The Variable Sampling Rate feature can
generate waveforms with a sampling rate lower than the hardware sampling rate. Through explicit event
definition, waveform downsampling, or other operations, events on a downsampled channel may not align with
an actual waveform sample, but rather occur at a hardware sample position in between the waveform samples.
These events will be drawn using linear interpolation when applicable, and only if the waveform is being drawn
in line plot mode. In step plot and dot plot modes, regular event drawing routines are used, with the vertical
position and amplitude of the nearest waveform sample to the event’s left.
When an event is to be drawn on an intermediate position on a waveform, the linearly interpolated value is
calculated for the hardware sample location. The interpolated value is derived from the closest waveform
sample to the left and to the right. The vertical position on the waveform of the event and indicator line will
match the vertical position of the linearly interpolated sample amplitude. This will place it immediately above
the line connecting the two waveform samples on screen.
If an event is being drawn using linear interpolation
§ Event icons will be dimmed, regardless of their display position (on waveform or top of the plot).
§ Indicator lines will be drawn on the waveform at a linearly interpolated position and the indicator line will
be a gray dashed line instead of a solid black line. (Indicator lines are never printed.)
§ Amplitude labels, if included with the event, will correspond to the linearly interpolated amplitude at the
event location and the linearly interpolated amplitude will be drawn in italicized text.
Watch the AcqKnowledge Event Marking tutorial video for a detailed explanation of this feature.

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Chapter 12

Other Hardware Menu Commands

This chapter covers the following MP hardware menu items not appearing in other chapters:
Show Input Values

Display channel data values in real time in a color bar graph format.

Show Manual Control (MP160/150
only)

Monitor and/or output pulses through the digital input/output.

Show Gauge

Displays onscreen blood pressure gauge or stopwatch.

MP160/150 Info

Displays configuration and firmware information for the MP160 or
MP150 hardware.

BioNomadix Logger options

Only applicable when BioNomadix Logger hardware is used. Contact
BIOPAC for information about the Logger.

Autoplot – Scrolling – Sweep – Warn
on Overwrite options

Data display options during acquisition.

Organize Channel Presets

Rename, delete, reorder or configure channel presets.

Set Up Linked Acquisitions

Record data simultaneously from multiple hardware devices.

Manage Hardware Connections

Connect, disconnect or switch supported hardware types.

Show Input Values

The Show Input Values option displays channel values in real time in an easy-to-read bar graph format. This
allows values to be displayed prior to or following an acquisition.
The Input Values display can be set to numeric, horizontal or vertical bar graph format, and can be resized and
moved to any position on the screen. To set the display mode, use the “Mode” menu generated via the
“Options” button.
Note The Input Values window only displays values for channels that were Set Up with the “Values” box
checked (see page 114 for more information).
X241

X

Hold

Regardless of the display options selected, the display can be “frozen” at any point in time by
clicking the Hold button. Clicking this icon will hold the values at their level(s) when the icon
was pressed. The window will remain frozen until the icon is clicked again. Once the values
are “unfrozen,” the values will return to the standard real time display mode.

Options

Mode controls the format of the values display.
·
·

Numeric Values—displays the voltages of the appropriate channels numerically.
Bars: Horizontal bars or Vertical bars—the range of values of the bar graphs
corresponds to the range for that channel in the graph window. To see the bar “bounce”
less for a particular channel in the graph window, increase the units per division.
· Font and Size determine text display from fonts installed on the computer.
Precision controls the total number of digits displayed.
Show controls the amount and type of information displayed regarding each channel. Click the
box next to each option to activate or deactivate it.
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· Channel Numbers will display the channel numbers (A1 for the first analog
channel, for example).
· Units will display the units for each channel (as indicated in the main graph
window).
· Labels will display the channel labels (ECG 1, Respiration, etc.) along with the
input values. This feature is especially useful when values from multiple
channels are being displayed simultaneously.
· Min/Max will display the range of values associated with the data. This range
corresponds to the upper and lower display limits for each channel as it appears
in the graph window.
· Values will display number values along with the horizontal or vertical bar chart.
Manual Control (MP160 and MP150 only)

STM100 option

The Manual Control dialog allows the monitoring and/or outputting of pulses through the digital input/output
(I/O) channels. The Manual Control is also used manually set the magnitude of the signal on either of the
analog output channels. The digital outputs in Manual Control cannot be used to trigger an online Averaging
acquisition.
Stimulator Usage Note
Use Manual Control to specify the stimulation output level
a. If the wide range of waveform output options available in the Stimulator Setup dialog cannot
match the desired specifications.
b. For pre-stimulation and post-stimulation.
See page 187 for important Analog Output details.
X

X

The 16 digital channels are sectioned off into two blocks, with the first block consisting of I/O channels 0
through 7, and the second block consists of I/O 8 through 15.
·

All the channels within a given block are programmed together and can be set as either inputs or
outputs.

·

The two blocks can be set independently.
o

For example, one block can be set to input data and the other to output data, or one block is
inactive and the other block reads or outputs data.
To read incoming values for a given block of digital channels, click the Input button below the row of channels
to have the input values displayed. This enables a block of digital channels to receive incoming data. To read
the values for the entire block simultaneously, click the Read button to the left of the channel boxes for that
block. Since these are digital channels, the values on the individual channel boxes will toggle between 0 and 1.

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When Read Continuously is enabled (below the Input button), the values will be read in real time. When
unchecked, the displayed values correspond to the values for that block of channels as of the last time the Read
button was depressed. This mode provides much the same information as the Show Input Values mode.
To output values for a given channel, the block containing that channel must first be enabled to output data. To
do this, click the bar below the channel boxes so the button reads “Output.” The individual channels within that
block can then be reprogrammed. These channels will toggle between 0 and 1, with a 0 corresponding to zero
Volts and a 1 corresponding to + 5 Volts. To output a digital 1 on I/O channel 3, the dialog would be setup as
shown above.
The function buttons toggle as follows:
Input toggles to Output
When Input is selected, the checkbox is “Read continuously.”
Set toggles to Read
When Output is selected, the checkbox is “Set immediately.”
To output a signal on Channel 3, click the Set button to the left of the channel box. If the Set immediately box is
checked, the signal will be output when the channel button is clicked.
IMPORTANT
Potential use conflicts can arise between the parameters set in the Manual Control window and
those set for digital channels in the Set Up Channels window.
STM100 option

STM100 option

When the STM100C stimulator module is connected to an MP160 or MP150 System, the output level can be
controlled via the STM100 option of the Manual Control dialog.
Attenuation
Attenuate the output signal by a given number of decibels (dB) for controlled stimulus
applications. To output a signal with no attenuation, simply set the “Stim 100 Attenuation“ to 0
dB.
Manually outputting a value on a digital channel can stop an acquisition if data is being
collected at very high speeds (greater than 10,000 samples per second aggregate).
Invert output Check this box to invert the polarity of the signal output through the STM100C.
This function can also be achieved by flipping the polarity switch on the STM100C from
positive (POS) to negative (NEG).
For more information on the STM100C stimulator output module, see the MP Hardware Guide.pdf.

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Set Up Linked Acquisitions
This hardware (MP or other) menu option allows acquisitions to be recorded simultaneously from multiple
hardware devices types into separate graphs. (For example, acquisitions can be simultaneously linked to two
MP160/MP150, two MP36R units or an MP160/MP150 and a B-Alert unit.) The linked acquisitions can
optionally be merged into a single graph for easy analysis.
In order to use linked acquisitions, a minimum of two graphs must be connected to different hardware units. If
two or more graphs are connected to the same hardware unit, linked acquisition sessions are not supported.
If multiple data acquisition devices are connected and global linked acquisition settings have not been set up in
AcqKnowledge Preferences, the following dialog will appear upon application launch:

Selecting “Use linked acquisitions whenever possible” will set a global preference to use linked acquisitions
whenever multiple hardware devices are detected, and offer additional preference settings. These settings can
also be reset or changed at any time in Display > Preferences > Hardware. (See page 247.)
Choosing “Cancel” will still allow the setup of linked acquisitions, but this operation must be performed
manually in AcqKnowledge.
Configuring New or Open Graphs for Linked Acquisitions
As stated above, Linked Acquisitions are supported only when two or more graphs are open, and only when two
or more hardware devices are connected. Linked acquisitions can also be configured while AcqKnowledge is
running, and graphs/devices added as desired.
· If multiple data acquisition devices are connected and powered on, these devices will be listed in a popup menu in the initial AcqKnowledge startup window.
· Choosing “All Devices” automatically creates a separate graph for each connected device. This acts as
a shortcut for setting up graphs for linked acquisitions.

Adding or changing hardware types with AcqKnowledge running: To add or change the hardware device
for graphs that are already open, click the “Connect to:” pop-up menu and select or add a new device from the
menu. (To be visible, the “Connect To” menu must be enabled via Display > Show > Hardware.)

The linked acquisition can output recorded data into the separate graphs, or optionally, merge the data into one
graph. If the latter option is chosen, data from the separate graphs will be contained in separate labeled channels
within the merged graph.

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To access Linked Acquisitions setup, select MP menu > Set Up Linked Acquisitions to open the following
window. Any open graphs are displayed in the “Acquire data into the following graphs” pane.

Top Column

Description

Graph Title

Displays the titles of the available graphs.

Acquire

Includes or excludes graphs from linked acquisition.

Hardware Status

Shows current status of hardware. (“No Acquisition” or “Acquiring Data.”)

Hardware Name

Identifies hardware device linked to graph.

Refresh button

Applies any settings that were changed (acquisition setup, etc.)

“The linked acquisitions session will be automatically stopped after:” This indicator displays the selected
length of the shortest-duration graph in the group. Multiple graphs set to different durations will default to the
length of shortest duration graph.
If the “Merge results into new graph at end of acquisition” option is checked, additional options become
available. Please refer to the table on the following page for details about these options.

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Functions

Description

Merge results into new graph at the end of
acquisition

Outputs data collected from multiple recordings into one
graph.

Resample merged data to: highest acquisition
sample rate (also available in the Hardware
Preferences)

The merged graph data is upsampled to the highest selected
sample rate among the linked graphs.(Example, if one graph
is being acquired at 500 s/s and the other 2000 s/s, the 500
s/s graph will be upsampled to 2000 s/s.)

Resample merged data to: lowest acquisition
sample rate (also available in the Hardware
Preferences)

The merged graph data is downsampled to the lowest
selected sample rate among the linked graphs. .(Example, if
one graph is being acquired at 500 s/s and the other 2000 s/s,
the 2000 s/s graph will be downsampled to 500 s/s.)

Synchronization method:

Offers various options for synchronizing the linked
acquisitions.

“Timestamp of first sample” – Compares all timestamps, detects the one with the latest time, and then cuts
the beginning section of the data in each channel.
“Master Synchronization Device” – Used for pairing and synchronizing data obtained during linked
MP160/150 and B-Alert acquisitions. This is the only option where the Master Sync Device radio button is
active. This option requires the use of a BIOPAC CBLX10 cable to link the MP160/150 hardware with the BAlert X10 headset. This cable allows for the injection of signals used to align data recordings between the two
independent units. (See the MP Hardware Guide for more details on the CBLX10.)
“Truncated” method – Searches for the shortest acquisition length and uses this parameter to calculate how
much data will be removed from the beginning of longer acquisitions. This is the least precise of the three
synchronization methods.
Start Acquisition button
Starts the recording for all selected graphs.

Graph Start/Stop button behavior: After linked acquisitions setup, Start/Stop buttons for all graphs display
an “(L)” to the right of the button. Linked graphs can be simultaneously started and stopped by toggling the
Start/Stop button of any graph. To Start/Stop linked graphs separately, hold down the Ctrl+Alt/Option keys
while clicking the button.

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Alternatively, the linked acquisitions setup dialog can be opened via the MP menu > Set Up Data Acquisition >
Length/Rate window. (Note the “Setup Linked Acquisitions” button in this window.)
Linked Acquisitions Preferences
Global preferences for linked acquisitions can be accessed and set up via Display > Preferences > Hardware.

Use linked acquisitions whenever possible: Use this option to automatically set up linked acquisitions if
multiple hardware and multiple graphs are detected.
Merge data automatically: Automatically merges data from multiple acquisitions into a single graph using the
Resample and Data alignment options selected in the Preferences.
If these preferences are not selected, linked acquisitions must be set up manually in the linked acquisitions
dialog (MP menu > Set Up Linked Acquisitions).
For complete Hardware Preferences information, see page 468.
Limitations on Linked Acquisitions synchronization methods
Synchronization Mode

Description

Criteria

Any method

Minimum number of selected
graphs

2

Minimum number of analog
channels

1

Minimum length of acquisition
when B-Alert device is used

12 sec.

Allowed hardware types

MP160/150 and B-Alert only

Minimum sample rate on first
channel of B-Alert hardware

256 s/s

Master Synchronization Device
method

Incompatible Acquisition Mode Warning
If an incompatible acquisition mode is used for any graph (such as append mode), the following dialog will
appear:

Choosing “Change Mode Now” reverts graphs to a compatible acquisition mode. Selecting “Cancel” will exit
the linked acquisition and leave acquisition modes unchanged.

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The sample rates can vary between the linked acquisition graphs, but all recordings are limited to Save Once to
Memory or Save Once to Disk mode. Append modes are not supported in linked acquisitions.
Linked Acquisitions and “Warn on Overwrite” dialog.
Compatible record modes for linked acquisitions are Save Once to Memory or Save Once to Disk. Rerunning
acquisitions in these modes normally results in a warning that data will be overwritten.
If data output is not being merged into one graph, the warning will be displayed. The warning can be suppressed
in this circumstance by deselecting the “Warn on Overwrite” option in the hardware menus. (MP36R or
MP160/150, etc.)

However, if the “Merge results into new graph” option is selected, the “Warn on Overwrite” dialog will not be
displayed.
Linked Acquisitions and wireless connections: In general, if the computer is trying to use multiple network
cards at the same time with an MP160/150, the MP160/150 either needs to be on the primary network, or
additional network cards must be disabled, or network bridging must be enabled in the Windows system
settings. When self assigning IP addresses, the MP160/150 may also choose a new IP address each time it is
power cycled, which will prompt for reconnection.
Watch the AcqKnowledge Linked Acquisitions video tutorial for a detailed explanation of this feature.

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Manage Hardware Connections
The Manage Hardware Connections option
enables easy connection and disconnection
of new hardware, and allows switching
from a particular hardware unit (or
hardware type) to another. It’s even possible
to have multiple AcqKnowledge graphs
running on different hardware types at the
same time. The following controls are
available:
Connect New Hardware
Choosing ‘Connect New Hardware’ opens a
popup menu for selecting and adding
additional hardware units. Once a new
hardware unit added, it will be available for
use in the application, and will appear in the
connected hardware list. (The example at
left shows the selection of additional MP
units on a local area network.)
The ‘Choose MP160/150’ pull-down menu
lists all MP160/150 units that are powered
ON and sitting on the same local area
network. The software pings the selected
MP160/150 unit and if available, the unit is
added to the list. If the unit is busy or
otherwise unavailable, a “Cannot connect to
MP160/150” prompt such as the example
below left is displayed.
Disconnect
Use to disconnect from any available
hardware in the list.
Playback from Graph
Launches the “Open for Playback” dialog.
For more information on Playback Mode,
see page 39.

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MP160 or MP150 Info
Select MP160/150 Info from the MP160/150 menu to generate a dialog with information about the software and
firmware versions being used by AcqKnowledge:

Note: For information about AcqKnowledge software, click Help > About AcqKnowledge.
Segment Labels
Selecting Set Up Segment Labels from Hardware > SetUp Data Acquisition > Segment Labels launches a setup
dialog enabling assignment of user-defined labels to append event segments. The Segment Label options are
applied to the active graph only. The selected settings will be saved with the graph, but will not be applied
globally to existing or subsequent graphs.

§
§
§
§
§
§

Add
Rename
Delete
Delete All
Top/Bottom
Up/Down

Adds a segment number to index. Segment text can be edited under ‘Label.’
Used to rename an existing segment label.
Deletes a selected segment from Index.
Deletes all segments from Index.
Moves selected segment to top or bottom of Index.
Incrementally moves a selected segment up or down the Index.

Enabling checkboxes below the

icons adds time/date stamps to the segment label.

Sound Feedback
Sound Feedback enables data to be redirected to the computer's default audio output in real time. This feature
can be used to monitor waveform data as sound through the computer speakers or headphones.

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CONTROLS

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FUNCTIONS

Sound enabled

Turns sound feedback of data on and off.

Output Sampling Rate

Selects from available sampling rates of the default audio device.

Source Channel

Selects the analog, digital or calculation channel from which the audio will be acquired.

Reset Adaptive Gain Control

Resets gain control to adapt to the current level of the signal. Use after sound feedback
has started to re-adjust the level after accidental spikes or large artifacts.

Enable low pass filter

Applies a low pass filter at the Nyquist frequency (50% of the acquisition sampling rate).
This IIR filter can help smooth out transition artifacts due to upsampling of data to the audio
sampling rate. (Enabled by default)

Median removal controls
(Window width, Recomputate)

Removes baseline offset from the output signal.

Window width

Sets width of median removal window (in seconds). Must be a positive value.

Recompute every

Provides the time duration (in seconds) after which the median of the data is regenerated
from the raw source data. Must be a positive value.

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Gauge

The Gauge is accessed
via Hardware > Show
Gauge. The optional
“Gauge” display shows
one channel of data in
a gauge/dial indicator
format.
The Gauge displays as
a separate window,
viewed simultaneously
with graph and other
windows.

The Gauge window:
·
·

Will display one channel of data: (analog or calculation)
Updates and displays simultaneously with the graph window. For analog channels only, the display will
update when the recording is stopped, but at a slower rate than when the recording is running.
· Can update during and in between acquisitions for all hardware devices; display may be updated at a
rate slower than the sample rate and may display a value that represents the average of several samples.
· The background image (BMP, JPG or TIFF), indicator origin, range, length, thickness and color are all
user-configurable. An optional range band overlay can also be enabled.
· Selectable gauge bitmaps include Blood Pressure Cuff, BPM or Stopwatch
· All window preferences as well as the window visibility, size and position will be saved with the file.
· Window sizing is “fixed” to the size of the background image, meaning it will have a 1 to 1
correspondence with the monitor pixels
Gauge Preferences
Gauge Preferences are accessed by right-clicking over the gauge and using the
contextual menu. There are four tabs for setting the various Gauge parameters.
Background is the default tab presented in Gauge Preferences and contains options for setting the Background
image.

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Channel

Provides a pop-up menu for assigning any one of the ENABLED analog or calculation
channels.

Background Image

Displays the path and file name of the current background image. The default image is a
blue blood pressure gauge sized at 451 x 451 pixels.

Browse

Allows alternative background images in different directories to be used in place of the
default gauges. The Browse location will default to the file path used by the currently
selected background image. To change the background image, click the “Browse” button
and locate the desired file. After the background image is specified, the pixel Width and
Height will be updated. The Width and Height fields are not editable.

Use Default

Displays a menu of available default background images. (Pressure, Stopwatch and
BPM).

Opacity

Changes the transparency of the gauge image.

Indicator
The “indicator” or “needle” is a simple line vector drawn from an assigned center point to an endpoint
calculated according to the “Length” parameter.

Origin

Center point of the indicator line referenced from the top left of the image (not the top left of
the window) meaning neither the frame of window nor the title bar is included. The “X”
parameter specifies the horizontal distance in pixels and the “Y” parameter the vertical
distance. “X” cannot exceed the Width of the background image and “Y” cannot exceed the
image Height. The default values are: Origin: X: Width/2, Y: Height/2. Note that the pixel
count starts at “0” so a 225 pixel square image will have its center point at 112 pixels.

Length

Specifies indicator span in pixels starting from the “Origin.” Default is the smallest of the
Length or Width dimensions divided by 2.

Thickness

Specifies the indicator width in pixels, with a selectable range between 1 and 10. The default is
1 pixel.

Color

Specifies color of the indicator “needle” as Black (default) or White.

When recording is stopped
If the source channel is a Calculation channel, no gauge
updating will occur when the recording is stopped. Under
this circumstance, the “When recording is stopped” options
become available. This allows the user to specify whether
the indicator should not be displayed, should be reset to
zero, or should retain the last value.
Mapping
For setting up two point mapping: Input to Angle.

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Input

Defines the input values in the scaled units. The units shown in the example are volts, but
would reflect the units of the source channel (mmHg, psi, etc.). The Input mapping of the upper
scale value is set to a default of 50 of the source channel unit type.

Angle

Any angle can be entered, but 0, 360, 720, etc degrees means that the indicator will always be
pointing straight down.
When assigning mapping angles: Because the indicator “needle” must rotate clockwise, the
first value should be the lower angle. The first value also defines the indicator’s starting angle
but does not to need to be 0 degrees. For example, the Stopwatch Gauge’s starting angle should
be 180 degrees (pointing straight up). If half-circle gauges are used, the starting angle may be
90 degrees.

Indicator is limited to specific mapping
If this option is enabled, and the indicator needle reaches its mapped upper limit, it will stop
rotating and turn red. If this preference is not selected, the needle will not change color if the
defined mapping limits are exceeded and the needle will just continue in a clockwise rotation.
Range Band (Default OFF)
Use the Range Band as an optional feature to highlight a specified area of the Gauge View.

Start/End

Defines a “pie” shape (defined by Mapping values) sourced from Gauge center and
superimposed over the background image.

Color

Clicking on the color bar will bring up a color palette, which allows any color to be selected.
The default color is green.

Opacity

Used to adjust the transparency of the Range Band. 100% means the background image will be
fully obscured behind the range band, and 0% means the Range Band itself will not be visible.
The default setting is 50%.

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Segment Timer “Stopwatch” option
In addition to the standard Gauge described above, the Segment Timer Gauge option offers an analog
“Stopwatch” view of an acquisition in progress. As the recording progresses, a circular onscreen stopwatch
gauge displays the elapsed time with a sweep-second indicator. All customizable parameters shown above for
the default Gauge view are applicable to the Stopwatch view. A custom mapping for the Stopwatch view can be
created, or use the pre-configured “Segment Timer Gauge” graph template in the Sample Data folder.
Using the Segment Timer graph template – open the sample template in the following directory:
Main drive\Program Data\Biopac Systems, Inc\AcqKnowledge 5\Sample Data\Segment Timer Gauge.gtl
Clicking ‘Start’ will show the Stopwatch in progress. The template is setup to record ECG Lead II on CH 1 and
is tied to a new Segment Timer calculation channel. However, no connections are needed to verify the segment
timer and the template can be customized as desired. To change parameters, choose Preferences from right
contextual menu with mouse positioned over the gauge window.
When the recording is stopped, timer indicator will also stop. When the next recording segment begins, the
segment timer will reset to 0. (This default can be changed in the Gauge Preferences).

To configure a new Segment Timer Stopwatch view:
1. Set up desired acquisition parameters and channels.
2. Hardware menu > Set Up Data Acquisition > Channels >
Calculation tab and choose the Segment Timer preset.
3. Hardware menu > Show Gauge and open Preferences by
right-clicking the contextual menu over the Gauge window.
4. In the Gauge Preferences, choose “C0 – Segment Timer” for
the Channel and “Stopwatch”, as shown on right.
5. Choose the “Mapping” tab, enter the following Input to Angle
mapping values and click OK:

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6. Start the acquisition. Note the Stopwatch view will accurately reflect the time scale of the recording
in progress.
Autoplotting, Scrolling and Sweep Display Modes
Checking or unchecking the Autoplotting, Scrolling and Sweep options controls how data is displayed on the
screen during an acquisition. By default, AcqKnowledge displays the most recently collected data first, and if
more than one screen of data is to be collected, then the time scale will “scroll” so that the newest data is always
on the right edge of the screen.
When Scrolling is disabled and Autoplotting is enabled, the screen will be cleared when the data reaches the
right edge of the screen, and plotting is redrawn from the left.
When both Scroll and Autoplot are unchecked, the incoming data will be plotted until the screen is full. Once
the screen is full, data will continue to be collected, but only the first screen is displayed. By default, the
hardware will display the first eight seconds of the data record, but this can be reset manually by changing the
horizontal scale. To toggle Autoplot ON or OFF in the middle of an acquisition:
Ø select Ctrl+T (Windows) or Command+T (Mac OS) on the keyboard, or
Ø Choose the MP menu and enable or disable “Autoplotting”
Sweep display mode is similar to an oscilloscope sweep display in which data is plotted left to right, but old
data remains visible on the screen while new data is incoming. This type of display is also seen in some clinical
devices. Sweep mode can be toggled from the hardware menu during acquisition and is data view independent.
Sweep mode is available in Scope, Chart, Stacked Plot, and Split View modes, and the sweep state is saved in
graph files and templates.
In order for Sweep display to function:
§ Autoplotting must be enabled
§ Scrolling must be disabled
§ Sweep must be enabled
In this configuration the old data remains visible while incoming data is in the form of a
black vertical line “sweeping” across the old data from left to right. The old data and
horizontal time scale are redrawn once the line sweeps across its axis.
Manual, Autoscrolling and Sweep options can also be accessed via the
,
, or
button in the lower right region of the horizontal axis region. For full details on this
tool, see Autoscroll Horizontal Axis Controls on page 49.
Limitations: Sweep mode is temporarily disabled when scale modifications affecting
the vertical or horizontal scale are applied. This includes: autoscaling, show all data,
adaptive scaling, zoom, window resizing, end of acquisition. Sweep mode is not
supported in XY mode.
“Sweep” mode cursor
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Warn on Overwrite
Selecting the “Warn on overwrite” option from the Hardware menu will generate a prompt each time a new
acquisition is started:

After clicking “Yes,” AcqKnowledge will erase the current file and overwrite it with a new acquisition. If the
current file needs to be saved, click “No” and open a new file.
This prompt will appear at the beginning of each acquisition when the hardware is in Save Once with repeats
mode. “Warn on Overwrite” can be disabled by deselecting this option under the Hardware menu.
Organize Channel Presets

The Organize Channel Presets option controls the channel presets (established or custom) in the Hardware > Set
Up Channels dialog. Presets can be renamed, rearranged or deleted. This option can be used to place the most
frequently selected Presets at the top of the menu or group related Presets, such as established ECG Presets.
Click a “Preset” description to select it, and then use the buttons to organize the Presets.
Up and Down buttons move the selection one space at a time.
Top and Bottom buttons jump to the start or end of the list.
Rename a Preset by typing in a new title and clicking OK.
Titles currently used by a Preset or any name that matches a Calculation type cannot be used. (Integrate,
Rate, etc.).

Delete a Preset by selecting that option. The Default Analog Input preset cannot be deleted. When deleting a
Preset, a confirmation dialog will appear because this is an irreversible action.

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Add Separator adds a new Separator entry to the Preset list and is useful for dividing different Preset types. If
a Preset is currently selected in the list, the Separator will be added below it. (See diagram above) If no preset is
selected, the separator will be added to the end of the list. Separators can be rearranged or deleted in the same
manner as Presets.
The default location for Preset files is Computer > Local Disk > ProgramData > BIOPAC Systems, Inc >
AcqKnowledge 5 > Presets.
Exit Playback Mode
This option is enabled when Open File for Playback (see page 39) has been selected. Select to resume
acquisition functionality (change Playback menu to Hardware menu, Replay button to Start button).
X

X

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Part C—Analysis Functions
OVERVIEW
This part describes how to analyze data; in most cases, analysis is performed after the data has been collected.
This involves creating, managing, and saving files, as well as editing data, performing mathematical
transformations, and displaying data in various ways. Many of the functions covered here are also discussed in
Part A—Getting Started. Features that can be computed during an acquisition (primarily transformations and
calculations) are discussed in Part B—Acquisition Functions.
For general information about sections of the graph window, and to become familiar with the “look and feel” of
AcqKnowledge, turn to the Editing and Analysis Features chapter. Descriptions of functions can be found in the
chapters describing each menu. All of the commands discussed here can be found under the File, Edit,
Transform, or Display menu items.
Menu

See…

File

Page 262

Edit

Page 286

Transform

Page 296

Analysis

Page 327

Specialized Analysis

Page 365

Display

Page 443

Media

Page 476

Type of Commands
X

General file management commands, including opening, saving, and
closing files. Export data files.

X

X

Cut, copy, and paste between and within files. Export data files.

X

X

Operations that primarily modify the data in the graph.

X

Operations that primarily derive data and measurements from the graph.

X

X

X

A courtesy copy of the new Specialized Analysis package with
automation and scoring routines is included under the Analysis menu.

X

Control how data appears on the screen either during or after an
acquisition.
Capture and Playback controls to synchronize video/audio with data.

Toolbars
Many of the most commonly used features in AcqKnowledge can easily be executed with a mouse click. The
toolbar contains shortcuts for some of the most frequently used AcqKnowledge commands; icons are grayed out
when they are not applicable. Custom toolbars can be created by clicking the Customize Toolbars icon.
Click Display > Show > to view the toolbar options. Check a toolbar option to activate it.
See page 57 for Toolbar icon definitions.
X

X

Shortcuts
Keyboard shortcuts are detailed on page 65.
Mouse shortcuts are detailed on page 69, including contextual menus.
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Analysis Shortcuts

In AcqKnowledge 5.0.2 and higher, Analysis Shortcut buttons are available within individual graph channels.
Analysis Shortcuts offer quick access to common Specialized Analysis* options. Clicking the shortcut presents
a pop-up menu containing analysis options relevant to the signal type present in the selected graph channel.
This feature is helpful for avoiding the confusion of having to scroll through a lot of unrelated Analysis menu
items when wishing to apply a transformation.
The Analysis Shortcut appears as a small button in the upper right corner of the graph channel
. In order for
this button to become active, one of the following configurations is necessary:
· A specific signal type must be configured in the AcqKnowledge Module Setup (MP160/150 menu > Set
Up Data Acquisition > Channels > Add New Module) and data acquired under those parameters.
· If using MP36R hardware, a specific preset signal type must be configured (MP36R > Set Up Data
Acquisition > Channels > Presets or MP36R > Channels > Setup > Advanced > Signal Types) and data
acquired under those parameters.
· Or post-acquisition, a specific signal type (ECG, EMG, etc.) can be assigned in the Channel
Information dialog. This will activate an Analysis Shortcut corresponding to the assigned signal type.
1. Choose Display > Channel Info…(or right click in a graph channel and choose “Channel Info”
from the contextual menu.)
2. Choose the appropriate signal from the “Type:” pop-up menu. See page 461 for more
information about the Channel Information dialog.

*See page 365 for complete Specialized Analysis information.

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Creating Custom Analysis Shortcuts
Custom transformations and analysis routines can be added. To add a custom item:
1. Right click the Analysis Shortcut button and choose “Customize.” (The “Customize” item will only
appear if the button is right clicked.)

2. Choose an option from the “Actions” list and click the right-pointing green arrow to add the item to the
shortcut. (Any number of custom items can be added.) Click OK.

3. Custom shortcut items will be present in the graph’s Analysis Shortcut list for the selected signal type.
(ECG for the above example.) Items can be removed via the “Clear” button or by selecting an item and
clicking the left-pointing green arrow.
TIP: Using the Alt or Option key in combination with the left-pointing green arrow will remove all shortcut
items.
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Chapter 13

File Menu Commands

Overview

Most of the items in the File menu are standard menu items and follow the standard Windows conventions or
Macintosh conventions. By default, all files are created and saved in the AcqKnowledge file format, a
proprietary format used to store binary data. Data can be read in from either text files or AcqKnowledge files,
and can be saved in text, graphic, or binary format. As a rule, storing data in the AcqKnowledge format saves
information in the most compact format possible and takes up less disk space than other file formats. In most
cases, graph windows and data will be saved in the AcqKnowledge format.
New
Graph Window
When a new graph window is created, the window parameters can be modified,
including horizontal scale, vertical scale, window size and position. These
settings take effect once an acquisition begins.
New > Graph-specific Journal
Creates a graph-specific journal; see page 50 for details.
X

X

New > Independent Journal
Creates an independent journal; see page 50 for details.
New > Data View
Creates a new Data View for the active (frontmost) graph and names the
window “Data View of ‘Filename’.” For Data View details, see page 41.
X

X

X

X

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New > Batch Acquisition
Use the Batch Acquisition feature to configure advanced experimental setups and acquire data from a
sequence of templates. Each template in the Batch may have different acquisition settings, channel
configurations, and stimulator setups. Use a Batch for long duration experiments with hardware setting
changes across segments, to automate routines, or to run multiple experiments on the same experimental
setup in succession.
§ For example, if an experiment has a preparatory period, a stimulus period, and a response period, three
graph templates could be batched:
§ A template to acquire for the length of the preparatory period
§ A second template with a stimulator configured for the stimulus period
§ A third template to acquire the response period without stimulation
All three templates could be added in sequence to a single Batch Acquisition, which would then acquire all
of the data for all three templates with a single start.
To create a new batch, choose File > New > Batch Acquisition to generate the Batch dialog.
The Templates controls at the top allows the addition,
removal, or re-ordering of templates.
§ Double click a template in the list to open the
output graph from the most recent acquisition.
§ Batch acquisition cannot combine acquisitions that
do not end, so the acquisition storage mode for
template files cannot be set to “Save last,”
“Autosave” or “Repeat forever.”

Status
N/A
In Progress
Waiting
Complete
Error

No status is available for the template, no batch acquisition has been performed.
Data is currently being acquired for the template.
A batch acquisition is in progress but has not yet reached the step where the template is used.
Data acquisition for the template has been finished successfully and has been saved to disk at
the batch output location.
A batch acquisition was aborted manually or due to communication errors. The data for the
template may not have been saved or may be unreliable.
Batch Errors
Misconfigured templates and misconfigured averaging templates may generate the Adjust
Length/Adjust Latency/Abort Acq warning prior to the start of acquisition. Clicking “Abort”
will halt the batch acquisition. Misconfigured templates may result in those rare cases where
data was acquired into a graph template with a different hardware configuration prior to saving
the template to disk.

Saving to:
Use the “Change” button to specify the
directory where the acquisition output should
be saved.

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Use MP Unit:
Specify the MP unit that should be used for the
Batch Acquisition.

This menu lists all of the available hardware units.
Entire menu dimmed out while batch acquisitions are in
progress.

Start/Stop Acquisitions
Toggles to starts and stop batch acquisitions; dimmed when the specified MP
unit is being used to acquire data unless it is a batch acquisition that is in
progress. Batch acquisitions may be terminated by using either a control in the
batch user interface or by clicking the “Stop” button in the graph window
actively acquiring data for the current template of the batch. During the
execution of an individual template acquisition, errors may occur that
abnormally terminate that acquisition (i.e., communications errors with the MP
unit, errors in calculation channel, disk errors, etc.). When the acquisition in
progress is terminated due to an error, the batch acquisition will be halted as
well.
§ If a batch acquisition is aborted early, the batch output directory
will contain the full result graphs for all of the templates that were
previously completed successfully. It will also contain a partial
graph file for the template that was being used at the time the
acquisition was aborted. Templates that were not used will not
have any associated graph files.
Resume
When a batch acquisition is terminated prematurely, the acquisition may be
restarted from the first template in the sequence or from where it was stopped
(e.g. the template with the error status).
Batch Acquisitions can be saved for use at a later time using File > Save Batch
Acquisition As. Batch Acquisition files retain all of the settings for their
individual templates and can be used even if the original templates used to
configure the batch no longer exist or have been moved. Each template is
acquired and saved into an output graph file that can be opened at a later point in
time to examine the results.
To open a Batch Acquisition, use File > Open and select type “Batch
Acquisition.”
When a batch acquisition is started, the templates will acquire data in the order indicated from the specified MP
unit. Files are saved before the next acquisition is started.
§ If the batch acquisition completes successfully, the batch output directory will contain all of the
graph files that were created during the acquisition. Each output graph is saved into a user-specified
directory and is titled “Batch n - template name” where n is the order in the acquisition sequence.

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Open
The File > Open command generates the standard file open menu, and supports a variety of different file
formats from the popup menu at the bottom of the dialog.

Multiple files
To open multiple files in a single dialog, hold the Control/Command key down and select multiple files. To
open consecutive multiple files in a single dialog, select the first file, hold the Shift key down and select
multiple files. AcqKnowledge can only recognize one Journal file at a time, so multiple selection is disabled
when the file type is set to Journal or Journal Template.
Graph

The default file formats (*.acq) is referred to as “AcqKnowledge” files. The
AcqKnowledge file format is the standard way of displaying waveforms in
AcqKnowledge. These files are stored in a compact format that retains information
about how the data was collected (i.e., for how long and at what rate) and takes
relatively little time to read in (compared to text files, for instance). AcqKnowledge files
are editable and can be modified and saved, or exported to other formats using the Save
as command. Format options for the graph file include
· Graph—AcqKnowledge 5
· Windows AcqKnowledge 3 Graph—previous release format
· Macintosh AcqKnowledge 3—previous release format
· Biopac Student Lab PRO Graph—import files created using the Biopac
Student Lab PRO software; to open BSL Lesson files (.ldd), manually add the
extension “.acq” to the end of the file.
BSL File Import Notes
BIOPAC produces two different software lines, the AcqKnowledge software
for research and the BSL software for higher education. These two
applications use different file formats, making it difficult to analyze data
recorded in one with the other.
AcqKnowledge can directly import data files that were created in Biopac
Student Lab PRO. This allows data acquired with an MP36, MP35 or MP30 to
be analyzed using the advanced analysis routines of AcqKnowledge.
Hardware and calculation channel settings are also imported. This allows for
the migration of some BSL PRO templates to AcqKnowledge. Only basic
analog, digital, and calculation channels can be acquired; templates that use
any of the BSLSTM or other output options are not supported.
Importing is limited to graph files created with BSL 3.6.6 or higher. It is not
possible to import files created with earlier versions of BSL. To import from
earlier BSL versions, those files must first be opened with BSL 3.6.6 or higher
and re-saved to disk to update the file format. The updated files can then be
imported directly into AcqKnowledge.
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When saving files, AcqKnowledge must save using the AcqKnowledge graph
file format or another available export format. It is not possible to open
AcqKnowledge graph files with BSL Lessons or BSL PRO.
Template

Graph Template files (*.GTL)
This powerful feature allows for creation of a template file with predefined experiment
parameters. Simply click “Start” to run the experiment.
The Graph Template option will save a copy of a master file and retains all settings for
future acquisitions. Graph template files open to previously saved setup parameters (as
established under the Hardware menu) primary graph window size.
This feature can be especially useful for recreating protocols in the laboratory. Set up an
experiment, save it as a Graph template, then simply open the Graph template file and
click the Start button to acquire data under the same settings.
When a Graph template file is opened:
a) The graph window will not contain any data. (Since no data is saved in the
N
template, arbitrary waveform output setups, which require a source date file,
O
will not function in a template.)
T b) The Journal window will contain all text entered and saved with the
E
template—this is a handy way to place instructions or information about the
experiment.
AcqKnowledge “Quick Start” (*.gtl graph template) files are available for over 40
applications. Just open the graph template file to establish appropriate settings for the
selected application, and click Start. Quick Start files were installed to the Sample Data
folder and can be used to establish the settings required for a particular application or as
a good starting point for customized applications.

Text

.TXT. Text files are a convenient way of transferring information between applications,
and most spreadsheet and statistics programs are capable of importing or exporting data
in a text file format. AcqKnowledge assumes that the text file contains numeric data laid
out in columns and rows, and that there is some delimiter between each column. It also
assumes that each column represents a distinct variable or channel of data. Normally,
the values in each row represent the state of each variable at different points in time.
When a text file is opened, the numeric values will be plotted as waveform data in a
standard graph window. Each column of data is read in as a separate channel.
If non-numeric values are encountered, a dialog will appear warning that data will not
be imported properly. In order for data to import correctly, the text file must consist
entirely of numbers and the separators (tab, comma, or spaces) between them.

Journal

Jrnl
Temp

*.JCQ—Opens an independent journal; see page 50 for details.
Open the journal file from the File Menu (File > Open > Journal); right-clicking or
double-clicking a saved Journal file will open a blank application window.
X

X

*.JTL—Opens a journal template; see page 50 for details.
X

X

Options
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When the Files of type: Text option is selected, an Options button is activated. Clicking
on this button generates another dialog with options for controlling the amount and type
of data to be read in, as well as the time scale for data display.

Wave data starts on line
To control how much data is read in, enter a value in the read line box at the top of
the dialog. This tells AcqKnowledge which row contains the first data point in the
series. By default, this is set to 1, although it may be necessary to set it to another
value since some applications (usually spreadsheets) generate a “header,” or text
information at the top of a file. It’s also possible to read in a limited amount of data
by entering a value in the box to the right of the line radio button. This value
indicates the last line to be read in as data. By default, text files will be read in
starting at line one and data will continue being read in until the end of the file is
reached.
Interval
To control the horizontal scale (usually time) for the text file after it is displayed in
the graph window, change the Interval between sample points, which can be
expressed either in terms of time or frequency. The interval between samples is
equal to the reciprocal of the sampling rate; Interval = 1/(Sample Rate). For
example, if data was collected at 50 samples per second, there is an interval
between sample points of 0.02 seconds. AcqKnowledge would then assume that
there is a 0.02 second “gap” between the data point in row two and the data point in
row three (and all subsequent pairs of adjacent rows). Likewise, with a data file that
spans 10 seconds and has 100 rows of data, the interval between sample points will
be 0.01 seconds.
Most files contain time domain data, although some applications generate
frequency domain data (the results of a spectral analysis, for example). The
principle here is the same as with time data, that there is some interval between
different frequencies. If a text file contains 20 sample points covering the range
between 0 and 60 Hz, then the interval would be set to 3Hz per sample.
Column Delimiter
This setting tells AcqKnowledge what characters indicate a “gap” between two
columns. This can be set to tab, comma, or space. All text files must have some
sort of column delimiter, unless there is only one channel of data present.
§ Tab delimited text files —the most common type— have a tab between each
column for every row of data. These files are most often generated by
spreadsheets and similar packages.
§ Comma delimited files place a comma between each column of data for each
row, much the same way as a tab delimited file. Statistics programs such as
BMDP and SAS frequently create these types of files.

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§ Space delimited files are also commonly created by statistics packages, and
place some number of spaces (usually two) between each column of data for
every row which contains information.
§ None. If uncertain which delimiter to use, select “none” and AcqKnowledge will
automatically select a delimiter.
When either tab or comma is selected, AcqKnowledge will read in a new column
each time it sees a delimiter, even if there are no numeric values between
delimiters. For example, the following text file will read in three channels of data,
although the channels will be of different lengths.
0.301424, 0.276737, 0.045015
0.338723, 0.808811, 0.542627
0.354271, 0.506313, 0.715995
0.001325, 0.762115
946207, 0.894992
0.926409,

Sample text file
The first channel will contain six data points, the first being 0.301424 and the last value
being 0.926409. The next channel will contain three data points, starting with 0.276737
and continuing through 0.506313. The software considers that there is no other data
values for channel two. The third channel starts with the entry 0.045015 and the last
data point for this channel is 0.894992. There are only five data points in the last
channel.
PhysioNet PhysioBank is a public service of PhysioNet and offers downloadable archives of
gigabytes of “standard” data for cardiac arrhythmias, gait analysis, and other types of
physiological signals. AcqKnowledge can use PhysioBank data directly and can be
integrated with other software tools that understand this interchange format.
A PhysioBank file is usually comprised of several files, including a header file (usually
“*.hea”), and all of the files must be located in the same directory for the PhysioBank
record to open successfully. Open using the header file.
Opening a PhysioNet file will import data and annotations into a new graph window. If
“atruth” annotations exist, they will be translated into appropriate events on the
appropriate channel. All annotation types are retained except LEARN annotations,
which are treated as UNKNOWN.
MATLAB® format AcqKnowledge can open files created as a MATLAB work space.
MAT
§ Windows™ can open MATLAB v6 compatible MAT files, including MATLAB 7
if the “v6” flag is specified in MATLAB before saving.
§ Interoperability with earlier versions of MATLAB is not guaranteed.
Uses the “MAT-file” binary format to load numerical and textual information. If the
MAT-file is properly formatted with the following arrays, AcqKnowledge will
reconstruct the graph with appropriate sampling rate, channel labels, units, and data:
T

data

units

labels

isi

isi_units

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269

MATLAB files open with no Start button.
If the MAT file is missing any of the
expected variables or contains extra
variables, only one two-dimensional array
variable can be imported into a graph. A
MATLAB Import Options dialog will be
generated. Choose which variable data is
stored in, what dimension maps to
samples, channel indices, and sample rate,
and then click OK to open the file.
If AcqKnowledge can’t recognize the file
format, an error prompt will be generated
and a blank graph window will be opened.

Raw

This low-level data exchange option interprets all data at a single sample rate; variable
sample rates are not supported. All of the data will be unscaled when opening
(importing) files. That is, a value of 0 will be imported as a zero voltage. Scaling will
need to be manually applied to the data. Options to open (import) raw data:
Data type:
32-bit or 64-bit IEEE floating point format or 8-, 16-, and 32-bit
integer formatted data
# of channels: Enter the number of channels stored in the data file as a positive
integer less than or equal to 60.
Layout:
Packed sequential: All of the data for an individual file is located in
a single block of the file and multiple channels follow one another.
Interleaved: Data is grouped into a single “frame” for each sample
location with one data element for each channel, so data for a
particular channel is spread throughout the file (similar to Linear
PCM audio file format).
Endian:
Little and big endian byte ordering, matching the data formats of x86
and PowerPC/Sparc, respectively. Set to big for Mac-Power PC
generated raw files (default), or to little for Mac-Intel generated or
Windows-generated raw files.
Set to x/sample: Specify the inter sample interval of data in the file, which will be
translated into an appropriate sampling rate. The edit field will
accept an arbitrary floating point number. The units menu contains
μsec, msec, sec, MHz, kHz, Hz. The edit field will be dynamically
converted to match the units selection; no conversion will be used
when switching between frequency and time.

Batch

Batch files (*bcq) is the format used for a saved Batch acquisition setup. All previous
configurations are saved in this file, so a Batch experiment can be rerun without having
to repeat the setup. When a saved Batch file is opened, the batch setup window appears
with previous graph templates intact. From here, the setup can modified and saved
under the same or a different name.

Igor Pro

Igor Pro Experiments (compatible with Igor Pro 3.1, 4.0, and 5.0).
The waves contained in an Igor Pro packed experiment can be opened (imported) in
AcqKnowledge provided that the packed experiment files comply with the following:
§ no text waves
§ no complex waves

§ all waves in Version 2 or Version 5 format (Igor defaults)
§ all waves one-dimensional (vectors)
§ all waves multiples of the same fundamental inter sample interval

If the wave has an associated wave note, it will be used as the channel label.
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WAV

WAV files containing 60 channels or less can be imported. When this format is chosen,
the list of available files will be filtered such that only files ending in the”.wav”
extension or having the “WAVE” type are shown. When a WAV file is selected, it will
be analyzed to determine if it is compatible with the AcqKnowledge application.
If the file is compatible, a new graph window will be created displaying the data
contents of the WAV file.
· Each channel will be numbered “Channel n” where n is an increasing digit.
These channels will be unitless in amplitude.
· All of the data will be converted into the 64 bit floating point format for storage
in memory and in the ACQ formatted files on disk.
· The horizontal axis of this graph will be set to time and the sampling rate set to
match the rate as specified in the WAV file headers.
· This graph will be marked as an imported graph into which data cannot be
acquired.
·

EDF

ACT
BBS

This will dim the start button and any appropriate hardware menu entries that
would be used to access the invalid hardware settings.
Opens files with .eeg and .edf extensions saved in European Data Format (EDF). Data is
imported entirely into memory in a newly created graph window titled after the
filename, similar to other file import routines. All scaling factors will be applied to the
data as it is imported, and it will be converted to double precision floating point format.
Since EDF format includes data that is not used by AcqKnowledge, only the following
items are imported:
· channel data
· channel labels
· units
· sampling rate (taken from maximum sample rate of all channels)
All other information stored in the EDF file will be discarded when the file is imported.
Only 60 channels of data can be imported from an EDF file. Channels will be imported
starting with the graph file index 1. If there is a 60th channel, it will be placed into the
channel with index 0. If an EDF file contains more than 60 channels, only the first 60
channels will be imported and a prompt will advise that not all of the channels could be
imported.
Opens actigraphy files generated from analysis of existing accelerometer data files
related to sleep studies and wake/sleep activity. Actigraphy licensed functionality is
required for this file format to be active. For information on Actigraphy, see page 537.
Opens Biopac Basic Scripting files. Biopac Basic Scripting licensed functionality is a
scripting language development option for AcqKnowledge. For more details, see page
503.

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Open Recent
The File > Open Recent command generates a list of recently used files. These files can be opened directly from
the list or with a Ctrl (PC) or Command (Mac) keystroke combination.

The listed files appear in the order they were opened, with the most recently-opened file appearing at the top.
Default number of files appearing in the list can be modified in the Preferences. (Display > Preferences > Other
or Main Toolbar)
Open Sample Data File
Allows easy access to AcqKnowledge Sample Data files, eliminating the need to navigate to them manually.
Open for Playback
The File > Open for Playback command generates a standard file open dialog; see page 39 for Playback details.
SMI BeGaze Import
This option allows for import of SensoMotoric
Instruments BeGaze software’s eye tracking data and
aligns the data with other physiological signals
recorded in AcqKnowledge. In order to use the SMI
BeGaze Import feature in AcqKnowledge, the BeGaze
eye tracking data must first be exported to a text file
format readable by AcqKnowledge. (BeGaze software
offers text file export of the eye position, pupil width
measurements, analyzed data and eye tracking events.)
BeGaze eye tracking data can then be imported into an
existing AcqKnowledge graph, a new graph, or aligned
to existing data.
To use TTL display trigger synchronization, the digital
output line from the SMI hardware must be connected
to the hardware unit used for recording record data,
and digital channels must be enabled during data
acquisition. The time of the first image presentation
within the BeGaze data will be placed at the first
positive peak within the digital signal. The software’s
timestamp alignment will extract the recording time
from the BeGaze data and align it with the internal
AcqKnowledge timestamps. For more details about
timestamp alignment, see page 272.
When importing and aligning data to an existing graph, physiological data must be recorded into a single
segment. Data recorded as multiple appended segments will not be properly aligned.
BeGaze exports may contain only a subset of the recorded and analyzed data. Signals not present in the export
file will be removed from the 'Signals to import' checkbox options.

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Importing SMI Begaze Data into AcqKnowledge
Use this feature to import eye tracking data from SMI BeGaze software into AcqKnowledge:
1. In Begaze software, export the eye tracking data to *.txt format and save the file.
2. Launch a new graph in AcqKnowledge or open an existing graph for BeGaze data import.
3. In AcqKnowledge, choose “File > SMI BeGaze Import” and navigate to the *.txt file exported in Step 1
and click “Open.” This will launch the SMI Data Import setup screen.
4. Under “Import data into:” choose the AcqKnowledge destination graph for SMI Begaze data import.
5. Choose the desired alignment option (digital trigger signal, timestamps from AqcKnowledge and SMI
data, or no alignment.)
6. Select the eye tracking signals and SMI events to import and click “Import.”
The selected SMI signals and events will be placed into the AcqKnowledge graph at the appropriate locations.
Eye tracking video created in the BeGaze software can be also be exported to AcqKnowledge and synchronized
with the graph data by using the “Sync SMI Video” feature under the AcqKnowledge Media menu. The video
synchronization is accomplished by extracting timestamp information from the exported BeGaze file.
Watch the AcqKnowledge SMI BeGaze import and synchronization video tutorial for a detailed
demonstration of this feature.
Using the Software Timestamps Option to Align Data
If the existing AcqKnowledge graph and SMI *.txt file selected for import were recorded in different time
zones, selecting the “software timestamps” option helps compensate for the time zone disparity and aligns the
data accordingly. In order for the timestamp alignments to be accurate, it is essential to know the time zone the
SMI *.txt file was recorded in. (The “export time zone” default setting is determined by the clock time/date
properties of the AcqKnowledge computer.) However, if the SMI eye tracking data was exported from another
computer in a different time zone, changing the “export time zone” parameter to match that time zone will help
properly align the imported data with the current time zone of the AcqKnowledge graph. This is best illustrated
in the following example.
In this example, the exported SMI BeGaze eye tracking data selected for import into AcqKnowledge was
recorded in the “Europe/Berlin” time zone, while the AcqKnowledge graph was recorded in the “America/Los
Angeles” time zone. To synchronize both files timestamps to the current time zone:
1. Follow Steps 1-4 from above (“Importing SMI BeGaze Data”).
2. Under “Align to existing data,” select the “software timestamps” option.
3. Scroll down the “Export time zone” list and select “Europe/Berlin.” (Or an applicable time zone.)

4. Click “Import.”
If the AcqKnowledge graph and the SMI BeGaze file selected for import were recorded/exported in the same
time zone, it is not necessary to use the “software timestamps” alignment option. In this instance, choose the
“No alignment” option.
Dataquest Import
Dataquest ART is a data acquisition software package from Data Sciences International (DSI). This package is
used with a variety of devices including implantable telemetry units. The File > Dataquest Import option allows
data acquired from ART files to be directly extracted into AcqKnowledge. The following Dataquest file
information is supported and retained in AcqKnowledge:
· Data accuracy

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Retention of animal IDs
Import of either waveforms or parameters

· Provides choice of animal subjects to be imported
Datquest File Description
Unlike graph files, Dataquest ART saves data as multiple files in a single directory. Each file may be either a
continuous recording or consist of multiple segments.
A recording may contain multiple animals/subjects. Each animal/subject is given an animal ID. This animal ID
forms the basename of all of the various Dataquest data files.
Two primary types of data are recording for each animal: waveforms and parameters. Waveforms are the semicontinuous raw data recorded from transmitters during the segment. For multi-channel recordings, each channel
may have an independent sampling rate and the sampling rate may vary within an individual channel for an
individual experiment, but the duration and recording frequency are identical across all channels and animals.
Parameters are derived measurements such as heart rates, mean pressure, and other values derived from the raw
data. The user's protocol may dictate which type of data will be useful in the analysis, but many DSI customers
perform further data reduction on the parameters instead of working with the raw data.
Dataquest splits waveforms and parameters up into separate files. Specific ID parameters are stored into a
sequence of files named “ID.P##” where ## is a continual incrementing sequence of alphanumerics 0-9A-Z.
Each individual waveform is stored into a series of files named “ID.C##.” C is a single character indicating the
channel number 0-9A-F, for up to 16 channels. ## is a continual incrementing sequence of alphanumerics 09A-Z, similarly to parameter files.
Each individual parameter or waveform file may contain data from multiple segments. A new file is created
once the size of a particular storage file reaches a user-specified limit. The total number of files, therefore, does
not necessarily equal the number of segments.
The data for each specific segment in the file also contains a timestamp indicating the calendar time of the
beginning of the segment.
Creating Graphs from Dataquest Data
Although related, waveforms and parameters are very different types of data. AcqKnowledge primarily stores
and analyzes continuous signals. As parameters are not continuous signals, they are not easily combinable with
waveforms in a single graph. Therefore, parameters and waveform data are imported differently.
Waveform Graphs
Waveform graphs are imported with waveform data within individual channels. Dataquest waveforms may have
different sampling rates for each individual waveform and potentially varied sampling rates within an individual
waveform. The imported graph’s sampling rate will be set to the highest sampling rate of all segments of the
file.
If a file contains multiple animal units, the animals can be selectively imported. By default all animal units are
imported into a single graph.
Each data segment is separated by an append marker to allow the use of Find Cycle across discontinuous data
segments. The append marker label corresponds to the segment timestamp of the in the local time zone.
For each animal with ID, the individual channels are imported with labels as “ID – label” if the DSI file
contains a label for the channel. If there is no label is found, it will be labeled with its index “ID – Channel C”
where C is the index from the beginning of the specific DSI file extension.
Parameter Graphs
Parameters are stored by Dataquest as one set of numbers per segment. Parameter graphs are imported using the
same approach as rate detector XY output graphs. The graph will be set up as an arbitrary horizontal axis
labeled “segment index.” Each parameter will be imported into a single graph channel, with the channel named
“ID – Param,” “ID” replaced with the animal ID, and “Param” replaced with the name of the parameter as read
from the Dataquest DSI file. The parameters are then imported as data points.
Only subsets of animals may be chosen; all parameters will be imported for the chosen animals. Users wanting
a subset of parameters may optionally erase or hide graph channels after the data is imported.
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To Import Dataquest files into AcqKnowledge:
1. Choose “File > Dataquest Import.”

2. Navigate to the Datquest file and click “Choose.”
3. Make the desired selection in the Dataquest Import dialog and click OK.

Dataquest Import
Opens a destination directory to export files to Dataquest format.
Close
This File menu command will close the active file window and display a prompt to Save.

TIP: To close multiple graph files at the same time, hold down the Alt/Option key while closing a file. All
graphs must be saved in order to use this keyboard shortcut.
Close without saving
§ Windows—click the

in the upper right corner of the file window

§ Mac OS—click the
in the upper left corner of the file window
Click “No” to the Save Changes prompt.
Close during acquisition

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Close multiple data views
Set the level of close functionality under Display > Preferences > Other or Main Toolbar.

Save

This menu command will save any changes made to a file. If more than one file is open, this command applies
only to the active window. For untitled files, a name file prompt will be displayed. The file will remain open
after the save is complete, allowing for continued work on the file.
· The Save menu is dynamic and corresponds to the type of file to be saved, i.e. Save Graph, Save
Journal.
Files should be less than 2 GB, except AcqKnowledge 3.9 “Graph” files on the Mac, which can be larger if not
compressed. Data files greater than 2 GB can be opened, but edit, transformation and analysis operation cannot
be performed.
To save data in another format (such as a text file), use File > Save As.
Save As
Choosing File > Save As produces a standard dialog that allows saving of data in a variety of formats and to
any location. As with all dialogs, use this to save a file to a different file name or directory than the default
settings.

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Graph

AcqKnowledge format
The default file format for the File > Save as command is to save files as an
AcqKnowledge 5 file, which is designed to be as compact as possible. These files can
only be opened by AcqKnowledge 4, but data can be exported to other formats once it
has been read in.
· To save in the previous release format, choose Windows AcqKnowledge 3
Graph. When a file is saved in AcqKnowledge 3 format, the following
calculation channel types will revert to Integrate: Band Stop Comb Filter,
Adaptive Filter, FLC, WFLC, CWFLC, Rescale and Metachannels.
File Compatibility
Windows AcqKnowledge cannot save as Macintosh AcqKnowledge files.
Macintosh AcqKnowledge 3.9 and above can save as “Graph (Windows)” files, but it
saves in Windows AcqKnowledge 3.7.1 format. In this earlier format, all data is
retained, but new Windows AcqKnowledge features (like dual stimulation, data
views, embedded archives, etc.) are lost along with any settings specific to Macintosh
AcqKnowledge (like events, adaptive scaling settings, etc.).
§ Macintosh AcqKnowledge 3.9 and above can save PC-compatible Graph (*.acq)
and Graph Template (*.gtl) files. Variable sampling rate information and
hardware settings are retained, and Journals can be read from and written to PC
files. Choose the format “Graph (Windows)” to create PC-compatible files.

GTL

Graph Template
This feature can be especially useful for recreating protocols in the laboratory. Set Up
an experiment and save it as a Graph template, then simply open the Graph template
file and click the Start button to acquire data under the same settings.
TIP: Check the existing Quick Start template files listed on page 266 before
X

X

creating or saving a new template. With over 40 templates provided, one
might be a close match to the settings required for a particular application
or to use as a good starting point for customized applications.

The Save As Graph template option saves the setup parameters established under the
hardware menu and retains the size of the primary graph window. In general, the
minimum file size for graph templates is 700 K-800 K; file size may increase as setup
options are enabled.
When a file is saved as a Graph Template:
a) No graph data will be saved.
· Since no data is saved in the template, arbitrary waveform output
N
setups, which require a source date file, will not function in a
O
template.
T
· It’s necessary to select Save / Save as and select “File of type .ACQ”
E
to save the graph data.
b) Journal text will be preserved. Any entered text will be saved to the
Journal window and stored with the template—this is a handy way to
place instructions or information about the experiment for future
reference.
TXT

Text
Saves graph data in text format. When Save As Text is selected, an Options button is
generated. Clicking on this button generates a Save Options dialog that allows control
over how much data is saved and the format it is saved in.

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Include header
When the first box is checked, a “header” is included at the top of the text file that
contains information about the sampling rate, number of channels, date created, and
other information relating to the data. This information is frequently useful, but some
programs will attempt to read in the header information as data, which could result in
nonsensical results. Including the header is recommended as it can always be edited
out later using a text editor or the journal.
Horizontal Scale
Enabling this checkbox will include the horizontal scale (usually time) values in the
text file, along with the data to be saved. This allows time series plots to be produced
in other applications, as well as correlating events to time indexes in graphing and
statistical packages. Since a separate row is generated for each sample point, To
exceed the limitations of programs if data is collected at a fast sampling rate (many
spreadsheet programs are limited to about 16,000 rows). It’s recommended to consult
the section on resampling data after an acquisition is completed (page 322 ).
Delimiter
When data is saved as a text file, each channel of data is saved as a separate column,
with the number values for each data point saved in rows. Use the pop-up menu to
select the delimiter to separate the columns of data in the text file. By default, a tab is
placed between each column for every row of data; this format is called a tabdelimited text file and almost all applications will read in tab-delimited text files.
Data can also be saved in a comma-delimited format or a space-delimited format.
Line ending
Use to create text files that are compatible with Classic Mac OS applications (Mac),
Unix-compatible applications (Unix), or PC-compatible applications (DOS).
Precision
Use to define the number of significant digits used for the horizontal scale when
pasting wave data. Very high sampling rates may require more than the default value
of 6 digits to accurately resolve the inter-sample interval.
X

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PhysioNet

This format requires that the WFDB library is present on the computer. PhysioBank is a
public service of PhysioNet and offers downloadable archives of gigabytes of
“standard” data for cardiac arrhythmias, gait analysis, and other types of physiological
signals. AcqKnowledge can use PhysioBank data directly and can be integrated with
other software tools that understand this interchange format.
Saving a file in PhysioNet (WFDB) format will export the entire contents of the graph
to a PhysioBank record. The record will consist of multiple files, all in the location
specified for export. There will be a header file (*.hea) and a single data file for each
channel of the graph (starting with “d” and ending with the base name of the header
file). The files must not be separated for a successful move or copy.
Export Limitations
Precision Some precision may be lost due to differences in binary representation
between AcqKnowledge and PhysioBank formats.
Events
Events will not be exported to the PhysioNet format.
Channels Only 32 channels of data can be exported from a graph (the max allowed
in a PhysioBank file).
Rate
When exporting a graph that uses variable sampling rates, all channels in
the exported file will be downsampled to the lowest waveform sampling
rate of the source graph.

*.MAT
MATLAB

Raw

MATLAB® format. Uses the “MAT-file” binary format to save numerical and textual
information as Filename.mat.
§ Windows™ create MATLAB Version 6 files, which are compatible with both
MATLAB Version 6 and MATLAB Version 7.
§ Interoperability with earlier versions of MATLAB is not guaranteed.
The following variables will be in the workspace when the file is opened in MATLAB.
data
Contains the data of the graph in floating point format, for all of the
channels of the array. The first dimension of this array is the amount
of data in each channel, the second dimension increments with each
channel. Therefore, each column contains a full channel of data that
can be accessed in MATLAB via data (1:length, [channel number]).
units
This string array contains the textual representation of the units of
the samples stored in data, with one element per channel of data.
labels
This string array contains the labels of each of the channels, with one
element per channel.
isi
This floating point array of one element gives the number of units of
a single inter sample interval of the data.
isi_units
This single string array provides a units string for a single unit of isi.
Time data will always be “ms,” frequency data will always be
“kHz,” and other values will be represented by an Arbitrary
horizontal axis type in an ACQ graph.
start_sample Contains the time offset of the index 0 sample of data in isi units.
This will be 0 for many graphs, but if only a selected area of a graph
was exported into the MAT file, the start_sample will contain the
offset from the original data corresponding to the start of the data
array in the MAT file.
Options to save (export) data for low-level data exchange are:

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Data type: 32-bit or 64-bit IEEE floating point
Layout:
Packed sequential: All of the data for an individual file is located in a
single block of the file and multiple channels follow one another.
Interleaved: Data is grouped into a single “frame” for each sample
location with one data element for each channel, so data for a particular
channel is spread throughout the file (similar to Linear PCM audio file
format).
Endian:

Little and big endian byte ordering match x86 and PowerPC/Sparc data
formats, respectively. To exchange with Windows applications or MacIntel, set to little endian; to exchange with standard Mac applications, set
to big endian.
Raw Data Export Limitations
Formats Raw export only allows data to be saved in 32-bit and 64-bit IEEE floating
point format.
Rates
All files will be interpreted at a single sample rate; variable sample rates
are not supported. If a graph with variable sampling rates is exported,
channel data for downloaded channels will be padded to match the highest
waveform sampling rate.
Length If channels have unequal lengths, the overall file length will match the
longest channel. Shorter channels will be padded at the end using their
final sample value so that all channels contained in exported files will be
equal in length.
Scaling When integer-valued analog channels are exported from AcqKnowledge to
raw files, all relevant scaling and offset will be applied—the data in the file
will appear the same as if the channel had been internally converted to
floating point format before export.
If the value of a channel is outside the maximum/minimum value that a
chosen export data type can represent, the value will be clipped
accordingly. (AcqKnowledge uses a 64-bit data type, so this should only be
a problem if exporting to 32-bit floating point values.)
Igor Pro

WAV

Igor Pro Experiment format.
An AcqKnowledge graph will be saved (exported) to a single packed experiment file,
with each channel saved into a separate Igor wave that preserves the channel label,
waveform sampling rate, and unit information. Vertical units will be stored as data units,
and horizontal units will be stored dimension units; extended units are supported. The
scaling of each wave will be adjusted to match the waveform sampling rate. All data
will be stored in 64-bit floating point format in a one-dimensional wave. The waves will
be named incrementally from “wave0” and the channel label will be stored in the wave
note field. Files will have the type/creator pair “IgsU/IGRO” and a .”pxp” extension will
be added to the file name for compatibility with Igor Pro for Windows™.
This option saves the graph data into a WAV audio file for exchange with other
applications. The .”wav” extension will automatically be added if the save as filename
does not end with it.
The “Selected area only” checkbox will be active for WAV export. When checked, only
the highlighted area will be exported to the WAV file. The final sample of this range is
not included in the export, mirroring the other file export routines of AcqKnowledge.
All exported WAV files use the 64 bit floating point format. This format preserves full
operational precision. Most audio applications should be able to support floating point
WAV files. Exported data will not be normalized when it is exported. Any
normalization to audio ranges should be performed prior to exporting the data.
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WAV files are normally either one or two channels (e.g. mono or stereo).
AcqKnowledge graph files, however, usually contain more than two channels.
Although they can contain more than two channels, most audio applications may not be
able to recognize these multiple channel files.
· If a graph file contains only one or two channels of data, a WAV file will
automatically be created without further interaction.
o Graphs with a single channel will result in mono WAV files.
o Graphs with two channels will result in stereo WAV files.
· If a graph contains more than two channels, the user will be presented with the
following choice:

all channels—create a multiple-channel WAV file with one channel per
channel of data in the graph. While this WAV file may be easily opened
by some applications, it may not be fully compatible with audio
applications and other applications expecting two channels or less.
o selected channel only—create a single channel mono WAV file using
only the data of the selected channel. This will be the selected channel
in chart mode, the active channel in scope mode, or the vertical channel
in X/Y mode. This single channel export may be useful for exporting
audio channels that are recorded along with physiological data, such as
heart sounds, audio stimuli, and the like.
After a WAV file is exported, the WAV file will not be reopened; the open graph will
be left unmodified. To view the exported file, import the WAV file.
o

EDF

Saves file in European Data Format (EDF). The saved file will automatically have an
.edf extension added onto it if the user did not include it. Users will be able to save
either the entire graph or only a selected portion of data.
AcqKnowledge does not retain sufficient information to accurately complete an EDF
header. When exporting, the following default values will be used:
EDF Header Element
subject ID
recording ID
recording date
recording time
transducer description
filter description

Default
Empty*
Empty*
Set to the modification date of the graph file on disk.
If no graph file is on disk, the current date is used.
Set to the modification time of the graph file on disk.
If no graph file is on disk, the current time is used.
Empty*
Empty*
* Empty: indicates that the field will be left blank

All other fields will be filled with corresponding information from the graph, including
channel titles, sampling rates, channel units, and scaling factors. Variable sampling rate
information will be preserved as it can be expressed in the EDF format.
EDF is used by many applications and online recording databases to store information,
particularly EEG recordings. EDF is an open file format originally developed for sleep
studies. It stores continuous time recordings of data in a binary format. Since its original
proposal, EDF has been adopted by a number of open source and commercial tools as a

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Volts

1.261495

BPM

71.134882
60.972756

0.886667
0.760000

Seconds

Heart Rate

-1.261495

R-R Interval

2.156067
0.718689

Volts

AcqKnowledge also supports formats for
saving graphical information. Most
drawing, page layout, and word
processing programs can read .JPG files.
This is particularly useful for writing
reports. A. JPG file can be opened in any
standard drawing program and can then
be embellished or used to highlight any
particular phenomena of interest.

R-Height

JPG

ECG

supported data file format.
Usage has also expanded beyond sleep studies into other types of recording.

When data is saved as a graphic, only the
3.71129
4.32983
4.94838
5.56693
current screen data is saved. For example,
seconds
for a data file that spans eight hours but displays only two minutes of data onscreen,
only the two minutes of data will be converted to a graphic file. Since AcqKnowledge
uses information about the computer screen in creating the graphic file, the default
resolution of the file will be the same as the window. Most word processors and
graphics packages allow for some way to resize and scale graphics.
Compressed Saves a compressed AcqKnowledge formatted file. The degree of compression varies
based on data characteristics, but will generally achieve about 60% compression. Saving
small files (less than 200K) may have little effect. Using a sample file as an example:

Compressed graphs no longer allow data acquisition and will open with no Start button.
A warning prompt will be
generated when attempting to
compress a graph in which
data can be acquired (Start
button active):
Excel
Spreadsheet

Excel Spreadsheet Export—Graph data can be saved directly to an Excel spreadsheet by
using the Excel Spreadsheet format in File > Save As. Each channel will be placed into
its own column of the spreadsheet. Also available for File > Save Journal Text As, Find
All Cycles journal, and Specialized Analysis tools.
Note

The Excel spreadsheet option requires Excel or a compatible spreadsheet
application that can read Excel files (OOo, Symphony, etc.). If Analysis results
are exported to an Excel spreadsheet, and a compatible application is not
available, results will open as a text document the data and nonsense characters.

Save Selection As
To save only the data that has been selected with the I-beam tool, choose File >
Save Selection As; this option saves the selected area to another file and does
not affect the currently open file. Specify file name and file type and click
Save.

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Save Journal Text As

Choosing File > Save Journal generates a save dialog to save the journal text as a separate file. Specify file
name and file type and then click Save.
Journal
Text (*.TXT) format—Saves an independent journal; see page 50 for details.
X

Jrnl
Temp
Excel
Spreadsheet

X

.JTL format—Saves a journal template; see page 50 for details.
X

X

Excel Spreadsheet File (*.XLS)—Journal text can be exported directly into an Excel
spreadsheet by using the File > Save Journal Text As with the Excel Spreadsheet format. Each
line of text in the journal will be saved as a single row with tabs separating columns. A
selected portion of a journal can also be written to a spreadsheet. This export allows for
textual data reduction results to be easily exported into a spreadsheet to allow for further
analysis.
·

Also available for File > Save As, Find All Cycles journal, and, for Specialized
Analysis tools.

Note The Excel spreadsheet option requires Excel or a compatible spreadsheet application

that can read Excel files (OOo, Symphony, etc.). If Analysis results are exported to an
Excel spreadsheet, and a compatible application is not available, results will open as a
text document the data and nonsense characters.
File Format prompts
When a file open or save function requires a format change for compatibility or alters file content, a prompt will
be generated to require the user to confirm the option to update format or convert and save.

Created with a previous version of AcqKnowledge

Windows PC AcqKnowledge format

Saving as a “Graph Template” will erase all data

Imported from another file format

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Send Email Attachment
Use this feature to create an email attachment containing an image of the active AcqKnowledge graph, along
with the journal contents.
When using this feature:
o

The default email program will launch, along with a ‘compose new email’ window.

o

An Open Document (*.odt) text file containing an image of the currently opened graph and associated
journal text will be copied to the attachment field. The formatting and images present in the journal
should be preserved.

o

Further details can be typed into the body of the email prior to sending.

In order to open the attachment, the email recipient must have a word processing application compatible with
*.odt file format, such as OpenOffice, NeoOffice or Microsoft Word™.
Copy to Dropbox – Open from Dropbox
The Dropbox options allow for copying or opening AcqKnowledge data files to or from a Dropbox account
directly from within the AcqKnowledge application. This is useful for storing files online where they may be
accessed from any computer. In order to use this feature, access to an active Dropbox account is necessary.
To create a Dropbox account, go to www.dropbox.com.
To set up AcqKnowledge to use Dropbox:
1. File > Copy to Dropbox. If Dropbox is being used for the first time in AcqKnowledge, or if not
logged in to a Dropbox account, the following authorization dialog will appear.

2. Click the “Authorize Button” and sign in to the Dropbox account.

3. Click “Allow” to grant AcqKnowledge permission to create a new Dropbox folder (above left).
4. A confirmation dialog will appear indicating AcqKnowledge is successfully connected to
Dropbox (above right). Close or minimize the browser window.
5. Dismiss the Step 1 Dropbox authorization dialog by clicking “Login.” While logged in to the
Dropbox account, this setup procedure will not need to be repeated.
To Copy files to Dropbox:
1. File > Copy to Dropbox.
2. Accept the default filename or enter a new one and click OK.

3. A confirmation dialog will appear indicating the file is stored on Dropbox.
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To open files stored on Dropbox:
1. File > Open from Dropbox.
2. Select the desired file from the list of stored AcqKnowledge files and click “Open.”

NOTES:
· If Dropbox is being used for the first time in AcqKnowledge, or if not logged in to a Dropbox account,
the authorization dialog shown on the previous page will appear before allowing access to a stored file.
· More than one file can be opened from the list, but must be selected individually. Multiple selections
are not supported.
· To log out of Dropbox from AcqKnowledge, choose File > Logout from Dropbox.
Page setup
Choosing File > Page Setup produces a standard printer setup dialog that allows setup for any available printers.
All options in this dialog function as described in the system manual. There are also options for configuring
printing adjustments with respect to fonts, image orientation, and graphics presentation.
Print
The File > Print menu that AcqKnowledge uses is similar to the standard computer print dialog; however, there
are additional options available
The Print menu is dynamic and corresponds to the type of
file being printed, i.e. Print Graph, Print Journal.
Click Print for more options.
Note: In Mac OS, the option to create a PDF file appears in
the initial Print dialog.

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· Print Options
§ Plots per page—Control how many plots appear per page when the file is printed. Printing more than
one plot per page has the effect of “snaking” graphs on a page much the same way text appears in a
newspaper. For example, if this option was selected so that two plots were printed per page,
AcqKnowledge would divide the amount of data to be printed on that page into two graphs—one graph
printing at the top of the page, the second graph printing at the bottom of the page. This option allows
records to be printed on considerably fewer pages than standard printouts, and is most effective when
only a few channels of data are being printed.
§ Fit to pages—Print the contents of a window across multiple pages. When a record is printed over
multiple pages, the amount of data on the screen (the amount of data to be printed) is divided by the
number of pages entered in the dialog. The graph on the screen is then printed across the number of
pages specified in the Total pages box at the bottom of the File > Print dialog. These two options apply
only to graph windows, and do not apply to Journals.
· Draw vertical dividers at event positions—Adds visible borders at points where events occur.
· Print waveform data in black—Waveforms will appear black when printed, regardless of selected colors
in graph channels.
· Print waveform background in white—Prints white background, regardless of selected background
colors in graph channels.
· Print focus areas—Turns focus areas on or off for the printout.
· Range Options—determine the range of data that will be included in the printout
§ Visible portion only synchronizes the range of data in the printout to match the range of data that is
visible on the screen.
§ Selected portion only prints only the data that is selected in the graph. This option is disabled if there
is no selection in the graph. When working with Journals, it is easy to generate large amounts of text
content in the window. Only a portion of this information may actually be of interest and this feature
allows for only portions of the text to be printed. If there is no selected text, the entire journal or
modification log will be printed regardless of this setting.
§ Entire graph prints all of the data contained in the graph from zero to the maximum length channel.
· Print to PDF file—generate a PDF file.
Go to Startup Wizard
Closes graphs and exits to the Startup Wizard. This is useful if multiple graphs are open and circumvents the
need to close each one individually via the close (X) button or File > Close.
Quit
Select Quit from the File menu to entirely exit AcqKnowledge software; a prompt will appear to save
any open graph files that have been modified.
Mac OS only—Use Quit under the AcqKnowledge menu (page 474) to exit the software.
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Chapter 14

Edit Menu Commands

Overview

One of the most useful features in AcqKnowledge is the ability to edit and work with data by cutting and
copying sections from one window to another. In this sense, AcqKnowledge can manipulate data much as a
word processing program handles blocks of text. To select an area of interest in the AcqKnowledge data for
further study, use the I-beam selection tool to highlight an area.
This selection tool is used for a variety of
purposes including cutting and pasting waveform data, making measurements and determining which portion of
a waveform to save as text values. To select this tool, click its icon on the toolbar. Notice that the cursor
changes into the familiar “I-beam” cursor when moved within the graph area. Click the mouse and drag to
select a portion of the waveform.
IMPORTANT
When multiple waveforms are present, the highlighted area appears to include all of the waveforms,
but most modifications and transformations apply only to the selected channel.
Once a section of a waveform has been selected, functions such as editing, transformations, saving data to the
journal, saving as text, and using the measurement functions can be performed on the selected area. The cursor
always selects at least one sample point; when there is no defined area, a single sample point will be selected,
and the cursor will blink. Highlight a larger area by positioning the cursor over the first point of interest, hold
down the mouse button, and drag the cursor either left or right to highlight an area. Modify the selected area by
placing the cursor anywhere on the graph, then holding down the shift key and clicking the mouse. This feature
is useful for fine-tuning the selected area. To fine tune, first coarsely select an area. After zooming in (with the
zoom tool) on either edge, then use the shift key to precisely align the edges of the selected area.
AcqKnowledge also allows the selection of an area spanning multiple screens. To do this, first select an area
that contains the leading edge of the graph portion of interest. Next, use the horizontal scroll bar to scroll to the
end of the area of interest. Then place the mouse near the area of interest and click the button while holding
down the shift key. While still depressing the mouse button, move the cursor to the exact position desired.
By using the selection tool to select areas of the waveform, the Cut, Copy, Paste and Clear functions are
designed to work in much the same manner as any text editor. These functions operate only on the selected area.

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Edit menu functionality during acquisition
The following Edit menu functions cannot be performed during acquisition: Undo, Cut, Clear, Clear All, Paste,
Insert Waveform, Duplicate waveform, and Remove Waveform.
Undo / Can’t undo
The Undo command allows for restoration of data that was unintentionally deleted or modified. Undo applies to
editing commands and transformations (such as digital filtering and mathematical operations).
There are some important exceptions to the Undo command.
First, neither Edit > Clear all nor Edit > Remove waveform can be undone. It is a good idea to make backup
files before performing any editing, especially when using these commands.
Second, changes in the display options (i.e., changing the horizontal scale or changing the color of a waveform)
cannot be undone, since they are easier to manipulate and less drastic than cutting data out of a waveform. If the
screen scale (or other display parameters) is modified, it is possible to undo this modification.
TIP: If a waveform is removed of if a “Clear All operation is applied accidentally, one
way to recover the data is to close the file without saving the changes. The data
file can now be reopened and changes made since it was last saved will not be
retained.
Perform multiple levels of undo on a per graph basis. The most recent operation is undone first followed by the
previous operation until the maximum number of Undo operations are reached. The maximum number is set in
Application Preferences (Display > Preferences > Graph > Maximum levels of undo) .

NOTE: Specialized Analysis (page 365) scripts are complex and undo may not function for all steps.
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Cut
When Edit > Cut is selected, the selected portion of the active graph channel removed and copied to a clipboard,
where it is available for pasting into other windows.
Cut cannot be performed during acquisition.
§ When a selected area is removed from a waveform, the data will shift left to “fill in” the deleted area. So,
if ten sample points are deleted, all data after the selected area will be shifted over ten sample points.
Since this alters the relationship of events to the time base, it’s recommended to consider alternatives to
cutting sections of data—such as using smoothing, digital filtering, or the connect endpoints functions to
transform the section of data.
Area selected using the
editing tool à

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Same data with selected
area Cut out à
Note that the data
after the selected
area has shifted
backward in time.

Copy
Choosing Edit > Copy will copy the selected area of the active graph channel to the clipboard without
modifying the text/waveform on the screen.
§ Once the area has been copied, it can be inserted in another window of the same type using the Edit >
Paste command or, for waveforms, the Edit > Insert waveform command.
§ To copy a waveform to another channel in the same graph window, choose the Edit > Duplicate
waveform command.
§ Edit > Copy applies only to a selected area of graph data. To copy and entire graph, use Edit > Clipboard
> Copy Graph (see page 291.)
Paste
The Edit > Paste command will take the contents of the clipboard and paste it into the currently selected area of
the active window of the same type.
§ If no area is selected, the data is pasted at the beginning of the waveform in a Graph window or the end of
the text a Journal window.
§ Paste cannot be performed during an acquisition.
Clear
The Edit > Clear command works much the same way as the Cut command, with the key difference being that
data is not copied to the clipboard. This function deletes the selected area from the selected channel only. If the
entire waveform is selected (as with the Edit > Select all command), the clear command will delete all the
waveform data and leave an empty channel.
Clear may move or alter memory and cannot be performed during acquisition.
§ As with the cut command, the clear function operates on only one channel, and when a portion of the
waveform is deleted, the remaining data will shift left. If multiple channels of data are present, one
channel will be “shorter” than the others.
§ To remove a selected area of data from multiple channels, use the Edit > Clear all command.
Clear all
Choosing Edit > Clear all will delete the selected area from all channels. This is similar to the clear function in
that data is removed and is not copied to the clipboard. The Clear all command, however, removes a section of
data from all waveforms, whereas the clear command applies only to the selected channel.
Clear All may move or alter memory and cannot be performed during acquisition.
§ When Edit > Select all is chosen prior to performing the Clear all function, all waveform data for all
channels will be deleted.
§ The Edit > Undo command does not work for Clear all.
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Select All
When Select all is chosen from the Edit menu, the entire selected channel becomes highlighted. For almost all
commands, when a waveform is selected using Select all, subsequent operations apply to the selected channel
only.
§ The exception is when Edit > Clear all is chosen after Edit > Select all. When this occurs, all data from
all waveforms will be deleted.
Insert waveform
The Edit > Insert waveform command is useful for copying a waveform (or a section of a waveform) within the
same or another graph. However, within the same graph, Duplicate waveform is simpler. To do this, first select
the area to be copied using the cursor and the Edit > Copy command. Next open the graph window to insert the
waveform into.
Select the new graph and choose Edit > Insert waveform. A new (empty) channel will then be created and the
data copied into the empty channel.
§ Insert waveform cannot be performed during acquisition.
§ This command cannot be undone directly, although selecting the inserted channel and choosing Remove
waveform from the Edit menu effectively undoes this operation.
Duplicate waveform
Choosing Edit > Duplicate waveform will create a new channel in a graph window and copy an entire
waveform (or a selected area) to the new channel. When a portion of the waveform is selected, only the
highlighted area will be duplicated.
Duplicate waveform may move or alter memory and cannot be performed during acquisition.
§ To duplicate the entire waveform, choose Edit > Select all and then select Duplicate from the Edit menu
or click the right mouse button and select Duplicate from the pull-down menu.
Remove waveform
Deletes the entire selected waveform, regardless of what other options are selected. Remove waveform may
move or alter memory and cannot be performed during acquisition.
§ The Edit > Undo command does not work for Remove waveform.
Remove last appended segment
Removes the last appended segment. Equivalent to the

§

Rewind toolbar icon.

Edit > Undo does not work for Remove last appended segment.

Create Data Snapshot
The Snapshot options store “snapshots” of the original acquired data at specific stages along with the full graph
file. Use snapshots for analysis or reporting to compare results to original waveforms or intermediate stages of
analysis. This is essentially an embedded archive; it is not a backup tool.
IMPORTANT: Archive functions do not create a new file—they are not backup functions.
Original data is copied and pasted to the end of the original file.
This feature cannot be used to recover lost or damaged graph files.
See page 51 for Snapshot details.
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Merge Graphs
Combine multiple graph files into a single file for performing cross-file analysis and storage. Use merge with
the multiple-hardware capabilities to produce single graph files containing multiple streams of data from an
individual subject.
Use Merge Graphs to combine data from multiple graph files acquired with the same acquisition rate into one
merged graph file.
Note Merge Graphs requires AcqKnowledge to allocate additional memory and then load the data into
memory; when this operation is executed on large data files, the application may crash—on Windows
OS, the resulting file size of a merge should be less than 2 GB; data files greater than 2 GB can be
opened, but edit, transformation and analysis operation cannot be performed.
1. Select Edit > Merge Graphs to generate the Merge Graphs dialog.
2. Click Add Graph to generate the Choose Graph dialog.
3. Choose a file to add to the merge.
§ “Add” the “Matching graph” listed (this pull-down menu includes all open files with the same
acquisition rate)
§ “Add File…” to browse and select a file that is not already open
4. Adjust the selection for individual channels if desired.
§ Click the “+” to list individual channels in the graph file.
§ Toggle the checkbox to add or remove the associated channel/graph file.
§ File names cannot be deleted from the list, but they can be removed from the merge.
5. Repeat as desired for multiple files.
6. Click Merge and wait (the status can be checked in the Total Channels bar).
7. Save the merged file.

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Merging graphs as data segments
Individual graphs may also be merged into a single channel as appended segments. This can be useful for
concatenating data types that don’t support append mode, or when importing data from software that outputs
each session as a self-contained graph file.
To merge separate files into sequential segments, check the Merge Graphs “as data segments” option and select
the data files as shown in steps 1-7 above. The same limitations exist for appended graphs as do for graphs
merged into individual channels. (All selected graphs must share the same sample rates and channel
configurations.)

Additional navigation controls become available when merging graphs as appended segments. This allows
reordering of the data segments into the sequence desired for the merged file. By default, the first graph added
to the list will be displayed as data segment 1, but this can be modified by selecting any appended graph and
moving it up or down the list via the “Up”, “Down”, “Top”, “Bottom”, or “Delete” navigation buttons.
Clipboard

All of the clipboard commands involve copying data from AcqKnowledge to the standard Windows clipboard,
where the contents of the clipboard are made available for other applications. Transferring data to the clipboard
allows data to be copied from AcqKnowledge to other applications even after closing the graph window and/or
quitting AcqKnowledge.
Data can be copied to the clipboard in two formats:
Text/Alphanumeric Copy Measurement and Copy Wave Data save information to
the clipboard in text/numeric format.
Graphic format
Copy Graph transfers the image in the window to the clipboard.
Ø Copy Measurements
Copies the contents of all visible measurement popup menus, along with the values associated with
these windows. Once the measurements have been copied, they can be pasted into any application that
allows paste functions, including word processors, drawing packages, and page layout programs. A
sample of measurements pasted from AcqKnowledge into a text document follows:
BPM = 85.714 BPM
delta T = 0.700 sec
p-p = 0.8170 Volts

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Ø Copy Wave Data
Copies the data (in numeric form) for all channels from the AcqKnowledge graph into the clipboard.
When an area is selected, only the data in the highlighted area will be copied to the clipboard. As with
the copy measurement command, once the data is stored in the clipboard, it can be pasted into virtually
any application.
When multiple channels of data are copied to the clipboard, the data is stored in columns and rows,
with data from each channel stored in a separate column. For a four-channel record, four columns of
data will be copied to the clipboard. As with a text file, AcqKnowledge will insert a delimiter between
each column of data. The default delimiter is a tab; the delimiter can be changed to either a space or tab
in the File > Save as Options dialog. See page 266 for more detailed instructions on how to set the
column delimiter. Transferring data through the clipboard performs essentially the same function as
saving data as a text file (using the File > Save As command), with the obvious exception that
transferring data through the clipboard does not save data to disk.
Ø Copy graph
Copies the graph window as it appears on the screen to the clipboard, where it is stored in graphic
format. The graphic can be placed into a number of different types of documents, including word
processors, drawing programs, and page layout programs. The JPEG graphic format are common to
almost all applications, and images saved in these formats can be edited in most graphics packages and
many word processors.
Using the copy graph function is similar to saving a graph window as a JPEG (using the File > Save As
command), except that using the file save command writes a file to disk, whereas transferring data
through the clipboard does not save a file.
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Ø Copy Acquisition Settings
Creates a textual summary of the current acquisition settings and sends it to the clipboard, where it can
be pasted into the journal via Edit > Journal > Paste Acquisition settings, or pasted to another program.
The summary includes sampling rates, channel configuration, calculation channel settings, triggering
options, averaging options, and if any stimulator is active. This is useful for retaining records for
acquisition parameters (and for technical support, if necessary). Use this feature to keep a textual record
or printout of the hardware unit configuration along with the data.
Ø Copy Data Modification History…
Copies the transformation history for all channels or a selected channel to the clipboard. Modification
history includes the transformation name, channel (analog, calculation, or digital), date & time, and
relevant transformation parameters, including starting and ending sample position.
Use Edit > Paste to move it from the clipboard to an active Journal window or other word processing
application.

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Ø Copy Focus Area Summary
Copies the starting and ending position of the focus area in horizontal axis units. Summary includes focus
area label.
Ø Copy Event Summary
Copies events to the clipboard as selected in the Event Summary setup dialog.
Journal

The Edit > Journal sub-menu options are similar to those found in the Edit > Clipboard menu. The key
difference is that data (whether measurements or raw data) is pasted directly into the journal rather than copied
to the clipboard.
Ø Paste Measurements
Choosing Paste Measurements from the Edit > Journal menu will cause all visible measurement
windows to be pasted into the journal. Each time this is selected, the measurements and values are
pasted into the journal using the precision specified in the Display > Preferences dialog. Additional
measurement rows and degrees of precision can be added in the Preferences (see page 461).
Paste Measurement shortcuts:
Keyboard: Ctrl + M
Mouse: Right-click in the Journal and choose “Paste Measurement”
Ø Paste Wave Data

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Converts the selected area of the waveform to numeric format and paste it into the journal in standard
text file format. As with the copy wave data command (in the Edit > Clipboard submenu) this will paste
the selected area from all channels, not just the selected channel, and will place a delimiter between the
columns when two or more channels are being pasted to the journal. By default, tab characters are used
to separate columns but can also be changed to comma or space delimiters in the File > Save As >
Options dialog. See the Save As section on page 275 for more information on how to change the
column delimiter.
Ø Paste Acquisition Settings
Pastes the acquisition settings to the journal as they were copied via Edit > Journal > Copy Acquisition
settings.
Ø Paste Modification History…
Use after Copy Data Modification History… to paste the transformation history from the clipboard for
all channels or for the selected channel to an active Journal window or other word processing
application. Modification history includes the transformation name, channel (analog, calc, or digital),
date & time, and relevant transformation parameters, including starting and ending sample position.
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Ø Paste Focus Area Summary
Pastes the focus area summary to the journal as copied via Edit > Journal > Copy Focus Area
Summary.
Ø Paste Event Summary
Pastes the event summary to the journal as copied via Edit > Journal > Copy Event Summary.

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Ø Manage PDFs
Use this option to select and import (embed) PDF files into the Journal as tabbed windows. Multiple
PDFs may be imported and each PDF appears under its own tab heading. Choose Edit > Journal >
Manage PDFs, or right-click in the Journal and choose Manage PDFs. The following dialog will appear:

Control

Description

Embed New

Launches a “File > Open” dialog for navigating to
the directory containing the PDFs to be embedded.

Remove

Removes a PDF from the list. (The actual PDF is
not deleted.)

Up

Moves the selected PDF up the list and determines
its tab order in the Journal.

Down

Moves the selected PDF down the list and
determines its tab order in the Journal.

OK

Imports the embedded PDFs into the Journal

After embedding PDFs into the Journal, toggle between them by clicking the tabs. Clicking the Journal
tab will activate the Journal window. Saved Journal content is not affected by embedded PDFs.
· The Journal formatting tools are not available when a PDF is actively displayed.
· The Manage PDFs option is only available when the Journal is displayed (Show > Journal).

Ø Show Journal
Toggle to display/hide the Journal window.

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Chapter 15

Transform Menu Commands

Overview

The Transform menu contains operations that primarily modify the data in the graph.
AcqKnowledge provides a number of options for post-acquisition analysis and transformations. These
transformations perform a range of operations on the data, from digital filtering and Fourier analysis to math
functions. All of these options can be found under the Transform menu, and are disabled while an acquisition is
in progress. Unless otherwise noted, all transformations described here apply to the selected channel only. Some
options (such as the expression and math functions) allow users to specify a channel (or channels) to be
transformed.
It is important to remember that AcqKnowledge is always selecting at least one point, and the cursor will flash
whenever only one point is selected. Some of the transformation functions (e.g., math function, waveform
math) can operate on a single sample point, and will transform a single sample point when only one is selected.
There are two ways to apply a transformation to an entire waveform.
a) For transformations that generate a dialog, check
the “transform entire waveform” box (usually
located toward the bottom of each dialog). This
will transform the entire waveform, regardless of
whether a single point, area, or the entire
waveform is selected.

b) For transformations that do not generate a dialog, use the Edit > Select all command prior to selecting the
transformation. This will transform the entire waveform for all of the transformation functions.
· Edit > Select All is not necessary when only a single point is selected prior to selecting the
transformation because AcqKnowledge will automatically apply the transformation to the entire
waveform since it is not possible to perform these transformations on a single point.

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Recently Used Transformations
The Transform > Recently Used submenu allows quick access to a user’s most recently used transformations
and analysis commands. The Recently Used submenu also appears at the top of the Transform submenu
available from the context menus of waveforms.
The submenu lists a default of five of the most recently used transformations, with the most recently executed at
the top of the menu. To adjust the number of recent transformations displayed, select Display > Preferences.

The recently used transformation listing is saved and restored across subsequent launches of AcqKnowledge. It
also is application wide: Executing a transformation in any graph will add that transformation onto the recently
used list. The recently used list is independent for each user account.

The recently used transformations can also be launched by the keystroke combinations appearing in the menu.
Digital Filters

FIR filters are linear phase filters, which mean that there is no phase distortion between the original signal and
filtered waveforms.
IIR filters are not phase linear filters, but are much more efficient than FIR filters in processing data. The IIR
filters are useful for approximating the results of standard biquadric filters of the form:
(as2 + bs + c) / (xs2 + ys + z)
These types of filters are commonly implemented in electronic analog circuitry. IIR filters are also used for
online filtering (discussed on page 146).
Ø See Appendix B for more information about the differences between these types of filters.
Adaptive filtering is a signal processing technique that processes two different signals in relation to one another;
see page 303 for details.
To understand how digital filters work, it is important to understand the nature of analog signals and their
frequency components. All analog signals are comprised of signals of various frequencies. A commonly used
analogy is that of the color spectra. Just as white light is made up of a variety of colors that have different
wavelengths (frequencies), physiological signals are comprised of specific signals with unique frequency
signatures.
For example, an electroencephalogram (EEG) recording is comprised of several different types of signals, each
of which has a different frequency signature. Alpha waves (one of the most studied EEG signals) have a
frequency range of about 8 Hz to 13 Hz. This means that alpha waves go through a complete cycle (from peak
to peak or trough to trough) anywhere from eight to 13 times a second.
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There are, of course, signals that have other frequency signatures in EEG data. Most types of physiological data
have a number of different frequency signatures present in the overall signal. In addition, frequency components
besides the signal(s) of interest are often present. In the U.S., it is not uncommon for 60 Hz electrical noise to be
acquired along with physiological signals (in other countries, AC interference is present at either 60 Hz or 50
Hz).
Use digital filtering to retain only the frequency components of interest and remove other data (whether it is
“noise” or merely physiological signals outside the range of interest).
It is important to note that the way in which data is filtered depends in large part on the sampling rate at which
the original data was acquired. For instance, if data was collected at 50 samples per second (50 Hz), it is not
possible to filter out 60 Hz signals.
In fact, data must be sampled at a rate equal to at least twice the frequency of the signal to be removed. So, if
data is to be collected and the information between 80 Hz and 120 Hz is to be removed, the data must be
sampled at 120 Hz*2, or 240 samples per second (or faster). Also, each channel of data is filtered separately, so
removing one type of data from one channel will not affect any other channels.
Digital filters can be divided into four general classes:
low pass band pass high pass band stop
Descriptions of these four classes of filters follow, with visual examples of how these filters work. In each of
the four examples, a single channel of data containing frequency components in three ranges (low frequency,
mid-range, and high frequency) is acquired.
§ Low frequency data, by definition, has slowly changing values, much like respiration patterns or core
temperature variations.
§ High frequency data, compared to low frequency data, is noticeably more “spiked,” much like an EMG
signal. The high frequency wave repeats itself about five times in the time it takes the low frequency
wave to repeat once.
§ Mid-range data falls somewhere in between these two extremes.
In the examples that follow, one possible way that these data could have been collected is if respiration were
measured, but the measurement was contaminated with high-frequency muscle movement and mid-frequency
signal coming from AC interference. The data is then passed through a filter, where some of the frequency
components are removed.
Low pass filtering
In the example below, a low pass filter attenuates the data above a given threshold, allowing only lower
frequency data to “pass” through the filter.
High
frequency
data

Low
Pass
Filter

Mid
frequency
data

Low
Cutoff
Low
frequency
data

Incoming data

Filtered data

High pass filtering
In the example below, a high pass filter removes the low and middle range data, but allows the high frequency
data to pass through the filter.

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High
frequency
data

High
Cutoff
Hipass
Filter

Mid
frequency
data

Low
frequency
data

Incoming data

Filtered data

Whereas the low pass and high pass filters retain data either above or below a given threshold, the next two
types of filters work with a range, or band, of data.
Band pass filter
The band pass filter, allows only the data within the specified range to pass through the filter. A band pass filter
is useful for retaining only specific waves from an EEG record. For example, to retain alpha waves, set the filter
to only pass data between 8 Hz and 13 Hz.
High
frequency
data

High
Cutoff
Band
Pass
Filter

Mid
frequency
data

Low
Cutoff
Low
frequency
data

Incoming data

Filtered data

Band stop filter
The band stop filter allows data to pass above and below the specified range. This type of filter is typically
applied to remove extraneous 60 Hz or 50 Hz noise from a data record.
High
frequency
data

High
Cutoff
Band
Stop
Filter

Mid
frequency
data

Low
Cutoff
Low
frequency
data

Incoming data

Filtered data

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FIR Filters

Digital filter dialog
When selecting an FIR filter type, the corresponding Digital Filter dialog will appear, allowing a number of
different filtering options to se selected.
1. Window. The Window popup menu presents a variety of filtering
algorithms. The filter default is set to a “Blackman” type. These
different Windows (described in detail in Appendix B on page 585)
allow fine tuning of the filter response.
2. Cutoff Frequency (Hz) (or threshold). Enter a fixed value or set to a
fraction of the sampling rate or to line frequency.
Sampling rate—frequency is set to a fraction of the sampling rate and
automatically updates when the sample rate is modified.
Line frequency—frequency is set to the line frequency at which the
data was recorded.
Fixed at —Fixed value guidelines are as follows:
· Low Pass Filter—data with frequency components below the
cutoff will pass through the filter, whereas frequency components
above the threshold will be removed. For low pass filters, the
default cutoff frequency is the waveform sampling rate divided by
eight and can be set to any value between 0.000001Hz and 0.5
times the sampling rate.
· High Pass Filter—data with frequency components above the
cutoff will pass through the filter, whereas frequency components
below the threshold will be removed. For high pass filters, the
default threshold is the waveform sampling rate divided by four
and can be set to any value between 0.000001Hz and 0.5 times the
sampling rate.
· Band-type Filters—a low threshold and a high threshold must be specified to define the band of data
(the frequency range) that is either passed or stopped, depending on whether it is a Band Pass or Band
Stop filter. In either case, the default for the low threshold is the waveform sampling rate divided by
eight and the default for the high threshold is the waveform sampling rate divided by four. The
threshold settings can take on any value from 0.000001Hz and 0.5 times the sampling rate, but the two
thresholds cannot be set to the same value and the high threshold must be greater than the low
threshold.
3. Number of Coefficients. Enter a fixed value or enable the optimize option.
· Fixed at—This determines how well the filter will match the desired cutoff frequency (or range). The
minimum number of coefficients is 3 and the maximum must be less than the total number of sample
points in the selected area. The software will truncate the maximum number of coefficients to the
highest odd number less than the total.
· Optimize for sample rate and cutoff—the number of coefficients is set as four times the sampling rate
divided by the cutoff frequency of the filter. Optimize does not necessarily produce the best quality
filter, but it takes less time.
The recommended number of coefficients is

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4 x (waveform sampling rate/lowest frequency cutoff for the filter)
For every filter except the band pass, the lowest frequency cutoff is equal to the specified cutoff frequency
for the filter; for the band pass filter, the lowest frequency cutoff is the low frequency cutoff setting. Filters
that use a small number of coefficients tend to be less accurate than filters that use a large number of
coefficients. Larger coefficients increase filter accuracy, but also increase the processing time required to
filter the data.
To see how changing the number of coefficients affects the way data is filtered, it can be useful to examine
the filter response patterns. In the example below, data was collected at 500 Hz and the band stop filter was
designed to remove 60 Hz noise using a low cutoff of 55Hz and a high cutoff of 65Hz. The same data was
band stop filtered using 39 coefficients (upper waveform) and then 250 coefficients (lower waveform).

Along the horizontal axis, the units are scaled in terms of frequency, with lower frequencies at the left of
the screen. The values along the vertical axis are scaled in terms of dB/V and indicate the extent to which
various frequencies have been attenuated.
In both filter response waveforms, there is a downward-pointing spike that is centered on 60 Hz. The
baseline of the filter response corresponds to a value of approximately 0 on the vertical axis, indicating that
the signals significantly above or below 60 Hz were not attenuated to any measurable extent. Observe that
the filter does not chop the data at either 55 Hz or 65 Hz, but gradually attenuates the data as it approaches
60 Hz.
For example, the upper waveform in the filter response plot represents data that was filtered using a value
of 39 coefficients. The slope is relatively shallow when compared to the lower waveform, which represents
a filter response performed with 250 coefficients. Although the filter that used 250 coefficients took slightly
longer to transform the data, the filter response pattern indicates that the data around 60 Hz is attenuated to
a greater degree. Also, the 250-coefficient filter started to attenuate data considerably closer to the 55 Hz
and 65 Hz cutoffs, whereas the default filter began to attenuate data below 55 Hz and above 65 Hz.
TIP: A good rule of thumb is to use a number of coefficients greater than or equal
to two times the sampling rate divided by the lowest cutoff frequency
specified. For example, if running a low pass filter at 1 Hz on data sampled at
100 Hz, choose at least (2 x 100/1) or 200 coefficients in the filter. Additional
coefficients will improve the response.
4. Show Filter Response. When checked, this option generates a plot of the
filter response in a new window, labeled “Frequency Response” (see
example above).
§ Units: Select linear units or dBV.
5. Don’t modify waveform. This option is useful in conjunction with the “Show Filter Response” option.
When both boxes are checked, AcqKnowledge will produce a plot showing the filter response, but will not
modify the waveform. This allows for repeatedly specifying different filter options (without modifying the
waveform) until the desired frequency response is achieved.
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6. Filter entire wave. If this option is checked, AcqKnowledge will filter the entire wave and replace the
original. To keep the original, duplicate it prior to filtering.
IIR Filters
To access the IIR filter dialog, click the Transform menu, scroll to select Digital Filters, drag right to IIR and
drag right again for the filter options. For all filter types, the software will limit the frequency setting so it
cannot exceed one-half the channel sampling rate. For real-time filter options, see page 146.
X

Low Pass and High pass

X

Pass data that falls below or above the specified standard. The Low Pass default is
waveform sample rate/8; the High pass default is waveform sample rate/4.
Band Pass (low + high)
Pass a variable range of data. Specify a low frequency cutoff and a high frequency
cutoff to define the range or “band” of data that will pass through the filter;
frequencies outside this range are attenuated. For the Band Pass Low + High filter,
the low default is waveform sample rate/8 and the high default is waveform sample
rate/4.
§ This filter is best suited for applications where a fairly broad range of data is to
be passed through the filter. For example, apply to EEG data to retain only
alpha wave activity.
Band Pass (single freq)
Requires only a single frequency setting, which specifies the center frequency of
the band to be passed through the filter. The “width” of the band is determined by
the Q setting of the filter (discussed in detail below). Larger Q values result in
narrower bandwidths, whereas smaller Q values are associated with a wider band
of data that will be passed through the filter. This filter has a bandwidth equal to
Fo/Q, so the bandwidth of this filter centered on 50 Hz (with the default Q=5)
would be 10 Hz. Although functionally equivalent to the Band Pass (low + high)
filter, this filter is most effective when passing a single frequency or narrow band
of data, and to attenuate data around this center frequency. The Band Pass (single
frequency) default is waveform sample rate/8.
Band Stop (single freq)
Defines a range (or band) of data and attenuates data within that band (the opposite
function of a band pass). This filter is implemented in much the same way as the
standard Band Pass, whereby a center frequency is defined and the Q value
determines the width of the band of frequencies that will be attenuated. The Band
Stop (single frequency) default is waveform sample rate/8.
Q coefficient
The online filters are implemented as IIR (Infinite Impulse Response) filters, which
have a variable Q coefficient. The Q value entered in the filter setup box
determines, in part, the frequency response of the filter. This value ranges from
zero to infinity, and the “optimal” (critically damped) value is 0.707 for the Low
Pass, High pass and Band Pass filters. A Q of .707 for any of these filters will
result in a second order Butterworth response. The Q is set to a default of 5.000 for
the single frequency Band Pass and Band stop filters. For more details about the Q
setting, see the Appendix.
Sampling rate
Sets the Frequency to a fraction of the sampling rate and automatically updates when the
sample rate is modified.
Line frequency
Sets the Frequency to the line frequency at which the data was recorded.

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Adaptive Filtering
Adaptive filtering is a signal processing technique that
processes two different signals in relation to one another
and can be used for noise estimation, noise reduction,
general-purpose filtering, and signal separation. Adaptive
filtering creates efficient high-quality filters with a minimal
number of terms, which can be very useful in blocking
mains interferences or other known periodic disturbances.
§ Useful for noise filtering where it is possible to acquire
a signal that is correlated to the noise (similar to the
way noise-cancelling headphones detect and remove
outside noise). Applications include removing EMG
from ECG or EOG from EEG.

Ü See the Adaptive Filtering Calculation
Channel on page 161.

The weights within an adaptive filter are modified on a step-by-step basis. AcqKnowledge uses the N-tap FIR
adaptive filter, with coefficients updated using least means squares (gradient) feedback.
Source signal
The source channel will be replaced by the adaptive filter results.
Noise signal
The noise channel is the signal that is correlated with the noise to be eliminated from the Source; it is
not modified by adaptive filtering.
Source and Noise channels must have the same sampling rate.
Order
Specify a positive integer for the number of terms to be used in the internal FIR filter.
Step size
Provides mu, the rate of adaptation of the coefficients within the FIR filter.
Comb Band Stop Filter
Comb Band Stop filters out a fundamental frequency and its overharmonics (integer multiples of the base).
Resonance, aliasing, and other effects may generate interference at multiples of a base frequency. The Comb
Band Stop filter combines all the required filters instead of requiring a separate filter for each interfering
overharmonic.

Transformation Dialog

Calculation Channel Dialog

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Comb Band Stop filters remove a fundamental frequency and its overharmonics (e.g., integer multiples of the
base frequency) from a signal, and are useful for removing noise. AcqKnowledge approximates a Comb Band
Stop filter by cascading a series of IIR Band Stop filters, and is limited to removing frequencies and
overharmonics. The number of filters used can be fixed at a particular number (e.g., limiting the number of
harmonics to filter out) or configured to automatically remove all possible harmonics for any given sampling
rate.
· Mac OS — Use the "Comb Band Stop Filter" Automator action to integrate Comb Band Stop
filters into Workflows.
For a given base frequency
and quality factor Q, the comb filter approximation will be given by the set of
following formulas:

y = (Fw o F2w o F3w × × × oFkw )( x )

where F represents a standard two-tap IIR band stop filter for the frequency
with coefficients
computed using the quality factor Q.
The number of overharmonics of the base frequency to be removed is given by the integer value k. The
maximum allowable number of overharmonics may be automatically determined given the sampling
frequency f s:
êf ú
=
k max êê 2ws úú
ë
û

This limits the maximum overharmonic frequency to be less than the Nyquist of the sampling
frequency.
After the first comb filter is performed, the most recently used settings for the comb filter will be displayed,
(except for “Transform entire wave,” which will be reset each time the dialog is opened).
Textual export will include the source channel, base frequency, quality factor, and number of harmonics.
Comb Band Stop Filter Dialog
number of samples

Width of the selection.

@ samples/sec

Waveform sampling rate of the source channel.
· The channel sampling rate of the calculation channel can not exceed the channel
sampling rate of the source channel. Downsampling will be applied to the source
channel prior to comb filter processing, if required, and all Nyquist frequency
restrictions will be determined from the calculation channel sampling rate.

Frequency

Fixed—The comb filter will remove this base frequency and integer multiples of this
frequency.
· Must be positive and less than the Nyquist frequency (half the sampling rate).
Sampling rate—Sets the frequency to a fraction of the sampling rate and automatically
updates when the sample rate is modified.
Line frequency—Uses the line frequency at which the data was recorded.

Q

Quality factor used when computing the coefficients of the IIR notch filters.
· Must be positive.

all up to Nyquist

Removes all integer multiples of the base frequency. This will include all multiples of
the base frequency that are less than the Nyquist frequency.

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Part C — Analysis Functions

Harmonics

305

Removes the base frequency and integer multiples of the base frequency up to and
including the multiple contained in the edit field
· Must be an integer greater than 0 and must not exceed k max
· The final multiple must be less than the Nyquist frequency. If it is not, the input will
need to be corrected before the comb filter can be applied.

OK

If the settings are valid, executes the comb filter transformation. Verification of certain
calculation channel parameters does not occur until the start of acquisition as sampling
rates may be changed after calculation channels are configured.
Prior to the start of acquisition, the following will be checked:
· source channel to ensure it is still being acquired.
· base frequency of the comb filter to ensure it is less than the Nyquist frequency of
the channel sampling rate.
· if the user has manually specified that a fixed number of overharmonics should be
used, the number of overharmonics to ensure the highest used overharmonic does
not exceed the Nyquist frequency of the channel sampling rate.
If any of the parameters are invalid, a prompt will be displayed indicating which settings
are incorrect and must be fixed for the acquisition to be started.

Cancel

Quits without modifying any data.

Source

All enabled analog, digital, and lower-index calculation channels.

Label

When the calculation type of a channel is changed to comb filter, the title of the channel
will be replaced with the default label “Cn –Filter” where n is the index of the calculation
channel.
· Must be 40 characters or less.

Preset

Displays the title of any Calculation Preset currently applied to the calculation channel.

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Fourier Linear Combiners
Transform > Fourier Linear Combiners:

Ü See FLC Calculation Channel
options on page 160.
Ü See FLC references on page 307.
X

X

X

X

Fourier Linear Combiners are linear combinations of
adaptable sinusoidal functions that are particularly well
suited to processing cyclic data. Sine and cosine harmonics
of a base frequency are summed together and the order is
the fixed number of harmonics used in the model. Step size
provides mu, the gain factor used to adjust the weights of
the harmonics at each processing step. Step sizes must be
much less than 1 for the system to converge. As step sizes
decrease, relaxation time lengthens. The FLC model is
adjusted based on the source data using least means square
(LMS) feedback and the bias compensates for DC offset.
Basic FLC
Simple summation of fixed numbers of sines and cosines; uses
harmonics of a fixed frequency and adjusts weighting coefficients
of the mixture.
Operates on a single channel at a time.
Well suited for extracting data of a known frequency band from a
signal with a stable frequency.
§
Use as an adaptive noise filter to remove non-periodic and
semi-periodic noise uncorrelated to the base harmonic
frequency.

Scaled FLC
Fundamental harmonic frequency can vary on a cycle-to-cycle
basis. The frequency remains fixed within a single cycle and must
be known before processing.
Scales the harmonics used in each cycle based on cycle
boundary events (defined through the Cycle Detector, ECG
Analysis, or manually). Events from one signal can be used to
drive analysis of another signal.
Well suited for signals with detectable boundaries, such as ECG.
§
Use to extract information that is tightly coupled to other
cyclic signals, such as extracting ICG based upon
Knowledge of the RR cycles of the ECG.

Weighted-Frequency FLC
Base frequency of the harmonics is variable; adapts the
frequency in response to the input signal using LMS feedback;
the frequencies are similarly adjusted to the amplitudes.
Operates on a single channel at a time.
Well suited for modeling periodic signals of an unknown and
potentially varying frequency and/or amplitude.
§
No cycle boundaries or frequencies need to be predetermined.

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Coupled WFLC/FLC
Runs a WFLC on the signal to determine the harmonic frequency and
then runs the result through an FLC using the computed harmonic.
The second FLC can be run on the same or a different channel.
The transformation will occur in the channel designated as “ Output.”
Well suited for real-time extraction of information from one signal
based upon the frequencies contained in another signal.

§
§

Use to remove movement noise from ECG.
Unique configurations can be established with two input signals,
one for frequency and one for amplitude.

FLC References
The basic Fourier linear combiner (FLC) is described by Vaz and Thakor.
Ü Christopher A. Vaz, and Nitish V. Thakor, “Adaptive Fourier Estimation of Time-Varying Evoked Potentials,”
IEEE Trans. Biomed. Eng., VolBME-36, pp. 448-455.
The weighted-frequency Fourier linear combiner (WFLC) and the coupled weighted-frequency Fourier linear combiner
(CWFLC) are described by Riviere, Rader, and Thakor.
Ü Cameron N. Riviere, R. Scott Rader, and Nitish V. Thakor, “Adaptive Canceling of Physiological Tremor for
Improved Precision in Microsurgery,” IEEE Trans. Biomed. Eng., Vol BME-45, pp. 839-846.
The scaled Fourier Linear Combiner (SFLC) is described by Barros, Yoshizawa, and Yasuda.

Ü

Allan Kardec Barros, Makoto Yoshizawa, and Yoshifumi Yasuda, “Filtering Noncorrelated Noise in
Impedance Cardiography,” IEEE Trans. Biomed. Eng., Vol BME-42, pp. 324-327.

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Math Functions
AcqKnowledge supports a wide range of mathematical and computational
transformations after an acquisition has been completed. Unless otherwise
noted, each of these functions applies only to the selected area of the selected
channel. If no area is selected (i.e., a single data point is selected), the cursor
will blink and AcqKnowledge will transform the entire wave. If a math function
attempts to divide by zero, a zero will be returned.
For complex transformations involving multiple functions, using the Expression
transformation is recommended (see page 323 for details).
The following table describes the commands available in the Transform > Math functions menu:
Transform > Math

Explanation of Command

Abs (Absolute Value)

Computes the absolute value of the data. All negative data values are made
positive, with no change in magnitude. This function can be used to rectify data.

Atan (Arc Tangent)

Returns the arc tangent of each data point in radians. This rescales the data such
that the range is from -p/2 to p/2.

Connect endpoints
(Connect the endpoints)

Draws a line from the first selected sample point to the last selected sample point
and interpolates the values on this line to replace the original data. The connect
endpoints function is useful for removing artifacts in the data or in generating
waveforms.
In the example below, the “noise spike” in the data is an undesired measurement
artifact that should be removed. The Cut operation will remove data, but the
subsequent data will be shifted to the left. Connect endpoint preserves the time
series of data on the horizontal axis by connecting the edges of the selected area..

Area selected before (top) and after (bottom) connect endpoints function

Exp (Exponential)

Computes the function ex, where x is the waveform data and e is 2.718281828.
This is the base of the natural logarithms.

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Limit (Limit data values)

“Clips” data outside the range specified by the set of boundaries in the limit dialog.
This operation prompts the user for an upper and lower limit. Any data values
outside these limits will be clipped. To limit only one boundary (high or low), set
one edge to the desire level and the second boundary beyond the Max/Min value
of the data within the selected area. For example to set all negative values to zero
and leave the positive values unchanged: set the lower limit to zero and the upper
limit to a value greater than max for the selected area.

Ln (Natural Logarithm)

Computes the natural logarithm of the selected section. The inverse of this function
is the exponential function, Exp.

Log (Base 10 Logarithm)

Computes the base 10 logarithm of the selected section.
In order to perform the inverse of this function, which would be 10x, use the
Waveform Math power operator with the constant k=10 as the first operand and
the waveform data as the second operand.

Noise

Converts the selected section into random data values between –1.0 and +1.0.
This is mainly useful for creating stimulus signals and other waveforms.

Sin (Sine)

Calculates the sine of the selected section. The data is assumed to be in radians.

Sqrt (Square Root)

Takes the square root (Ö) of each data point in the selected section.

Threshold (Threshold
data values).

Transforms all data points above the threshold to +1 units, and converts all values
below the lower threshold to 0 units. Once the data crosses a threshold it will
continue to be set to +1 for the upper cutoff and 0 for the lower cutoff, until it
crosses the opposite threshold. The most common application of this function is to
serve as a simple peak detector, the results of which can be used in rate or phase
calculations.
Threshold Algorithm
Assume a domain variable t Î {t start ,t start + 1,t start + 2,K } with tstart being an
integer, a real-valued signal y(t) defined for all t, and two real valued levels ylow and
ymax satisfying the relation y low £ y high .
Define the threshold function thresh(t) function such that:

ì1 y(t start ) ³ y low
thresh(t start ) = í
î0 y(t start ) < y low
ì0
y(t) < y low
ï
thresh(t) = í1
y(t) > y high
ïthresh(t -1) y £ y(t) £ y
î
low
high

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Template Functions

The Template Functions are useful for comparing waveforms. Technically, the template functions provide
correlation, convolution, mean square error, inverse mean square error, remove projection, normalized cross
correlation transformations of a template waveform against another waveform. To activate the full template
menu, select an area and then select set template.
Set Template
Use the following ECG waveform as an example and contains an abnormality. After detecting an abnormality,
this operation can help detect if there are other (similar) abnormalities in the recording. To do that, it’s
necessary to select the pattern to search for, and then compare that pattern to other data sets in the file.
Selecting a section of a wave to be used as a template:
1) Highlight the section to be used as a pattern.

2) Click the Transform menu and choose Set template from the Template functions submenu. This copies
the selected portion into a buffer for subsequent template functions
3) Select the waveform and position the cursor at the beginning of the data.
4) Choose Correlation from the Template functions submenu. The center waveform in the graph below
shows the result of the correlation.
Note the higher amplitude peaks where the template data more closely matches the waveform. The lower
waveform illustrates the mean square error function, which is similar to the correlation function.
This indicates that there are two abnormal beats in the waveform. The first one appears at about 3 seconds
and is the one used as a template; the second one appears at about 11 seconds.

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Result of correlation and mean square error functions
5) Use the zoom tool to inspect the abnormalities more closely.
Remove mean
A drifting baseline can be problematic when comparing waveforms. The effectiveness of a comparison of a
template or waveform with a slowly drifting baseline will be increased by applying the Remove mean template
function. The remove mean option causes the mean amplitude value of the template and the compared section
of the waveform to be subtracted from each other before the sections are compared. This way, a large baseline
offset will have very little effect on the comparison. This option is toggled every time it is selected and is
enabled when a check mark is present.
For example, the following graph shows the original waveform at the top, the correlated waveform with mean
removal in the middle, and the same correlation without mean removal at the bottom. Note how the mean
removal effectively compensates for the drifting baseline in the original waveform.

Correlation with and without mean removal

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Template algorithms
The template functions are: correlation, convolution, mean square error, inverse mean square error, normalize
cross correlation, remove projection and adaptive template matching.
a) Correlation is a simple multiplication and sum operation. The template is first positioned at the cursor
position in the waveform to be correlated. Each point in the template waveform is multiplied by the
corresponding point in the data waveform (the waveform to be correlated) and summed to produce the
resulting data point. The template is then moved one data sample forward and the operation is repeated to
produce the next resulting data point. The resulting data points replace the waveform to be correlated.
The correlation function algorithm can be expressed by the following formula, where foutput(n) is the
resulting data point, ftemplate(k) is the template waveform data points, and K is the number of data points
in the template:
K

foutput(n) = å ftemplate(k) * fwaveform(n)
k =1

b) Convolution is identical to the correlation function except that the template waveform is reversed during the
operation. This function is not generally useful by itself, but can be used as a building block for more
sophisticated transformations. The convolution function algorithm can be expressed by the following
formula, where foutput(n) is the resulting data point, ftemplate(k) is the template waveform data points, and
N is the number of data points in the template:
N/ 2 - 1

foutput (n) =

åf

template

(-k) * fwaveform (n + k)

k = -N/ 2

c) Mean square error positions the template at the cursor position in the waveform to be compared. Each point
in the template waveform is subtracted from the corresponding point in the waveform to be compared. The
result is squared and summed to produce the resulting data point. The template is then moved one data
sample forward and the operation is repeated to produce the next resulting data point. The resulting data
points replace the waveform.
The mean square error function tends to amplify the error (or difference) between the template and the
waveform, which makes it useful when looking for an extremely close match rather than a general
comparison. When a match is found, the mean square error algorithm returns a value close to zero.
The mean square error function algorithm can be expressed by the following formula, where foutput(n) is
the resulting data point, ftemplate(k) is the template waveform data points, and K is the number of data
points in the template:
2

K

foutput (n) =

å [f

template

(k) - fwaveform (n)]

k=1

d) Inverse Mean square error simply inverts the result of the mean square error algorithm. Accordingly, when
this algorithm finds a match between the template and the data, the algorithm returns the inverse of a value
close to zero and, typically, a large positive spike will occur at the point of the match.
e) Remove Projection Template removes the projection of a reference signal from another part of a signal
(whereas the other template functions revolve around the comparison of a portion of a signal against a
reference signal).

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Remove Projection treats the template in memory as a vector. The projection of the selected area onto the
template is computed as a vector dot product. This projection is then removed from the source data.
After a remove projection transformation, the remaining data consists of the part of the signal that is the
most unrelated to the template.
Remove Projection can be useful for emphasizing signal differences. For example, it may be useful for
exploring differences in an arrhythmia in comparison to a normal reference beat. It may also be useful as a
denoising building block by removing the projection of a signal against idealized noise in the template.
The number of samples in the template should match the number of samples in the selected area of source
data.
·

Dot product is undefined for vectors of mismatched dimensions.

·

If the template is longer than the selected source data, the template will be shortened (for that single
transformation; it will be restored afterward) so its length matches the selection width.

·

If the selection is longer than the template, any data occurring after the end of the template will not
be transformed.

To create a Remove Projection template:
1. Highlight the portion of data to be used as the reference signal.
2. Transform > Template > Set Template.
3. Highlight the portion of the data to be analyzed.
4. Transform > Template > Remove Projection.
f) Normalized cross-correlation (NCC) is useful when searching for variations in the signal. Regular crosscorrelation (Transform > Template > Correlation) can exhibit large amplitude spikes when the energy of a
signal varies greatly or amplitudes change suddenly, causing jumps that are not necessarily indicative of a
match with the template. Normalized cross-correlation is a statistical method that can help resolve these
issues by applying normalization to both the template and signal being searched. This reduces the effect of
amplitude variation in the result, making normalized cross-correlation useful for template matching
purposes.
This transformation computes the windowed normalized cross-correlation, and results in a value between -1
to 1, which indicates the linear fit of the data set. Normalized cross correlation is defined as:
L

g=

å ( x - x )( y
i

i =0

L

i

- y)

L

å(x - x) å ( y
2

i =0

where

i

i =0

i

- y )2

x = template
y = signal
L = length
= mean value of the signal f

At the end of the transformation, the source data will be replaced with the sliding NCC values. Data outside
the selected area will be left unmodified. If the selected area is zero width when the transformation is to be
executed, the entire waveform will be transformed.
If selection is shorter than the template, the missing data at the right end of the selected area will be filled
with zero padding until it matches the length of the template. This padding occurs in memory and will not
affect the source data in the graph. The same zero padding is used when computing NCC at the end of every
selected area when the template is running off the end of the data. This zero padding should trend the NCC
to zero at the right edge of the transformed area, in most cases.

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Adaptive Template Matching
Many different types of physiological analysis involve
locating repetitive features within a signal. These may
occur at regular intervals or may occur sporadically.
Sometimes the areas of interest may be intermingled with
other results, such as occasional heartbeat arrhythmias
occurring in a long-term ECG recording. Template
matching is one frequently used approach for locating
areas of waveforms that exhibit certain characteristics. An
example selection is specified as the input template. Then,
using cross correlation or related methods, the areas of an
arbitrary wave that most strongly match the example can
be located.
Adaptive Template Matching allows the template to vary
during execution to incorporate changes to the
morphology of signal attributes. The adaptation consists
of a moving average of a number of the most recent
matching attributes. A template match will be defined as a
peak in the windowed normalized cross correlation of the
adapting template with the signal.
Normalized cross correlation helps to eliminate artifact due to baseline shift and changes in overall power
and amplitude. This heuristic is sensitive to waveform morphology instead of amplitude.
Template width
The number of samples in the template that will be used as the initial template for the transformation, as
set using Transform > Template Functions > Set Template.
Note One template is shared globally by all graphs and data views in AcqKnowledge.
Average template window size
Input positive integers only. Provides the number of previous matches to be used for constructing the
average template estimate.
Correlation threshold
Floating point input in the range -1 to 1. Provides the threshold used for peak detection on the
normalized cross correlation signal. Corresponds to r in the algorithm description.
Normalize matching data before updating average template
Toggle check box. When enabled, the reference set normalization algorithm option is used. This
performs mean subtraction and unit magnitude normalization to every member of the reference set prior
to constructing the average template. This option can help to compensate for unintentional weighting of
the windowed average template towards larger amplitude data.
Reject matches closer than
When checked, the minimum match interval algorithm option is used. This rejects matches that are too
close together and can compensate for degeneration of the algorithm into continual matching due to
signal self similarity. The edit field contains the minimum width that must separate valid matches. The
width must always be a positive number. The popup menu specifies the units of the separation interval.
Its contents are dependent on the horizontal axis type:
Time (seconds & HH:MM:SS)
Frequency
Arbitrary
samples
samples
samples
milliseconds
Hz
arbitrary units
seconds
minutes
hours

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Output
Show normalized cross correlation values provides access to the sequence of correlation values that is
examined by the heuristic for potential matches. Viewing the normalized cross correlation signal can
provide feedback that is useful for proper threshold selection and for detecting whether the heuristic has
fallen into one of its degenerate cases (e.g. NCC signal hovering around the threshold for extended
periods of time). When checked, a new channel will be added into the graph containing the normalized
cross-correlation values computed by the algorithm. The channel will be labeled “NCC Values.”
Generate synchronization waveform allows for the generation of spike trains. The value of the wave in
the graph will be zero by default. At each sample position where a match with the average template is
triggered, the wave value will be set to one. A single sample position set to 1 indicates a single valid
match. This synchronization wave can be used in conjunction with the cycle detector to perform further
data reduction, input to the rate detector for computing match frequencies, and other analysis.
Define events at match locations output allows placement of an event on the waveform being analyzed
at the location of each valid match. The event output can allow adaptive template matching to be used
to construct classifiers that provide event locations for further data reduction with the cycle detector.
§ Type—Used to choose the type of event that will be defined at match locations. Displays the
standard hierarchical menu list of event types.
§ Label—Label to be given to events defined at match locations.
Transform entire wave
When checked, the entire waveform will be analyzed. When unchecked, only the selected area will be
transformed.
Integral
Integral is essentially a running summation of the
data. Each point of the integral is equal to the sum
of all the points up to that point in time, exclusive
of the endpoints, which are weighted by half. The
exact formula is below, where f( ) is the data values
and DTs is the horizontal sampling interval
(reciprocal of the sample rate):
n -1

foutput (n) =

åf

input

(k) + [[finput (n -1) + finput (n)] / 2]* DTs

k=1

The units will be (amplitude units • horizontal units). The integral function can be used to compute the area
under the curve in a continuous fashion. For instance, in data acquired by an accelerometer, the integral of the
data would be the velocity, and the integral of the velocity would be the distance. As with all transformations,
this function can be applied to either a selected area or to the entire waveform.

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Derivative
Derivative calculates the derivative of the selected area of a waveform. Since high
frequency components return nonsensical results in a derivative, a low pass
filtering function is included in the Derivative function (see page 298 for more
information on low pass filters). Derivative is based on an FIR filter
implementation.
The Filter Response for a Derivative transformation will be displayed in linear
units or in dbV. The Derivative FIR filter frequency response will appear as a
linearly increasing magnitude up to the point of the specified cutoff frequency,
at which point, the filter magnitude will drop off sharply.
X

Derivative may provide better results than Difference; if high frequency noise is present in the signal.
Cutoff Frequency
The value entered in the cutoff frequency box should be roughly equivalent to the highest
frequency component of interest present in the time series data. The default cutoff
frequency is 0.125 times the waveform sampling rate.
Sampling rate—Sets the frequency to a fraction of the sampling rate and automatically
updates when the sample rate is modified.
Line frequency—Uses the line frequency at which the data was recorded.
# of Coefficients
Fixed—The default number of coefficients is (4 x waveform sampling rate)/Cutoff
Frequency. As the number of coefficients (Q) increases, the Derivative becomes more
accurate. Fixed can produce better filters but may take longer to execute.
Optimize for sample rate and cutoff—Estimate the number of coefficients as four times
the sampling rate divided by the cutoff frequency of the filter. Optimize does not
necessarily produce the best quality filter, but takes less time.

Units

Select linear units or dbV.

TIP: A good rule of thumb is to use a number of coefficients greater than or equal to
two times the sampling rate divided by the lowest cutoff frequency specified. For
example, if running a low pass filter at 1Hz on data sampled at 100 Hz, choose at
least (2 x 100/1) or 200 coefficients in the filter. Additional coefficients will
improve the response.

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Integrate
The Integrate transformation operates
the same as the Integrate calculation—
see page 134, except it does not have a
Max Cycle option, which is not relevant
post-acquisition, and Reset via channel
with mean subtraction enabled functions
differently online and offline.
X

X

Root mean square is implemented as:
Sqrt(sum(x^2)/(n))

Reset
Online

Offline

Mean subtraction causes the online version to be delayed by the mean cycle length. It waits for
that period of time to pass so it can determine a mean value for the initial cycle, and it then
tries to re-compute this mean for each cycle. If the resets are too short or too long, the window
expires and the processing halts again until a new mean can be recomputed. Online processing
may reset from threshold crossing in the control channel or window expiration when it loses
mean tracking.
Since all the data is available, the mean is computed from the data in the channel and doesn't
delay the signal. Also, since it isn’t doing windowed means, there are no window expiration
events that are inserted. Offline processing may reset from threshold crossing in the control
channel.

Output Reset
Enable the
checkbox
option to
create an
Event at each
signal reset.

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The Integrate formula is the same in the calculation (online, real-time) mode and the transformation (off-line,
post-processing) mode; it varies only based on the parameters selected.
Notes
· For the first points, value of index “i” will be less than or equal to zero; it means that for
summation the result will only contain values beginning with f (x1 ) .
o For the first point for summation: f (x -1 ) , f (x0 ) , f (x1 ) .
f (x -1 ) and f (x0 ) - don’t exist, resulting in: f (x1 ) .

o For the second point for summation : f (x0 ) , f (x1 ) , f (x 2 ) .

f (x0 ) - doesn’t exist, resulting in: f (x1 ) + f (x 2 ) .

· The Integrate formula is implemented as a Standard Deviation formula (see
mathworld.wolffram.com > Wolfram Research > equation 5 at
http://mathworld.wolfram.com/StandardDeviation.html.
H

H

· The Root Mean Square formula is identical to the Standard Deviation formula, but without mean
removal; this is the n-1 definition.
o For an explanation of n-1 versus n in the formula, see notes in:
http://duramecho.com/Misc/WhyMinusOneInSd.html
o For a window size n, to convert from the n-1 definition to the n definition, use (n - 1)
H

n

· The formulas to calculate RMS are optimal
for data with a zero mean (typical for
biopotential data). Data with a non-zero
mean can be rescaled with the Transform
option Rescale. Choose Transform >
Rescale, and then enter the following
parameters:
Input value
Map
(Scale) value
10
7.07107
-10
-7.07107
1. Via samples, no extra parameters selected

F (x j ) =

j

å f ( x ) * Dx

i = j - s +1

i

Where:
i - index for source values (***the real range is 1..j);
j - index for destination values (1..n);
n - number of samples;
xi , x j - values of points at horizontal axis;

f ( xi ) - values of points of a curve;

F (x j ) - integrated values of points of a curve;
s – number of samples to average across;
Dx =

x n - x1 - horizontal sample interval;
n -1

x n , x1 - values at horizontal axis at the endpoints of selected area.

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See Notes on page 318

Integrate formulas, continued…
2. Via samples, rectify
j

F (x j ) =

å ABS ( f (x )) * Dx
i

i = j - s +1

X

Where:
i - index for source values (***the real range is 1..j);
j - index for destination values (1..n);
n - number of samples;
xi , x j - values of points at horizontal axis;

f ( xi ) - values of points of a curve;

F (x j ) - integrated values of points of a curve;
s - number of samples to average across;
Dx =

xn - x1
- horizontal sample interval;
n -1

x n , x1 - values at horizontal axis at the endpoints of selected
area.
3. Via Samples, root mean square (RMS)
Where:
j
i - index for source values (***the real range is 1..j);
( f (xi ))2
i = j - s +1
j
- index for destination values (1..n);
F xj =
n
- number of samples;
s -1
xi , x j - values of points at horizontal axis;

( )

å

f ( xi ) - values of points of a curve;

F (x j ) - integrated values of points of a curve;
s - number of samples to average across.
4. Via samples, root mean square, remove baseline

F (x j ) =

j
é
ù
f ( x m )ú
å
ê
j
å ê f (xi ) - m = j - s+k1 úú
i = j - s +1 ê
ê
ú
ë
û
s -1

2

Where:
i and m- indexes for source values (***the real range is 1..j);
j - index for destination values (1..n);
n - number of samples;
xi , x j - values of points at horizontal axis;

f ( xi ) - values of points of a curve;

F (x j ) - integrate values of points of a curve;
s - number of samples to average across.
k - coefficient: for the first few points that have index j < s k=j,
for the other points with j > =s k=s

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Integrate Timed Reset Formulas
Given an input signal x with sampling rate expressed in Hertz to be reset every m samples, the timed reset
integrate output O is given by the following recursive formulas indexed in terms of samples evaluated with data
starting at a starting sample position j:

The default scaling factor applied to the signal x matches the rescaling applied by the integrate reset via channel
processing. When acquiring the first segment of data into a graph, j is set to 0. For subsequent segments, j is
set to the index of the first sample of new data acquired into the graph.
If rectification is enabled, the formula will be changed to take the absolute value of the source prior to the
integration:

Smoothing

The smoothing function is a transformation that computes the moving average of a series of data points and
replaces each value with the mean or median value of the moving average “window.” This has the same effect
as a crude low pass filter, the advantage being that there is less change to shape and amplitude of the original
waveform.
Samples
AcqKnowledge allows the user to set the width of the moving average window (the number
of sample points used to compute the mean) to any value larger than three. By default, this is
set to three samples, meaning that AcqKnowledge will compute the average of three adjacent
samples and replace the value of each sample with the mean or median before moving on to
the next sample. For data acquired at relatively high sampling rates, it is recommended to set
the smoothing factor to a higher value, since smoothing three sample points when data is
collected at 1000 Hz will only average across three milliseconds of data, and will typically do
little to filter out noise. To set the size of the window, enter a value in the Transform >
Smoothing dialog.
This function is most effective on data with slowly changing values (e.g., respiration, heart
rate, GSR) when there is noise apparent in the data record.
Mean value
Mean value smoothing is the default and should be uses when noise appears in a Gaussian
distribution around the mean of the signal. The Mean value smoothing formula is shown
below, where “m” is the number of points in the window and “n” is the sample number:

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k =n +[m-1)/2]

f

(n) =

output

åf

(k) / m

input

k = n-(m/2)

Median value

Use Median value smoothing if some data points appear completely aberrant and seem to be
“wild flyers” in the data set.
The Median value smoothing formula is shown below, where “m” is the number of points in
the window and “n” is the sample number:

f

(n) = median (n - [m/2]; n + [m/2])

output

Watch the AcqKnowledge Smoothing video tutorial for a detailed demonstration of this feature.
Difference

The Difference function measures the difference (in amplitude) of two sample points separated by an arbitrary
number of intervals. The difference is then divided by the total interval between the first selected sample and
the last selected sample.
When the difference transformation is selected, a difference interval dialog will be generated and the number of
intervals between samples can be entered (default of 1).
For data with no high frequency components, a 1-interval difference transformation approximates a
differentiator.
The formula for the difference transformation is shown below, where “m” is the number of intervals difference,
[ ] rounds the integer down, “n” is the sample number, and DTs is the horizontal sampling interval:

foutput(n) = finput(n + [m/2])—finput(n—[(m+1)/2])
(DTs * m)
Example for boundary values when
m = 3:

Note:

foutput(0) = (finput(1)—finput(0)) / (DTs * m)
foutput(1) = (finput(2)—finput(0)) / (DTs * m)
foutput(2) = (finput(3)—finput(0)) / (DTs * m)

If an odd number is entered
(K = odd):

foutput(K) = (finput(K+1)—finput(K –2)) / (DTs * m)

If an even number is entered
(K = even):

foutput(K) = (finput(K+2)—finput(K –2)) / (DTs * m)

The online (real-time) Difference calculation is calculated differently because projected values are not
available. The online Difference formula is:

foutput(n) = finput(n –m)—finput(n) / (DTs * m)
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Using the default difference setting of 1 interval will produce a “DP/DT” waveform when the
transformation is applied to a blood pressure or similar waveform.

Resample

Variable sampling rate and the flexible acquisition speeds of hardware units can create data sets that are at
different sampling rates. For some types of data analysis, the data must be resampled to a common sampling
rate. AcqKnowledge has resampling facilities with Transform > Resample Graph; Transform > Resample
Waveform, and Pasting between graph windows of different sample rates when the “Interpolate pastings
between graphs” Preference is enabled (via Display > Preferences, page 467).
AcqKnowledge provides three interpolation methods for resampling data. Any changes made to the interpolated
pastings between windows Preference and the interpolation method used in the Preferences dialog will be
retained across launches of the software.
Padding—Padding will use the closest original value of the waveform to the left of the new sample
position for the value, constructing a padded square save as the data is resampled. Padding is desirable
when it is imperative no new data or data approximations get introduced into an analysis.
Linear—Linear interpolation is the default; previous software versions generated any missing data via
linear interpolation. This method uses the sample points of the old waveform as the endpoints of a line.
Missing data points are approximated from points lying on this linear segment.
Cubic spline—Cubic spline interpolation will construct a spline for the entire data set and use the values of
this spline as the new waveform values. A natural fit spline is used that keeps zero second derivative at the
endpoints of the fit. Cubic splines are useful when the analysis requires data with a smooth derivative.
Resample Graph
Apply an arbitrary, user-defined sample rate to all waveforms present in a file.
§ This option will adjust as needed the channel sampling rate as well as the acquisition sampling rate.
Resample Waveform
§ For Resample Waveform, the highest rate that can be entered is the Acquisition Sample Rate.
Resamples the active channel to a different rate. Resampling data maintains the same time scale but
changes the number of samples per second. This option can be used to increase the number of sample points
per interval (usually samples per second). When this is applied, AcqKnowledge will interpolate between
sample points to adjust to the new rate. This will add data points, although not necessarily more
information.
§ Resampling to a lower sampling rate will “compress” a data file and information will be lost.
§ For example, a 4-channel data file sampled at 250 samples per second for 15 minutes requires about
1.8 MB of disk space. If these channels are resampled to 100 samples per second, the size of the file
on disk is about 720 KB, a considerable reduction.
§ The highest rate a channel can be resampled to is the file acquisition rate (Hardware menu > Set Up
Acquisition).

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If data is resampled to a lower rate and then resampled again at a higher rate, the waveform will
maintain the resolution of the lower sampling rate, only with more data points.

Expression

See the tables on page 152 for descriptions of sources, operators and functions for the Expression dialog.

The post-acquisition Expression transformation is available for performing computations more complex than
available with the Math and Function calculations. The post-acquisition version of the Expression
transformation includes all the same features as the online version described on page 148. The Expression
transformation will symbolically evaluate complex equations involving multiple channels and multiple
operations. Unlike the Math and Function calculations, which can only operate on one or two channels at a
time, the Expression transformation can combine data from analog or digital channels, as well as calculation
channels with a lower channel number. Also, computations performed by the Expression transformation
eliminate the need for “chaining” multiple channels together to produce a single output channel.
To have AcqKnowledge solve an expression and save the result to a new channel, choose Transform >
Expression. For each expression, specify a source channel (or channels), the function(s) to be performed, any
operators to be used, and a destination for the result. The components of each expression can be entered either
by selecting them from the pop-up menus (sources, functions, destination, and operators), or by typing
mathematical commands directly into the expression box.
Any expression can be assigned a specific name and saved as a custom preset. A pop-up menu of recently used
expressions is also available in the Preset menu, along with a pre-loaded list of commonly used expressions.
The Expression transformation can reference past and future points.
Delay
The Delay transformation allows the addition of time delays in postprocessing (similar to the Delay calculation
channel that can be used to add time delays to signals). The time delay can be added by introducing zero-valued
samples at the start of the area to be delayed. The length of the waveform will remain the same; an amount of
data at the beginning of the wave prior to the delay will be lost, with the length equal to the delay. To set up a
delay, choose the Transform > Delay menu item.
X

When inputting the delay amount, the units can be changed between seconds and samples.
· Delay by samples is applied according to the acquisition sampling rate, not the channel sampling rate.
The Automator action allows Delay to be used in Automator workflows. See page 23.
X

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Rescale
The Rescale transformation operates identically to the Rescale calculation—see page 162.
X

X

Waveform Math

The Transform > Waveform Math operation allows arithmetic manipulation of waveforms. Waveforms can be
added together, subtracted, multiplied, divided or raised to a power. These operations can be performed using
either two waveforms or one waveform and an arbitrarily defined constant. Operate on the entire waveform by
choosing Transform entire wave, or operate on portions of the waveform that have been selected using the
cursor tool. If there is no selected area, only one sample point (the one selected by the cursor) will be
transformed.
All of the main components of a waveform math calculation can be selected from pop-up menus in the
Waveform Arithmetic dialog.
Source
The channels to be used in the transformation are referred to as source channels (Source 1 and
Source 2), and can be combined using any of the operators in the pop-up menu. Source
channels allows for selection any of the existing channels in the current window, or a constant
(defined by K).
Constant
The “Constant =” entry box is activated when a Source is set to “K, Constant.”
Operand
The pop-up menu allows selection of addition, subtraction, multiplication, division or power
functions.
Destination
Save the results to an existing channel or create a new channel. Choose an existing channel
from the pop-up menu or select the “New” option, which will create a new channel (using the
next available channel).
Waveform math can be used many ways. As one example, two waveforms can be added together. The
following screen shows a sine wave in channel 14 and a triangle wave in channel 16.

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To add these two waves, select Transform > Waveform Math and set source 1 to channel 14, the operator to
addition “+”, source 2 to channel 16, and destination to New as shown here:

Click OK to perform the transformation. The following screen shows the sum of CH14 and CH16 on a new
channel.

NOTE: If two waveforms of unequal length are selected as sources, the length of the resulting
waveform will be equal to that of the shortest one. Likewise, if one of the source
waveforms extends only into a portion of the selected area, the resultant waveform
will only be as long as the shortest source portion. If waveform math is performed on
a selected area and output to an existing waveform that does not extend into the
selected area, the resultant waveform is appended to the destination waveform.
Slew Rate Limiter

The Slew Rate Limiter transformation is used for denoising and removing motion artifact during and after
recording. The allowable amount of motion artifact over a given time/sample window can be precisely adjusted
from a minimum allowable change to a maximum allowable change, thereby eliminating artifacts that exceed
the selected amplitude range within a given time period.
Tailor the range for a given type of artifact by modifying the Time window and Minimum/Maximum allowed
change parameters. Parameters for various levels of artifact detection can be permanently stored by clicking
“New…” and saving the signal type as a custom preset.
To apply the slew rate limiter transformation in AcqKnowledge:
1. Select the desired source channel in the data.
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2. Transform > Slew Rate Limiter.
3. Select the time window using a sample interval or a time value.
4. Set the desired minimum allowed change value.
5. Set the desired maximum allowed change value.
6. Click OK.
Any artifact that falls outside the boundaries of the maximum/minimum allowed change setting will be
eliminated from the data.
See also: Slew Rate Limiter online calculation channel on page 163.
Watch the AcqKnowledge Slew Rate Limiter video tutorial for a detailed demonstration of this feature.

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Analysis Menu Commands

Overview
The Analysis menu contains operations that derive data and measurements from the graph—plus a courtesy
copy of the Specialized Analysis package with classifiers and automation routines.
Histogram

The Histogram function produces a histogram plot of the selected area. When a histogram is created, the sample
points are sorted into “bins” along the horizontal axis that contain ranges of amplitude values. These bins divide
the range of amplitude values into equal intervals (by default, ten bins) and the individual sample points are
sorted into the appropriate bin based on their amplitude value.
For instance, if a waveform had a range from 65 BPM to 85 BPM, the lowest bin would contain all data points
with a value from 65 BPM to 67 BPM. The second lowest bin would hold all data points between 67 BPM and
69 BPM, and so on, until the tenth bin was created. AcqKnowledge then counts the number of “hits” (the
number of data points) in each bin and plots this number on the vertical axis.
Analysis > Histogram Options:
bins
Determines how many bins the data will be divided into; the default is ten bins.
Autorange
Fits all the data selected into a bin; the bin sizes are determined by the extent of the data and the
desired number of lines. Automatically sets the center of the lowest bin equal to the minimum
value of the waveform (or the selected area, if a section is highlighted), and centers the highest
bin on the maximum value of the waveform (or selected area, if any).
Disable to fix the bin sizes and enter values for Highest Bin and Lowest Bin.
After clicking OK, a histogram plot will be generated in a new window. By default, AcqKnowledge displays the
frequency of occurrence for each bin on the vertical axis. To calculate the cumulative frequency, select the
entire histogram waveform and choose Integrate from the Transform menu.
Since the histogram function sorts sample points into a relatively small number of categories, the histogram
window is likely to display a large number of “hits” in each bin, especially if data was collected at a relatively
fast sampling rate. If this is the case, it’s recommended to resample the data at a lower rate (using the Transform
> Resample function). The caveat to this is that resampling the data may cause a bias, unless the data was
filtered to remove all frequency components that are more than 0.5 the resampling rate.

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Autoregressive Modeling
About autoregressive modeling
Autoregressive modeling is linear mathematical modeling algorithm well suited to operation on discrete series of
data. Using autoregressive models of physiological data, it is possible to perform advanced time series
analysis, compression, denoising, arrhythmia detection, and waveform classification. Its ability to be used to
extrapolate spectral features from waveforms at low sampling rates makes autoregressive modeling quite
useful for electrogastrogram analysis.
AR modeling has a large number of applications in physiological signal analysis. These applications derive from
its ability to approximate data through a more compact representation in AR coefficients. Other applications
leverage AR modeling's ability to generate additional data for a signal with roughly the same characteristics.
Specialized applications exist for ECG, EEG, and EGG in addition to general purpose analysis procedures.

Autoregressive modeling estimates the
parameters of a fixed-order autoregressive
model, representing a model output value
as a linear sum of previous input values.
AR modeling may replace the source data
with the model of equivalent length. The
output length is equal to the source data,
unless specified.

AR Time-Frequency Analysis is on page 332.
X

X

Output can also paste model parameters as tabular text to a journal. If “Don’t modify waveform” and “Show
model in separate graph” are both enabled, a new graph window will be generated to display the specified
number of samples resulting from the best-fit autoregressive model.

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Nonlinear Modeling
About nonlinear modeling
Modeling is used in physiological data to assess how well data conforms to a theoretical model. This is
used to express a sampled signal in a continuous form and to perform data reduction. The nonlinear
modeling features in AcqKnowledge support more advanced physiological analysis than is possible with
the linear regression measurement, which is a rudimentary single order linear model.
Nonlinear modeling is the process of finding the best fit of a mathematical function to an arbitrary data
set. Fitting the function—or model—to the data consists of choosing a set of function parameters that
minimize error between the actual data points and the values generated from the model function.
Nonlinear modeling functions can be arbitrarily complex. When the model is close to the shape of the
data, the fits between different data sets may be good indicators of subtle variations in the data.
Most general-purpose methods of performing modeling are iterative and require an estimator for the
function. A commonly used estimator is the least means squares (LMS) estimator. Nonlinear models can
be estimated from data by combining LMS estimators with multidimensional function minimization
algorithms.
Applications in hemodynamics
Many pressure and ECG signals exhibit regular morphologies. Fitting data to models that share these
characteristics helps emphasize subtle differences in waveforms though variations in their model
parameters. Nonlinear modeling is one of the most accepted methods for computing indexes for the
relaxation period of left ventricular pressure. Cardiac researchers have used the time constant “tau”
in various studies on cardiac function and abnormalities. Tau is determined by one of the parameters
to an exponential model of the trailing end of the pressure signal. Studies have indicated that tau can
be a good indicator of cardiac dysfunction, but reliable methods for its calculation have proven difficult
and the effort is ongoing. The generic modeling abilities in AcqKnowledge allow researchers to
analyze data using the tau constant and potentially develop robust algorithms for its calculation.

Nonlinear modeling (also called “arbitrary curve fitting“)
determines the “best fit” of an arbitrary function to
source data; the function is called a model.
A model must match underlying trends in the data to
produce meaningful results. Also, to properly interpret
the value of the best fit coefficients and any further
derived results, users must consider the limitations of the
simplex search method, which include: estimation only;
not guaranteed to terminate; not guaranteed to find the
exact solution; may get stuck in local minima.

See the NLM measurement on page 106
X

X

Nonlinear modeling generates a new display and replaces source data with a model of equal (unless specified)
length and also pastes model parameters as text to a journal. The sampling rate and axis units match the source
graph.
Max Iterations
Indicates the number of iterations after which the simplex search will be terminated if no convergence has
been achieved.
Tolerance
Provides the tolerance used for termination of the algorithm. If the estimator decreases in two consecutive
steps by less than this tolerance, the simplex search will halt.
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Model Origin Placement
Controls where the zero point of the model is placed. Selection-relative placement is useful when comparing
different sections of the same channel of data by looking for variations in their best fit model parameters. If
channel data is used as part of the Model Expression the location from where the channel data is extracted
will not be translated; regardless of the model origin setting, the channel data will be used from the selected
area only.
Model Expressions
These model expressions use the same expression format as other parts the program, such as the Expression
calculation channel. See the function tables starting on page 152 for details on Sources, Functions, and
Operators.
Preset
The following presets for the most common types of models are included. Users can extend presets or create
custom models if these presets are too general to achieve exact fits with simplex search. Presets are stored at
X

X

Computer > Local Disk > ProgramData > BIOPAC Systems, Inc > AcqKnowledge 5.x > Presets.
Preset

Description

Expression

Cubic

3rd order polynomial.

param(3)*(TIME^3)+param(2)*(TIME^2)+param(1)*TIME+param(0)

Gaussian

Standard Gaussian model; useful
for peak fitting.

param(0)*EXP(-((TIME-param(1))/param(2))^2

Linear

Basic linear fit of the data.

param(1)*TIME+param(0)

Logarithmic

Logarithmic growth and decay;
useful for initial rapid growth/decay
followed by gradual
decline/increase.

param(0)*LOG(TIME-param(1))+param(2)

Logistic

Logistic LVP relaxation model;
TL given by a(1).

param(0)/(1+EXP(-TIME/param(1)))+param(2)

Monoexponential

Exponential LVP relaxation model;
Te given by a(1).

param(0)*EXP(-TIME/param(1))+param(2)

Power Series

Useful for a wide variety of data,
e.g. reactant analysis.

param(0)+param(1)*(TIME^param(2))

Quadratic

2 order polynomial.

param(2)*(TIME^2)+param(1)*TIME+param(0)

Weibull
Distribution

Commonly used in reliability
analysis.

param(0)*param(1)*TIME^(param(1)-1)*EXP(-param(0)
*TIME^param(1))

nd

Sources
All channels except the active can be used as sources with the Model Expression.
Parameters
Parameters are represented by param(n) where n is an integer index starting from zero. For example, in the
linear model param(0)*x+param(1), param(0) can be interpreted as the “a” in “ax+b and param(1) can be
interpreted as the “b” in “ax+b.”
Output to Journal displays the result of the modeling as text in the journal.
Show model in separate graph generates a separate graph to display the best fit model.
Length specifies the length of the separate model graph in samples.
Don’t modify waveform suppresses replacement of the selected source data.
§ If the model fitting does not complete successfully, the original data will be preserved regardless of
the state of this selection.
Transform entire wave
Fits the entire data of the selected waveform to the model, with model origin at start of graph.

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Power Spectral Density
The Power Spectral Density (PSD) function extracts the
power present at different frequencies within a signal
and is useful for EMG analysis. The PSD
transformation approximates the same result as
squaring the linear FFT magnitude. PSD is not available
when the horizontal units of the source graph are set to
Frequency.
AcqKnowledge uses the Welsh periodogram to average
signal time-sliced portions of the signal and reduce
noise effect, and generates a two dimensional graph
displaying the wattage of a particular frequency
component in a signal. Windowing options are
Hanning, Hamming, or Blackman. The graph is plotted
as horizontal frequency vs. vertical (units)^2/Hz, where
units are the vertical axis units of the source data.
Window

Used to change the window that is applied to each segment of the source data prior
to computing the PSD to be included in the average. Includes the following options:
Hamming

Window size

Hanning

Blackman

The specified number of samples must be a power of two. Note that the window
function is applied to the entire window width of the data; using a subset of the
windowed data will not include the final portion of the windowed data.

§

If the FFT size is less than the window size, only a subset of the windowed
sample data will be used.

Automatic If selected, the window size is selected automatically depending on the
size of the source data. For a data length of n samples, choosing this
radio button will use the window size:

n
L = 4.5
Manual

Overlap length

If selected, the window size will be input manually by the user in the
associated edit field. The window size must be greater than three and
must be less than the length of the data selection. Users will be warned
on invalid window sizes when attempting to click OK.

After each individual FFT, the window of source samples is shifted over by a certain
amount to compute the next FFT, so there is an overlap of source samples in
successive windows of source for the next FFT in the average.
Automatic If selected, the number of samples to overlap successive windows will
be computed automatically. Given a window length L computed
according to the window width choices, choosing this radio button will
use an overlap number of samples:

L
2
Manual

lf selected, the number of samples to overlap successive windows of
source data. Overlapping reduces windowing artifacts The overlap
length must be positive and must be less than the window size. Users
will be warned on invalid overlap lengths when attempting to click OK

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FFT width

Automatic

If selected, the number of points to use for each individual FFT will be
computed automatically. Given a window length L computing according
to the window width choices, the number of points in the FFT will be set
to:

§

Manual

The number of points in the FFT is set to 256 if the window width is
less than 256. Otherwise the length is set to the next power of two
higher than the window width.

If selected, the number of points in the FFT will be specified manually
in the edit box to the right of the radio. The number of points in the FFT
will be required to be a positive power of two. It is recommended that
the FFT length be set larger than the window size. If longer than the
window size, zero point padding is used. Users will be warned on
invalid FFT number of points when attempting to click OK. If the user
inputs a number of points for the FFT that is shorter than the window
width, a confirmation dialog will be displayed to the user warning that
the windowing is shorter than the requested FFT width and asked if
they want to continue.

Use linear detrending for When enabled, linear regression detrending is applied for each individual segment
each window
prior to the FFT computation. When disabled, windowing only is applied.
Detrend each segment
independently

This option is only available when “Use linear detrending” is enabled. When this
option is enabled, detrending is applied independently for each segment; when
disabled, detrending from the previous segment will be incorporated into the next
segment.

Transform entire wave

When enabled, the entire waveform is delayed. When unchecked, only the selected
area is delayed.

§

If there is no selection in the graph, the checkbox is enabled and dimmed.

§

As the selection changes in the graph with the selection palette, the state of this
checkbox is updated.

AR Time-Frequency Analysis
The AR Time-Frequency transformation can be used to
examine changes in the spectral density of a signal using
enhanced frequency resolution from derived AR models.
Examining frequency changes over time can be a useful tool
for arrhythmia detection and rough classification of
waveforms.
Autoregressive spectrum time-frequency analysis divides a
waveform into equal-length time segments, calculates an AR
model (see page 330) for each individual time segment, and
then computes a power spectrum from the model. (To perform
raw data time-frequency analysis, use the Cycle/Peak detector
with the FFT 3D output option.)
X

X

Time interval—Enter a positive floating point value to specify the segment width; the source signal is split into
fixed length segments of this width and a frequency spectrum is generated for each segment from a model of its
data.
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Model order—Enter a positive integer to specify the order of the AR model that is constructed on an interval
by interval basis.
Frequency resolution—Enter a positive integer to indicate the number of points contained in the FFT of an
individual time segment; it will be rounded to the closest power of 2 when analysis is performed.
Amplitude scaling—“Normalize amplitudes” scales amplitudes such that the maximum peak-peak distance is
equal across time intervals.
Show 3D Output—Constructs a 3D surface plot of the time-frequency analysis with amplitude vs. frequency
vs. time.
Paste results to journal—Inserts a series of tab-delimited tables representing the frequency distributions on a
cycle-by-cycle basis into the Journal.
FFT Fast Fourier Transformation

The FFT algorithm requires that the data length be an exact power of two (i.e.,
256 points, 512 points, 1024 points, and so on).
The Fast Fourier Transformation (FFT) is an algorithm that produces a description of time series data in terms
of its frequency components. This is related to the frequency spectrum. The FFT displays the magnitude and
phase of the time series data selected and displays only the DC and positive frequency components; the FFT
does not display negative frequency components. To reconstruct a signal from additive sines or cosines, it’s
necessary to include both the positive and negative frequency components. Since it’s not physically possible to
generate a negative frequency signal, the amplitude of the corresponding positive frequency component must be
doubled.
The output from an FFT appears in a graph window with magnitude (vertical axis) plotted against various
frequencies (horizontal axis). A large component for a given frequency appears as a positive (upward-pointing)
peak. The range of frequencies plotted is from 0 Hz to 1/2 the sampling frequency. Thus, if data was collected
at 200 samples per seconds, AcqKnowledge will plot the frequency components from 0 Hz to 100 Hz.
Fourier analysis can yield important information about the frequency components in a data set, and can be
useful in making determinations regarding appropriate data cleaning techniques (e.g., digital filtering). The FFT
algorithm assumes that data is an infinitely repeating periodic signal with the end points wrapping around.
Thus, to the extent that the amplitude of the first point differs from the last point, the resulting frequency
spectrum is likely to be distorted as result of this start point to end point discontinuity. This can be overcome by
“windowing” the data during the transformation. For more information on the windowing feature, see the
window section that follows.
The FFT transformation cannot be performed in real time (i.e., during an acquisition). To emulate an online
spectral analysis, use online filters and the Input Values window. See page 241 for more information about realtime frequency information.
Pad

If a section of data is selected that is not a power of two, AcqKnowledge will always “pad” data
up to the next power of two, filling in the remaining data point with either:
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Show Mod.

Window

Pad with zeros: a zero
Pad with last point: the last data point in the selected area
In other words, if 511 data points are selected, AcqKnowledge will use a modified version of
the waveform as input. The modified waveform will have 512 points, and the last point in the
modified wave will be either a zero or equal to the 511th point of the original data.
To view the modified waveform being used as input for the FFT, check the Show modified
input box. Whenever possible, it is best to use an input waveform (select an area) that is an
exact power of two. The waveform is modified by applying the windowing and padding
options. Window functions diminish the discontinuities that occur at either end of the wave.

The FFT algorithm treats the data as an infinitely repeating signal with a period equal to the
length of the waveform. Therefore, if the endpoint values are unequal, the resulting frequency
spectrum will show larger than expected high frequency components due to the discontinuity.
Windowing these data minimizes this phenomenon. For example, to apply a window
transformation to a sine wave whose endpoints do not match up, check the box next to Window
and choose a type of window from the pop-up menu. Each of the windows has slightly different
characteristics, although in practice each provides similar results within measurement error.
As shown below, the frequency spectra of the windowed and non-windowed data differ
significantly when the endpoints are unequal. When data are not windowed, the very low and
very high frequencies are not attenuated to the same extent as when windowed.

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Trend

335

Sometimes, data contains a positive or negative trend that can cause extraneous
frequency components to “leak” into the frequency spectrum. This can be prevented by
selecting remove trend when performing the FFT. This effectively draws a line through the
endpoints, and subtracts the trend from the waveform.
For example, the
following sine wave
has an upward trend
through the data
(positive trend
component). The lower
graph shows FFTs of
the skewed sine wave
data with and without
the trend removed.
Note that the spectrum
of the data without the
trend removal has
gradually decreasing
frequency components,
while the data with the
trend removed has far
fewer frequency
components except for
the single spike due to
the sine wave.

without trend removal

trend removed

Remove Mean Remove mean calculates the mean of all the points in the selected area and then subtracts it
from the waveform. This is generally useful for windowing a waveform that has a large DC
offset.
As an example, start with a sine wave with a 10-volt DC offset (with a little noise added to
broaden the spectrum), and perform spectral analysis with and without mean removal:

Note the large spectral components at the beginning of the top plot, without mean removal.
This is due to the offset of the original data. The bottom plot is with mean removal.

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Linear

Phase

Since the offset of the waveform is often an artifact of the way it was generated, the remove
mean option provides a more accurate indication of the true spectral components. This is
especially true for applications where low frequency components are of interest. If the data has
a large DC offset and the data is to be windowed, generally a more meaningful spectrum will
result if the mean is removed prior to windowing.
By default, the FFT output is described in terms of frequency along the horizontal axis and
dBV on the vertical axis. The Bell scale (from which dB are derived) is logarithmic, and in
some cases it may be useful to have the output scaled in linear units. To do this, click the button
next to linear and check OK. The other options in the dialog work as they normally do when the
dB scaling option is selected. The relationship between log and linear units is: dBVout = 20 log
VIN.
The standard FFT produces a plot with frequency on the horizontal axis and either dB/V or
linear units (usually Volts) on the vertical axis. In some cases, it may be useful to obtain phase
plots of the waveform (as opposed to the default magnitude plots). Phase plots display
frequency along the horizontal axis, and the phase of the waveform (scaled in degrees) on the
vertical axis. This option functions apart from the magnitude option—either can be checked
independently. If both are selected, separate magnitude plot and a phase plots will be produced.

Inverse FFT
The Transform > IFFT menu option is generated after an FFT is
performed. An Inverse FFT (Transform > IFFT) converts spectral
values back to a time series waveform to reverse the FFT
transformation. Any modifications to the original data (such as
windowing or padding) will be shown in the resulting time series
data.
To obtain a meaningful IFFT result, the FFT graph must contain at
least one magnitude channel and at least one phase channel. With the
window open, choose IFFT from the Transform menu to generate
the Inverse FFT dialog.
To accurately recreate the time series waveform
1. Select the source channels for the inverse FFT in the Magnitude and Phase pull-down menus.
2. Select whether to express Magnitude in linear units or dB logarithmic units (decibels). To determine
this setting, check the vertical axis units of the magnitude channel; this should correspond to the
Magnitude scaling choice that was used when performing the forward FFT.
§ The Phase waveform must be in degrees.
3. Click OK to perform the IFFT.
§ The result is generated in a new time domain window, labeled “IFFT of Spectral…”

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The following FFT example uses an electroencephalogram (EEG) signal acquired when the subject
alternated between eyes open and eyes closed. Typical results suggest that higher levels of alpha activity
(activity with frequency components between 8Hz and 13Hz) are to be expected when a subject’s eyes are
closed.
1. The raw data, prior to FFT, is shown here:
Eyes
open

2. Select Transform > FFT from the menu.
The FFT Parameters dialog will be
generated; in this example, the Window
function chosen is Kaiser Bessel:

Eyes
closed

Eyes
open

13107

3. Click OK.
A frequency domain window (a graph
window which places frequency along the
horizontal axis rather than time) will be
created and displayed, showing the spectrum
of the input data.
The window is named “Spectral of (the
original window name)” and ends with the
channel number, as shown here:
The resulting magnitude value for each
component is equal to the peak value of the
sine wave contributing to that component.
The entire pattern of frequency components
is known as the frequency spectrum of the
data. The somewhat erratic appearance of the
spectrum is usually due to small-scale
variations in the original waveform.
4. Optional—This “noise” can be removed by
applying a smoothing transformation to the
FFT output. In the graph shown, there is a
pronounced frequency component centered
on 8Hz, which corresponds to the alpha wave
frequency band (8Hz—13Hz). The frequency
spectrum (0-20 Hz shown) used 20-point
smoothing.
Watch the AcqKnowledge FFT video tutorial for a detailed demonstration of this feature.

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DWT/SWT
About Wavelet Transformation
Wavelet transforms are similar to Fourier transforms. Instead of
projecting a signal in a space of sines and cosines, wavelet transforms
project a signal into a space comprised of orthogonal functions called
wavelets. Discontinuities are more obvious in wavelet transforms than in
sines and cosine analysis, making wavelet transforms a better choice
for decomposing a signal to its fundamental form. Wavelet transforms
can be used for noise reduction and filtering, extracting features from
signals that are not apparent in time or frequency domains, and
predicting signal qualities from a small number of data points.

Discrete wavelet transformations (DWT) break a source signal into high-frequency and low-frequency
components. Use for ECG and EEG analysis. DWT creates a new graph with wavelet coefficients on the
horizontal axis and the amplitude for each coefficient on the vertical axis, pastes acquisition settings to the
graph journal, and places an event at each boundary between the high- and low-frequency components
produced at each iteration.
Wavelet type
Specify Biorthogonal 4.4, Symlet 4, Coiflet 6, Daubechies 8 or Spline 3.
Number of iterations Specify the number of transforms to execute.
Stationary wavelet transformations (SWT) differ from DWT in that the “stationary” transformation retains all
coefficients at each processing level, so each level’s output is equivalent to the length of the input signal. At
each output level, the low and high pass filters are upsampled by inserting 2k−1 zeros between each wavelet
filter coefficient. This method retains information unnecessary for reconstruction of the original signal but
produces output that may be more useful for identifying and enhancing specific characteristics of the original
signal.
To enable the SWT option, check the “Use algorithme à trous / SWT” box. Like the DWT transformation, the
SWT output will appear in a new graph.
Multi-channel output: This option places a copy of the original source data in the first channel of
the output graph. Coefficients for each level are inserted as subsequent channels of the graph labeled “dn” with
n replaced by the level of decomposition. The final channel is prefixed with an “h” indicating the high-pass
coefficients left over from the final run.
If either the multiple channel or the SWT options are used, the Inverse DWT cannot be used to reconstruct the
original data. To reconstruct the original data, apply regular DWT with single channel output.
Inverse DWT
Operational on the result of a DWT. Projects data from wavelet
space to time space. For correct recomposition of the source
data, the wavelet type specified for the IDWT must match the
wavelet type used for the DWT. Amplitudes of the wavelet
coefficients may be changed, but an IDWT will fail if the
horizontal units, events at DWT iteration level boundaries, or
file length have been modified. Note: Spline 3 DWT is not
supported in Inverse DWT.

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Principal Component Analysis
About Principal Component Analysis
Principal Component Analysis decomposes source signals into a
new signal space (constructs an orthogonal set of vectors). PCA is
useful as a feature extraction and data reduction tool.
Changes in the values of the mixing matrix may be indicative of
changes in underlying signal morphologies that other methods
cannot easily detect.
For example, PCA is useful for EEG analysis; where it can reduce
32 channels to the fundamental elements of signals.

AcqKnowledge uses a mean-adjusted covariance matrix method to generate a new PCA graph with each
component in a separate channel. The coordinates of the new space are the eigenvalues extracted from the
matrix defined by the source data and are called “Principal components.” The extracted eigenvectors are the
“mixing matrix.” Sine and cosine are orthogonal signals. The principal components are numbered in order of
decreasing eigenvalues, which implies that the first principal component contains the majority of the variation
of the source signals. Results are also pasted in to the journal, including the eigenvalue magnitudes and the
eigenvector matrix. To determine the percentage contribution of each component, review the eigenvalue
magnitudes. Select two or more channels—all of the selected channels must have the same sampling rate.
Inverse PCA
Available only for graphs produced by PCA. Reconstructs the source signals based on the components and
mixing matrix of the PCA graph. The graph is reconstructed in a new window, with a list of the components
used pasted to the journal.
Ü For noise reduction, use only the strongest principal components to reconstruct the source signals.
Independent Component Analysis
About Independent Component Analysis
Independent Component Analysis is useful for signal separation,
denoising, and advanced EEG analysis to remove noise signals or
locate approximate regions of active processing centers in the brain.
ICA is a form of statistical blind separation that attempts to separate
mixed (overlapped) signals based on the assumption that they are
statistically independent.

§ For example, if two microphones in a room record one person
reciting Shakespeare and another person playing the banjo, the
recordings will capture both the speaker and the banjo. After
performing ICA on the two recordings, one result will have only
the speaker and the other will have only the banjo.

AcqKnowledge uses the FastICA algorithm to generate a new ICA graph with each component in a separate
channel.
For more information on the FastICA algorithm, see this link.
Select two or more channels—all of the selected channels must have the same sampling rate.
Specify tolerance and number of iterations.

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ICA limitations to consider for application and interpretation:
1. The number of mixed sources must be equal to the number of independent components (as in the
example where two microphones captured two sound types).
2. Sources must be statistically independent; highly-correlated signals cannot be effectively separated.
3. Sources must have non-Gaussian probability distribution. It is not possible to separate out components
like white noise through ICA.
4. Signal mixing must be a constant, linear process. Any type of non-linear signal propagation cannot be
expressed in linear combinations of sources, the underlying assumption of ICA.
5. The component sources must be stationary (that is, point sources).
Inverse ICA
Available only for graphs produced by ICA. Reconstructs mixed signals based on the components and
mixing matrix of the ICA graph. The statistical nature of the algorithm implies that it cannot perfectly
reconstruct original source data—it estimates the most probable set of source signals. The graph is
reconstructed in a new window, with a list of the components used pasted to the journal.

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Find Cycle (Peak Detector)
Watch the six-part AcqKnowledge Find Cycle video tutorial for a detailed demonstration of this feature.

The Find Cycle/Peak Detector setup dialog is accessed by choosing Analysis > Find Cycle, or using the Ctrl+F
keystroke.
Overview
The advanced Cycle/Peak Detector combines with the powerful Event Marking System. Use it to perform
amplitude, time, or event-based measurements. New output options for measurements, averaging, events,
clustering (K-means), and 3D surface (cycle data, histogram, FFT, and DWT).
The Find Cycle detector uses three tabbed settings panels to define and automate cycle/peak detection:
Cycles/Peaks
Selection
Output
Cycle detector settings are graph-independent, which means that find cycle/peak operations can be performed
in multiple graphs without needing to re-enter graph-specific settings for each run. By using multiple data
views, different find cycle/peak operation can be performed on the same set of data without losing settings
between “Find Next Cycle/Peak” operations.
When the Cycle/Peak Detector is first opened for a graph, the dialog will be filled with the values from the last
successfully executed find Cycle/Peak operation. Subsequently, changes to the settings will be applied only to
that graph.
TIP
When running the cycle detector multiple times and needing to put the edge back at the beginning
of the waveform for the next pass, use the keyboard shortcuts Home, End, Page Up, and Page
Down to quickly change edge location (see page 65).
Cycles/Peaks tab

Peaks

Events

Fixed Interval
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Find Cycle controls available at bottom of dialog

Find Next Cycle
When selected from the Analysis menu (or Ctrl+E), both edges will move one peak to the right while staying
above the threshold.
Find All Cycles in Graph
When selected from the Analysis menu, Find Cycle setup dialog or selecting Ctrl+R, the software will find all
cycles/peaks through the end of the file. If the data file is very large, it may take some time to find all the cycles
since AcqKnowledge loads data from disk while it scans for the cycles.
Find in Selected Area
When selected from the Analysis menu or in the Find Cycle setup dialog, only cycles within a selected area will
be detected, all others will be ignored.
Find All Cycles in Focus Areas
If the graph contains defined focus areas, this option will limit cycle detection to focus areas only. If no focus
areas are defined, this option will not be available. This is selectable via the Analysis menu or in the Find Cycle
setup dialog.
Find First Cycle
Use this option to apply changes to the Find Cycle setup and locate the first cycle. This is selectable via the
Analysis menu or in the Find Cycle setup dialog.
Preview (Selection tab)
When selected, a preview of the selected Find Cycle operation is displayed prior to applying the settings.

Find Cycle definitions
The Cycles/Peaks tab offers three general methods for
establishing cycle parameters:
§
Peaks: Data driven maximum and minimum (see page
345)
§
Events (see page 345)
§
User-defined fixed time intervals (see page 346)

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When the cycle location mode is switched on the “Cycles/Peaks” tab, the edge selection offsets will be checked.
If they are non-zero, a prompt will appear, warning that that the edge adjustment offsets may not apply for the
new cycle location mode. The user can reset the offsets to zero (default) or retain the (non-zero) settings used in
the previous cycle location mode.
Peaks
Peak direction
Level

Use selected...

Threshold
Tracking

Positive/Upward – searches for positive voltage spikes in the signal.
Negative/Downward – searches for negative voltage spikes in the signal.
Important usage note—Level is not set automatically when the Cycle/Peak detector is
generated. (Automatic Level is used in previous versions of AcqKnowledge for Mac and
current version for Windows.)
To optimize the threshold detection level for the selected area of data in the graph, click the
“Use selected maximum/minimum” button underneath the level. When changing the source
channel or peak direction, also use this button to re-compute the recommended level based
upon the new settings. The recommended level is “Tracking using % of peak value” (see
below) using a percentage factor of 75%.
Fixed—Keeps the threshold voltage level constant.
The Tracking threshold mode modifies the threshold after it finds a peak, depending upon the
value of the new peak, and will compensate for a slowly drifting baseline.
Hints regarding the use of Tracking Threshold Options
·
·

If data has a very consistent cyclical nature, either Tracking Option will work.
If data has spurious positive or negative peak values present, the Means Reference
Tracking Option is a better choice.

·

If data has an erratic baseline, but consistently sized, positive and negative peaks, the
Peaks Reference Tracking Option is a better choice.

Tracking using mean value and % of peak value—Adjusts the threshold voltage level after
each peak, based on the average of the last cycle’s data and the specified percentage of the
current peak voltage. The Means reference option will determine the Mean Value of all the
data, from peak to peak. This Mean Value establishes a variable reference upon which the
tracking threshold operates. The software determines the new threshold (NT) as follows:
For Positive Peaks
NT = Mean Value + (Positive Peak Value - Mean Value) x (% factor)
For Negative Peaks
NT = Mean Value - (Mean Value - Negative Peak Value) x (% factor)
Tracking using % of peak value—Adjusts the threshold voltage level dynamically based on
the specified percentage of the value of the most currently found peak. The Peaks reference
option will determine the Positive Peak Value and Negative Peak Value of all the data, from
peak to peak. The Positive and Negative Peak Values establish a variable reference upon
which the tracking threshold operates. The software determines the new threshold (NT) as
follows:
For Positive Peaks
NT = Neg. Peak Value + (Pos. Peak Value—Neg. Peak Value) x (% factor)
For Negative Peaks
NT = Pos. Peak Value - (Pos. Peak Value—Neg. Peak Value) x (% factor)

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Events
Event-based cycle location are used to extract information from events or define events based upon Find Cycle
output. Either one or two events may be used to define a cycle.
Start / End

Define the event; any of the predefined event types can be explicitly matched. To
use only one event to define each cycle select the exact same event type for both
“Start event” and End event,” and see the “Match Pairs” discussion below.
Match pairs “Match pairs of events only” may be unchecked only when the Start event and
End event are identical. Under this condition, if the box is checked, two such
events are used to define one cycle. If the box is unchecked, then each event
defines a cycle by itself. This is useful for adjusting a selection relative to an
event, such as locating the first second prior to each event of a specific type. This
option makes it possible to hit time periods for each event since each cycle
consumes two events.
Located on
Specify the channel when the event must be defined, either its actual channel or
“Global” for events not associated with any channel. Select “Anywhere” to search
for events of specific types across channels.
With Labels Toggle the “With labels containing text” checkbox to set this option.
optional
When checked, the matching event’s label must contain the text in the edit box to
the right of the checkbox.
§ The text search is not case sensitive. The search must be non-empty for cycles
to be located properly.
When unchecked, the matching event can have any label, including none.
The Cycle detector uses the following algorithm to search for cycles in the graph:
1. From the starting point, find the first event matching the criteria of the Start event. This will be defined
as the left event. If no event matches the Start criteria, no more cycles are in the file.
2. If the Start event criteria match the Ending event criteria and zero width cycles are allowed (e.g. “Match
pairs of events only” is unchecked), define the right event as identical to the left event and go to step 5.
3. From the location of the left event, find the closest event matching the criteria of the End event. This
will be defined as the right event. If no event matches the End criteria, no more cycles are present in the
graph.
4. Within the time region between the left and right events, search for any events that match the Start
criteria. If such an event occurs, redefine the left event to be this matching event and repeat the step. If
no event is located, then the closest pair of events has been located.
§ This step is useful for working with data that has missing portions of the sequence, as can come out
of some classifiers. For example, if two event types A and B are used as the endpoints, a sequence
of three events AAB will match the last two events as the cycle. This is logical in the case of
physiological data where, if B should occur periodically in the signal, AA is an indicator of an
abnormality or missed classification.
5. Set the selected area to the time interval whose endpoints are the left and right events.
6. Perform selection adjustment and output as indicated by the settings on the “Selection” and “Output”
tabs.
7. If “Find All Cycles” is being performed, return to step 1 and use the ending event location as the new
starting point to find any remaining cycles in the graph.

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Fixed Interval
Fixed interval-based cycle detection is based upon cycles found in consecutive time intervals of a fixed width.
The time width is user defined and the starting point of the cycle detection can be placed at the current location
of the cursor, or to begin at an exact point of time in the graph.

The time units for starting the first interval and setting the interval width can be selected in milliseconds,
seconds, minutes or hours.
Selection tab
Use the Selection tab to adjust the range of data that will be analyzed to generate any output. By default, the
data range is set to be the entire cycle as located by the settings on the Cycle/Peak tab, but it can be adjusted to
analyze only specific portions of the cycle.
The controls on the Selection tab vary based on the settings on the Cycle/Peak tab
Peak

When the Cycles/Peaks location method is “Peaks,” the Selection can be adjusted based on the
times of the peaks in the data or the times of the threshold crossings prior to the peaks.

To perform analysis on the entire data within each cycle, the selection should be from the
“previous peak” to the “current peak.” To examine fixed-width time windows located at each
peak, use the “current peak” to “current peak” settings and adjust the two time offsets
accordingly. Note that the settings must place the left edge earlier in time than the right edge for
the peak detection to succeed properly.
“Move Cursor To Origin” (at bottom left of screen) sets the graph data selection back to the first
sample. Use this to reset the cursor in order to find all of the data in the graph.
Event

When the Cycles/Peaks location method is
“Events,” the Selection can be adjusted
based on the locations of the events that
define the boundaries of a cycle.
For a specific cycle, the starting event will
be the event at the left boundary of the cycle
and the ending event will be the event at the
right boundary of the cycle. The starting
event will never be located after the ending
event in time.

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To analyze data over each entire cycle, use the “starting event” to “ending event” setting. To
examine fixed-width time windows occurring within each cycle, set the left edge and the right
edge to the same event (e.g. “starting event” to “starting event” for time windows at the
beginning of each cycle) and adjust the offsets accordingly. Note that the settings must place the
left edge earlier in time than the right edge for the peak detection to succeed properly.
Fixed

When the Cycles/Peaks location method is “Fixed time
intervals,” the Selection can be adjusted based on the
endpoints of the time interval.
To analyze the data over each entire interval, use the
“previous interval” to “current interval” setting.
To examine fixed-width time windows within each
interval or only a sub-portion of each interval, use the
“current interval” to “current interval” setting and adjust
the time offsets accordingly. Note that the inputted
settings must place the left edge earlier in time than the right edge for the peak detection to
succeed properly.

Output tab
The Cycle/Peak Detector includes six Output
options, which can be independently enabled:
Measurements, Averaging, 3D Surface, Events,
Focus Area and Clustering. The selected output, if
any, is listed at the top of the Output tab as Enabled
output.
Output Measurements
Toggle each checkbox to enable/disable the option:
§ Paste measurements for each cycle to the
Journal.
§ Plot measurement results; display
measurement values as channels in
graph.
§ Save measurements to Excel spreadsheet
file, plus output options. In order for
spreadsheet output to be generated, a
“Find All Cycles” operation is required.
§ Apply Measurement Preset – this option
replaces the current measurement
configuration with any of these
selectable presets.
NOTE: If the horizontal axis is in world time
(HH:MM:ss), any time measurement exported to
Excel will be reported in standard time units, such as
seconds or minutes.

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Output: Averaging—Offline
Use Averaging Output” to perform offline ensemble
averaging of source data or ensemble averaging of event
locations. Specify the channel where the cycles/peaks
are to be located in the “Cycles/Peaks” tab and specify
the channel whose data should be ensemble averaged in
the “Average” controls on the “Output” tab.
Toggle the “Average channel events checkbox near the
bottom of the tab to turn event averaging on and off.
Offline averaging can produce average locations of
events within the defined cycle along with the average
data. When a cycle is found, any events in that cycle
will be noted. Events that are on the channel of data
being averaged will be examined for inclusion in the
average.

Index

For each individual cycle, each event will be given an index starting at 0 and increasing to one less
than the number of occurrences of that event type within the cycle. The time offset for each event
from the start of its cycle will be averaged along with the offset for events with the same index
from all other cycles. When the graph of the averaged data is produced, these average time offsets
from the start of the cycle will be used to define new events for the averaged data. If the events and
averaging interval were correlated with the data, the average event offset will produce a reasonable
representation of the appropriate event locations for the averaged cycle.
§ Average events reflect the accuracy of classifiers and the consistency of data used to locate each
cycle.
Label
Each event is labeled with the number of cycles contained in the event. Differences in the event
sequence can cause spurious events to be inserted. The label helps in manual inspection for events
that were only in one or two cycles.
Rejection Toggle the “Events must be in…” checkbox to turn rejection on and off, and specify a percentage
for the relative number of cycles an event must appear in to be considered valid.
Remove… When mean removal is enabled, the mean value of the data within each cycle is subtracted prior to
including it in the overall signal average. This mean removal option is useful for:
o Extracting signals that are “riding” on top of other signals with high DC offset (e.g., MRI
artifact on top of skin temperature)
o Compensating for baseline drift where there are not enough cycles present in the data for
the baseline variation to completely cancel itself out.

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Output 3D Surface

Toggle the “Generate a surface” checkbox at the top of the 3D tab to turn Surface Output on and off.
1) Choose a channel to generate a 3D surface from.
2) Confirm or establish the cycle period of interest on the channel.
§ Use the Cycles/Peaks tab and the Selection tab to adjust the threshold and edge positions for the
cycle period for 3D output.
3) Choose a cross-section output format for the cycle data: cycle data, histogram, FFT, or DWT.
§ For histogram, FFT, or DWT, click “Configure Transformation” to change the settings.
4) Select surface and background colors.
5) Set axis options.
6) Click OK.
Use the cursor to rotate the 3D image; the magnitude of display response increases as the cursor moves further
the center of the screen (keep cursor close to center for slow response/display control).
3D Output Example

Compare ECG cycles in 3D Output. The following example shows how to
AcqKnowledge will generate a 3D image using each cross section of ECG.
a) Cycles/Peaks tab: set the threshold level to identify each R-wave.
b) Selection tab: set the edge to
Current Peak
Left edge -.5 seconds
Right edge .5 seconds
c) On the Output tab
Enable 3D Output
Specify the channel to generate a surface from.
Choose “cycle data” for the cross-section format.
d) Click Find All Cycles.

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Output Events
Toggle the “Output events” checkbox at the top of the
Events tab to turn Event Output on and off.
The Cycle/Peak Detector Output mode can define
events at specific locations; a maximum of two events
per cycle can be inserted with Event Output. After the
Cycle Detector has located a cycle and adjusted the
selection, the data within that cycle can be analyzed
and used to create new events in the graph (datadriven or time specific).

Event definition

Insertion method &
channel selection

Brief definitions follow, see the Event Location table on page 351 for details:
To place the event directly at the specified interval (start or end). See Interval
Adjustment on page 350.
Percent change looks for a crossing based on a percentage of the value of the
signal at the corresponding edge and places the event when a signal increases or
decreases in value from the edge.
% peak to peak change looks for a point where the signal's value has changed
by a percentage of the maximum peak-to-peak amplitude distance over the
selected area and places the event when a signal increases or decreases in value
from the edge
Minimum place events at the minimum of a specific channel's data within the
selection.
X351

X

Output type

X

X

Maximum place events at the minimum of a specific channel's data within the
selection.
The channel whose data should be examined is specified in the pull-down menu
directly to the right of the insertion method pull-down menu:
For each insertion method, the “Output type” pull-down menu adjusts the event
type of the inserted event.

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Sets the channel where the event is inserted, either “Global” for defining global
events or specific channels.
§ None—disables any insertion for that event and all of the other controls
will be hidden except the insertion method pull-down menu.
§ Interval start / Interval end—a pull-down menu is displayed to be used to
change between the different offset methods
§ Minimum / Maximum
Use this edit field to type in specific label text. Each event that is inserted will
have its label set to this text. By default, it is empty (inserted events will not be
labeled).

Output channel

Output label

Interval Adjustment

When an “At location” method is used, options will be generated to fine-tune
event placement relative to the Interval end or Interval start of the selection.

Offset Underneath the insertion method pull-down menu, a set of controls will be
added, allowing the user to specify the percentage, choose whether to search for
an increase or decrease, and choose the channel whose signal should be
examined.

When the offset method is “Threshold crossing,” the event will be placed when
the signal on a channel crosses a threshold.
There are a number of possible ways to configure the threshold crossing:
§ Fixed—The edit field may contain a specific voltage level for the threshold.
In this configuration, an event will be placed if the value of the channel
specified in the next pull-down menu crosses this fixed voltage value.
§ + value—The edit field may specify an offset from the value of the channel
at an interval start or end. The threshold voltage level is the value of the
chosen source channel plus the offset from the edit field. To specify a
threshold lower than the value of the channel at the interval start or end,
choose the – value option. Mean and percentage of peak-to-peak + or –
options are available as well.
The
direction of the crossing can be specified.
Direction of
crossing § + (positive crossing)—the signal must approach the threshold from below
and cross to above the threshold before an event is inserted.
§ - (negative crossing)—the signal must approach the threshold from above
and cross to below the threshold before an event is inserted.
§ ± (mixed threshold)—an event will be inserted at the first positive or
negative crossing that is encountered.

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Event Location Table
Insertion Method
Interval, at location
Interval +/- percent
offset

Location Process
Place an event at the left or right boundary of the selected area, as specified.
Given a particular channel, place an event at the specified time within the
selection when the signal increases or decreases by a specific percentage.
Interval start + Place at the time closest to the left boundary of the
selection. The percentage is calculated from the value of
the signal at the left boundary of the selected area.
Interval end -

Interval +/- percent
peak to peak offset

Interval +/- threshold
crossing

Minimum
Maximum

Place at the time closest to the right boundary of the
selection. The distance between the event and the right
edge of the selection will have an amplitude difference
equal to the indicated percentage of the right edge’s
value.
If the signal does not increase or decrease by that percentage within the
selection, no event will be inserted.
Given a particular channel, place an event at the specified time within the
selection when the signal increases or decreases by a specific percentage of
the peak to peak delta of the selected area.
Interval start + Place at the time closest to the left boundary of the
selection. The percentage is calculated from the result of
subtracting the minimum value of the signal over the
selected interval from its maximum.
Interval end - Place at the time closest to the right boundary. The
distance between the event and the interval end of the
selection will have an amplitude difference equal to the
indicated percentage of the minimum value of the signal
over the selected interval subtracted from its maximum.
If the signal does not increase or decrease by that percentage within the
selection, no event will be inserted.
Starting at the specified boundary of the selection, determine a threshold
value. This threshold voltage may be:
§ fixed voltage level
§ value of signal at the specified interval + offset
§ mean value in selected area + offset
Interval start + Search for the first location where the signal on a
particular channel crosses the threshold.
Interval end - Examining data from right to left, search for the rightmost
location where the signal on a particular channel crosses
the threshold.
If the direction of the threshold crossing matches the user specified direction,
then an event is inserted. If it does not, then the next threshold crossing is
located and the process repeats. If the threshold is never crossed within the
selected area in the user-specified direction, no event is inserted.
The event will be placed at the time location corresponding to a specific
channel’s minimum value within the selected area.
The event will be placed at the time location corresponding to a specific
channel’s maximum value within the selected area.

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Output Focus Area
Use this tool to define and highlight focus areas within the graph and include them in the Find Cycle output.

Define focus areas at selection boundaries
When checked, focus area output is enabled. Focus area selection boundaries will be defined as determined in
the Find Cycle selection setup.
Label basename
Use to assign a name or label to the cycles located in the focus area. The defined basename will appear in the
focus area section of the graph, along with incremented numbers for each subsequent cycle. (See below)

Find Cycle data derived from multiple focus areas can also be exported to either a single spreadsheet, or
multiple spreadsheets. If the “Multiple” option is selected, each defined focus area will have data exported to a
separate spreadsheet. (i.e., three focus areas will output three spreadsheets.)

Output: Clustering
Clustering is the process of taking a set of data points and partitioning them into a fixed number of groups
called clusters. Each cluster represents data points that may share some type of commonality. This can be used
to assign each data point to a class of similar points. Clustering can be used for hemodynamic analysis and is
one of the basic analysis tools used for spike analysis in neurophysiology.

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Algorithm Overview
K-means clustering is an iterative algorithm that begins with a data set of real-valued points in an ndimensional space. Given this data set, one then specifies how many clusters are present. The k-means
clustering algorithm attempts to find the location at the center of each of these clusters. Essentially, this
algorithm partitions the data set into k groups such that the sum of the differences between the centers of
each group and its remaining members is minimized.
A basic algorithm description is:
A. Given a total of k clusters, choose k potential cluster centers.
B. Assign each member of the data set to a cluster according to the closest potential cluster center
using a Euclidean distance function (sum-of-squares).
C. Adjust the location of the potential center for each cluster to a more optimal value. The most basic
method is to assign the new center to match the mean value of all of the members of the set.
D. Determine if the set of clusters and centers is satisfactory. If not, go to step 2 and repeat the
clustering process.
There are many different variations on what constitutes satisfactory ending conditions. The most ideal
stopping criteria are when the cluster assignments no longer change with successive iterations. When there
is no change in the centers, the solution perfectly minimizes the Euclidean distance sum for each cluster,
unique up to variations in ordering of the dimensions. In practice, determining the perfect clustering of a
data set is computationally intensive and may require some time to process. Approximations of perfect
clustering are quicker to compute and usually produce sufficiently accurate results.
A waveform segment is reduced to a single data point by extracting numerical quantities known as
features. Feature clustering is a very common data reduction method in use by clustering-based spike
sorting software. Each feature is a single real-valued number extracted from the data. Examples of features
are: maximum amplitude in waveform segment, minimum, time to maximum, time to minimum, peak to
peak distance, sum of all values, maximum slope of peak.
A commonly used clustering analysis starts with two features. The features are then calculated for each
waveform segment and presented on a scatter plot, allowing the user to visually determine how many
clusters may be present. A k-means clustering analysis is then run on these data points to determine the
center of the clusters in feature space. With the center known, each waveform segment is then assigned to a
cluster depending on the values of its features.
Clustering Settings

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Number of clusters
After features have been extracted, data points constructed from the feature are split up into a number of
groups. Enter the number of clusters into which the data is to be partitioned.
Locate Cluster Centers
Clustering has a good potential to form the basis for classifiers to score physiological data. The cluster
centers can be located by keeping the centers fixed and manually setting the cluster centers (above left) or
by automatic learning, which dynamically locates the cluster centers based upon a training set of all data, a
subset of data based upon a percentage, or based upon a selected event in the data.
Manually
The manual method allows the centers of each cluster to be manually typed in and edited. Instead of
running a full k-means algorithm to locate centers, the k-means algorithm will simply run through the data
set and assign each element to the closest cluster center and apply any outlier detection.
This simplistic clustering will allow centers as computed from a previous run to be used in subsequent
clustering. Using manually specified centers is necessary to provide consistency when clustering data that
may occur in different experiments or different graph files. The use of manual centers allows for the
clustering implementation to be used as a classifier to compare new data sets to clusters as determined from
either ideal or previously scored data sets.
By Learning
The learning method will use the full k-means clustering algorithm as described above. This consists of
choosing candidate centers, computing mean distances, adjusting the candidate center positions, and
repeating until termination conditions are met.
The data set used to compute the center positions can either be the full data set, a subset of the data or an
event within the data set.
Training Set Definition
The training set is the set of data that is used during the iterative portion of the clustering algorithm that
learns the potential center of each cluster. Training sets are only used for learned centers. There are three
ways to specify a training set for use in clustering:
· Use all of the source data when searching for the centers.
· Allow the training set to be a specific percentage of the total source data set with members of the
training set chosen at random.
· Manually identify the training set with events located in the data.
Partial clustering refers to running the k-means clustering algorithm on only a subset of the source data.
There are a number of reasons to perform partial clustering. One is computational efficiency. K-means
clustering can be a time intensive procedure, as each iteration of the algorithm must recompute all of the
distances to reclassify the entire data set. By performing partial clustering, it is possible to reduce the
complexity of the k-means clustering step by limiting the amount of source data that needs to be processed
in each step. This may be acceptable in situations where perfect partitions are not required.
Another use of partial clustering is to construct a classifier. A classifier is some method for assigning a
particular data point to a specific class. To construct a classifier using k-means clustering a k-means
algorithm is run on a training set that has known desirable data properties for splitting data into a number of
classes. Once the centers of this training set are known, they can be used to perform another clustering
analysis on a set of unknown data and determine how well that data exhibits the properties of the training
set.
Max. iterations
This field is used for entering the maximum number of iterations the k-means algorithm is run. If the
specified number of iterations is reached, processing will halt and centers will not be located.

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Tolerance
This value represents the minimum distance allowed for center adjustment. If the centers move by less than
this value in subsequent learning steps, they will be considered stable and clustering will commence.
Remove Outliers
The clustering analysis allows for optional removal of outliers, or spurious data points. When enabled, each
cluster is assigned a boundary. After each data point has been assigned to the cluster, the standard deviation
of the distance of each point from the center of the cluster is computed. When outlier rejection is enabled,
any data point that is farther away from the center than a specific number of standard deviations will be
removed from the cluster. Enabling outlier removal retains only the points in a cluster that have the
strongest association with each other.
Clustering Criteria
For a particular segment of a waveform, features are
extracted based upon user-specified criteria.
Segment Width
Value (left edge)
Max
Min
Time to Max
Time to Min

Peak to Peak
Time peak to Peak Delta
Sum
Median
Mean
Measurement Result

Multiple segments are located using the Find
Cycle/Peak functionality. After the criteria have been
computed for each segment, clustering is then
performed. This allows segments to be partitioned
based upon their features. For example, “Segment
Width” criteria can be used to partition ECG cycles
into two clusters of shorter segments and longer
segments.
The criteria Segment Widths are reported in milliseconds, as are the other time-based criteria (Time to Max;
Time to Min; and Time Peak-to-Peak Delta). If the measurements are fixed to units of milliseconds, then KMean Criteria results will match measurement magnitude results. Clustering is defined with a hard left to right
directionality for all measurements. Therefore, Delta T will have opposite signs than the same measurement
pasted with Find Peak.
Clustering Output
The output of a clustering analysis can be
presented in multiple ways, including events,
waveforms in the graph, textual tables, and
visual scatterplots. These outputs allow for visual
examination of the clustering results for
anomalies and also provide a foundation for
further data reduction using other AcqKnowledge
tools. By examining waveform data in a reduced
feature space, it may be possible to construct
clustering configurations that allow for
separation of neuron action potentials into
different classes, detection of heart arrhythmias,
and other classification tasks.
One of the traditional methods of presenting
results of a k-means analysis is through
scatterplots.
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Scatterplots are dot plots with a single dot per waveform segment run through the k-means clustering algorithm.
They provide good visual references that can be used to estimate the potential number of clusters actually
present in data and to compare the distinguishing abilities of different sets of criteria.
The scatterplot can be extended into three dimensions to provide feedback on relations between three criteria at
the same time. With each criterion assigned to one of the three coordinate axes, a small sphere centered around
the criteria values for a waveform segment can be constructed. Displaying the spheres for all data points would
create the 3D scatterplot.
To generate 3D criteria scatterplots, select at least three criteria. There is also an option to change the 3D
scatterplot background color and export results to an Excel spreadsheet. (See example scatterplots, next page).

If the “Paste measurement to Journal” preference is set, measurement values will be pasted into the Journal each
time a cycle is found, as shown above. Each column corresponds to a measurement value (in this case, Value
and BPM).
Excel Spreadsheet Export—The cycle detector has also been enhanced to allow for the direct creation of
spreadsheets. The cycle-to-cycle values of the measurements can be inserted directly into an Excel spreadsheet
file. Each measurement is placed into an individual column and each cycle corresponds to a single row. To
generate the spreadsheet a “Find All Cycles” operation is required.
·

Also available for File > Save As, File > Save Journal Text As, and Specialized Analysis tools.

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The following example details how to detect the positive spike in the QRS complex—a typical use of
the Find Cycle (peak detection) function.
1. Select the area around a typical peak.

2. Select Find Cycle (Locate cycles from peaks).
3. Enable “Use selected maximum” on the Cycles/Peaks tab to automatically set an appropriate threshold
value based on the amplitude of the cycle detector.
4. Click the Output tab and choose the desired option(s), such as paste measurement controls to update the
journal with the measurement values from the new peak.
5. Click a Find button.
· Find first cycle – the edge will blink at the first cycle point
· To manually move through the file, click Find next
· Or, select an area and choose Find all
· Or, place the edge in the data and Find all will detect cycles from that point forward.
· Find All Cycles will find all cycles from the beginning of the selected area to the end of the waveform.
· Find in Selected Area will only find cycles in the selected area.
· Find in Focus Area will only find cycles in focus areas.
To use an offset
Use the Selection controls to set a time window around the selected cycle; previous peak controls the left edge,
Current peak has options to control the left and right edges.
1. Use steps 1-4 above.
2. Click the Selection tab.
3. Set the desired edge values.
· For example, to set the time window 0.5 seconds prior to the previous peak.

To control the left and right edges, select current peak and enter the appropriate time window to define an
interval around the cycle.

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Find Rate

The Rate Detector is critical to AcqKnowledge’s ability to extract information from physiological data that has
a degree of periodicity. Physiological data that can be investigated using the AcqKnowledge Rate Detector
includes:
· ECG (e.g. Heart Rate or Inter-Beat-Interval recording)
· Blood Pressure (e.g. Systolic, Diastolic, Mean, dP/dt Max, dP/dt Min)
· Respiration (Respiration Rate measurement)
· EMG (Zero Crossing or Mean Frequency analysis)
The Find Rate function computes rate calculations (including BPM) for data that has already been collected.
Although this function uses the same algorithm as the online rate detector (which uses a Calculation channel), it
can be advantageous to perform rate calculations after the data has been acquired. One benefit is that off-line
rate computations do not require that a separate channel (i.e., a Calculation channel) be acquired. Since the
number of acquired channels is reduced, other data can be collected and/or data can be sampled at a higher rate.
Rate detector settings are graph-independent, which means that find rate operations can be performed in
multiple graphs without needing to re-enter graph-specific settings for each run. By using multiple data views,
different find rate operations can be performed on the same set of data without losing settings between “Find
Rate” operations. When the Rate Detector is first opened for a graph, the dialog will be filled with the values
from the last successfully executed Find Rate operation. Subsequently, changes to the settings will be applied
only to that graph.
Modes of Operation
The Rate Detector incorporates a significant amount of flexibility to optimize performance when extracting data
from periodic physiological waveforms. There are three basic modes of operation for the Rate Detector:
1)
Fixed threshold detect mode
2)
Auto threshold detect mode (enables Noise rejection)
3)
Remove baseline and Auto threshold detect mode
Generally, it’s best to use the simplest Rate Detector mode suitable for a particular application. If the simplest
mode doesn’t work, add layers of sophistication, one at a time. For example:
If the Fixed threshold mode can’t or will not work, use the Auto threshold detect mode.

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If the Auto threshold detect mode is similarly unavailable, adjust the Noise rejection or add the Remove
baseline option.
1) Fixed threshold detect mode:
Fixed threshold detect mode is the simplest mode of operation for
the Rate Detector. As shown here, the Threshold Level has been set
to 0.00 Volts. If the waveform crosses 0 Volts, the Detector will
begin to look for Positive or Negative peaks (based on the Peak
detect setting).
Not available in Fixed mode:
Noise rejection
Baseline window width
Windowing options

2) Auto threshold detect mode:
Auto threshold detect mode is a more advanced and flexible mode of
operation for the Rate Detector. In this case, the Rate Detector will
create a variable threshold defined as:
Positive peak search
0.75 • (Old Peak Maximum - Old Peak Minimum)
Negative peak search
0.25 • (Old Peak Maximum - Old Peak Minimum)
Furthermore, the Rate Detector will construct a moving file of data
points defined by 1.5 times the number of samples that can be placed
in the largest rate window size (defined by the Window settings). If
the Rate Detector loses sync (no trigger event inside the window),
the threshold is changed to the mean value of the moving file of data
points. This operation permits successful recovery in the event
of spurious waveform data values.
The Noise rejection setting creates Hysteresis around the variable
threshold. The Hysteresis level is defined as:
Hysteresis = Noise rejection (%) • (Old Peak Maximum - Old Peak Minimum)

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3) Remove baseline and Auto threshold detect mode:
Remove baseline and Auto threshold detect mode is an advanced
and flexible mode of operation for the Rate Detector. Primarily,
the Rate Detector performs an automatic (and hidden) moving
difference function on the waveform data. The difference function
is performed over a variable number of samples defined by:
# of points = (baseline window width / 1000) * Sampling Rate
This difference waveform is then passed through the variable
threshold:
Positive peak search = 0.75 • (Old Peak Maximum - Old Peak
Min)
Negative peak search = 0.25 • (Old Peak Max - Old Peak Min)
Furthermore, the Rate Detector will construct a moving file of data
points defined by 1.5 times the number of samples that can be
placed in the largest rate window size (defined by the Window
settings). If the Rate Detector loses sync (no trigger event inside
the window), the threshold is changed to the mean value of the moving file of data points. This operation
permits successful recovery in the event of spurious waveform data values.
FIND RATE OPERATIONAL SUGGESTIONS
Option

Waveform Characteristics

Fixed threshold option

·

·

Waveform data has clearly defined positive or negative
peaks (like respiratory or air flow data), which are
consistently higher (in magnitude) than the rest of the
waveform.
waveform data has clearly defined zero-crossings (such as
EMG), and it’s necessary to determine the rate of these
crossings

Auto threshold detect option

·

Waveform data has a moving baseline, but the peaks are
otherwise larger in magnitude than other parts of the
waveform (blood pressure).
It may be necessary to adjust the Noise rejection
(Hysteresis) to optimize performance.

Remove baseline and
Auto threshold detect options

·

Waveform data has high narrow peaks (like most ECG
leads), which may or may not be larger in magnitude than
other (slow moving) parts of the waveform.
It may be necessary to adjust the Noise rejection
(Hysteresis) to optimize performance.

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Signal type
The Signal type menu contains parameters for specific human and
animal waveform morphologies. All pre-defined and custom signal
types are common to both calculation channel Rate (online) and
analysis Rate (offline) dialogs. Signal type modifications affect
settings in the Signal Parameters tab only, and do not affect the
Output tab settings.
Select from six pre-configured signal types or click “New” to
create, name and save custom setups. This allows quick access to
frequently used Rate detection signals without the need to recreate
modified settings. Custom Rate signal types may be added or
deleted in the same manner that channel presets are in other areas of the AcqKnowledge application.
Peak detect
By default, the Peak Detector searches for Positive peaks (upward pointing, such as the R-wave of an ECG
signal) to calculate the rate of a waveform. In some instances, however, it may be necessary to base the rate
calculation on negative peaks (downward pointing). To do this, select Negative peak.
Remove baseline
The Remove baseline option applies a difference operation to preprocess the signal. This option is useful
when signals have a slowly fluctuating baseline.
Auto threshold detect
When the Auto threshold detect box is selected in the Find Rate dialog, AcqKnowledge automatically
computes the threshold value using an algorithm that accentuates peaks and uses information about the
previous peak to estimate when and where the next peak is likely to occur. This threshold detector is typically
more accurate than a simple absolute value rate calculation function, and is able to compute a rate from data
with a drifting baseline and when noise is present in the signal. (For a detailed description of how the
calculation is performed, contact BIOPAC Systems, Inc. for the complete Application Note.)
§ When Auto threshold detect is enabled, the Noise rejection and Window options are enabled.
Threshold level
This option (activated when “Auto threshold detect” is not selected)
allows a threshold level to be used for a simple absolute value rate
calculation function.
§ The Auto threshold detect option is typically more accurate.
Noise rejection
Noise rejection (activated when “Auto threshold detect” is enabled)
constructs an interval around the threshold level. The size of the interval
is equal to the value in the “Noise rejection” text box. Checking this
option helps prevent noise “spikes” from being counted as peaks.
§ The default is equal to 5% of the peak-to-peak range.
Cycle Interval Window
The Cycle Interval Window is used to specify an
upper and lower limit for the Rate calculation.
Window is activated when “Auto threshold detect”
is enabled; the Windowing Units pull-down menu is
only activated when the selected Function can have
variable units. (Hertz, BPM or Seconds.)
Setting the upper and lower bounds for the
“window” tells AcqKnowledge when to start looking
for a peak.

Defaults: Min 40 BPM
Max 180 BPM

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AcqKnowledge will try to locate a peak that matches the
automatic threshold criteria within the specified window.
If no peak is found, the area outside the envelope will be
searched and the criteria (in terms of peak value) will be
relaxed until the next peak is found.
For instance, once the first peak is found, AcqKnowledge
will look for the next peak in an interval that corresponds
to the range set by the upper and lower bounds of the
window. The interval associated with the upper band of
180 BPM is 0.33 seconds (60 seconds ÷ 180 BPM), and
the interval for the lower band is 1.5 seconds (1 minute ÷
40 BPM). If a second peak is not found between .33
seconds and 1.5 seconds after the first peak, then
AcqKnowledge will look in the area after 1.5 seconds for
a “smaller” peak (i.e., one of lesser amplitude).
For those rate functions that require a window interval in
seconds, it’s recommended to enter numbers like .33
seconds and 1.5 seconds (which correspond to the BPM
defaults of 40 and 180). These numbers will be suitable
for detecting the heart rate of an average subject.

Window (Peak Interval)
A simple peak detector uses what is called a threshold-crossing algorithm, whereby each time the amplitude
(vertical scale) value exceeds a given value, the peak detector “remembers” that point and begins searching
for the next event where the channel crosses the threshold. The interval between the two occurrences is then
computed and usually rescaled in terms of BPM or Hz. This is how the AcqKnowledge rate Calculation
functions when all options are unchecked.
In the sample waveform shown here, the threshold was set to 390 mV to detect the peaks of the waveform and
provide an accurate rate calculation. Since it only recognizes signals greater than 390 mV as a peak, this 390mV threshold is referred to as an “absolute threshold.” Most waveforms are not so well behaved, however,
and artifact can be introduced as a result of movement, electrical interference, and so forth. Combined with
actual variability in the signal of interest, this can result in “noise” being included with the signal, as well as
baseline “drift can render absolute threshold algorithms useless.

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Additional Find Rate Dialog Settings, Output Tab

Function
The Rate Detector Function menu lists a variety of calculations, which are discussed below.
Rate (Hz), Rate (BPM), Interval (sec)
The most commonly used function is the Rate (BPM) option, which calculates a rate in terms of beats
per minute or BPM. Rate calculations can also be performed that return a rate value scaled in terms of
frequency (Hz) or time interval (sec). When rate is reflected in terms of a time interval, the time
difference (delta T) between the two peaks is returned. This is sometimes referred to as the inter-beat
interval (IBI). The frequency calculation returns the rate in Hertz (Hz), which is computed by dividing
1 by delta T. These measurements are perfectly correlated with the BPM calculation, since BPM is
equal to 60 times the frequency calculation, or 60 divided by delta T.
Peak time
Returns the time (in seconds) at which the peak occurred. Like the other Rate functions (e.g., BPM and
Hz), the value of the last peak time will be plotted until a subsequent peak is detected. The resulting
plot will resemble a monotonically increasing “staircase” plot.
Count peaks
Produces a plot of the number of peaks (on the vertical axis) vs. time on the horizontal axis. When used
with the delta measurements (in the measurement windows), this is a convenient way to calculate how
many peaks occur within a selected area.
Peak maximum/minimum
Tracks the maximum value of the peak (the ECG R-wave). This correlates to the systolic pressure in
blood pressure readings. To search for minimum peak values, select negative from the Peak detect
section of the dialog.
Peak-to-peak
Looks at the vertical difference between the maximum and minimum values of the waveform on a
cyclical basis—useful when needing to determine the amplitude of the pulsatile signal.
Mean value
Computes the mean of a pulsatile signal on a cycle-by-cycle basis between two peaks; produces a
staircase plot.

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Area
This function computes the area of the signal between two peaks, on a cycle-by-cycle basis.
Sum (not shown)
This function extracts the sum of all amplitudes for each cycle.
Use Averaging Mode
Use this option to average the output of the selected function using values based upon a fixed time window or a
fixed number of cycles. If the average is taken from a fixed number of cycles, there is an additional option to
recompute on every cycle. When unchecked, the output will be reset after the selected number of cycles are
detected and remain fixed until the next group cycles are detected. When checked, the output will start after the
first cycle is detected and will then be refreshed on every cycle.
Output reset events
This option controls the definition of reset event insertion into the graph.
If no thresholds are found within the user-specified window width, the automatically detected threshold level
will “reset” and tracking will start anew; the output of the rate detector function may also drop to zero. When
“Output reset events” is enabled, a reset event will be added to the channel whenever the threshold is reset
due to window expiration
§ This helps distinguish zero-valued output due to
window resetting and true zero-value output.
In the sample shown, the signal drops to zero during a
period of analysis (e.g., due to lead clip falling off).
Reset events indicate automatic threshold tracking was
lost in this interval and the points where the search for
a new level begins.
Put Result in New Graph
When this option is checked, the results from the find rate calculation are plotted in a new graph window with
data displayed in X/Y format, with time on the horizontal axis. By default, this option is unchecked and the
resulting transformation is placed in the lowest available channel of the current graph.
NOTE: When put into a new waveform or used as a calculation channel, the output rate function uses
padding to generate a signal at a continuous sampling rate. The extracted value is used for padding until the
next cycle is detected. This padding can cause unsuitable weighting for statistical analysis. For accurate
statistical analysis with only one value for each cycle, use the offline rate detector "show output in new
window" to produce a "value" waveform with one output point for each cycle. This output is suitable for
export to Excel or other software for statistical analysis.
Find Rate of Entire Wave
When this option is checked, the rate (or other function from the Find rate command) will be calculated for
the entire wave (other than the selected area, if any).
Don’t Find
Saves dialog settings in order to close out of the dialog and select an area. When the dialog is reopened, the
earlier settings will be retained, after which the OK button can be clicked to perform the Find Rate function.
This is useful for setting parameters using an area of a waveform and then repositioning the cursor at another
point in the record.
Specialized Analysis
The Specialized Analysis package includes tools to automate analysis to save hours (or days!) of processing
time and standardize interpretation of results.
A courtesy copy of the Specialized Analysis package is installed under the Analysis menu with
AcqKnowledge™ 4.
See the next chapter for full details.

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Chapter 17

Specialized Analysis
The Specialized Analysis package includes comprehensive
analysis tools to automate analysis to save hours (or days!) of
processing time and standardize interpretation of results.
· AcqKnowledge 5 includes a courtesy copy of the Specialized
Analysis Package under the Analysis menu.
Specialized Analysis provides extensive post-acquisition analysis
options similar to modules from Mindware Technologies,
PONEMAH Physiology Platform, EMKA Technologies, SA and
other advanced analysis applications. If more analysis options,
save the data as MATLAB, Igor Pro, PhysioNet, raw, or text
format—or compress the file to reduce file size by about 60%.
Analyze data collected on Hardware Systems with Windows OS
or Mac OS.
See the Analysis menu on page 327 for other operations that
derive data and measurements from the graph:
Histogram
Autoregressive Modeling
Nonlinear Modeling
Power Spectral Density
AR Time-Freq Analysis
FFT
DWT
Principal Component Analysis
Independent Component Analysis
Find Cycle
Find Next Cycle
Find All Cycles in Focus Area
Find All Cycles
Find In Selected Area
Find Rate

The Specialized Analysis package includes the following Analysis Packages and Classifiers:
Analysis package—bundle of transformations created to assist with analysis in a specific area of research.
Classifier—special-purpose transformation that defines events at well-known points of interest on standard
waveforms, such as the ECG wave boundary classifier and the QRS beat detector and arrhythmia detector.

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Detect and Classify Heartbeats
Locate Human ECG Complex Boundaries
Locate Animal ECG Complex Boundaries
Gastric Wave Analysis
Gastric Wave Coupling
Chaos Analysis
Detrended Fluctuation Analysis
Optimal Embedding Dimension
Optimal Time Delay
Plot Attractor
Correlation Coefficient
Electrodermal Activity
Derive Phasic EDA from Tonic
Event-related EDA Analysis
Locate SCRs
Preferences: Output Display Format; Phasic EDA
Construction Method: Smoothing Baseline Removal or
High Pass Filter
Electroencephalography
Compute Approximate Entropy
Delta Power Analysis
Derive Alpha-RMS
Derive EEG Frequency Bands
EEG Frequency Analysis
Remove EOG Artifacts
Seizure Analysis
Preferences: Output Display Format
Electromyography
Derive Average Rectified EMG
Derive Integrated EMG
Derive Root Mean Square EMG
EMG Frequency & Power Analysis
Locate Muscle Activation
Preferences: Output Display Format
Ensemble Average
Epoch Analysis
Focus Areas
Define Between Events
Define for Appended Segments
Hemodynamics
Classifiers: ABP; LVP; MAP
Arterial Blood Pressure
Baroreflex Sequence Analysis (licensed feature)
Baroreflex Slope Analysis (licensed feature)
ECG Interval Extraction
Estimate Cardiac Output from ABP
Left Ventricular Blood Pressure

Monophasic Action Potential
Preferences: Output Display Format; LVEDP Location
Method; dP/dt pk-pk %; MAP Plateau Location Method;
dP/dt MAP pk-pk %
HRV and RSA
Multi-epoch HRV – Statistical
Multi-epoch HRV and RSA – Spectral
R-R Poincaré Plot
RSA – Time-series
Single-epoch HRV – Spectral
Impedance Cardiography
Body Surface Area
Ideal Body Weight
ICG Analysis
VEPT
PEP Pre-ejection Period
dZ/dt Derive from Raw Z
dZ/dt Classifier: B, C, X, Y, and O Points
dZ/dt Remove Motion Artifacts
Preferences: Output Display Format; C-, B-, and X-Point
Location; Stroke Volume Calculation Method; Body
Measurement Units; Body Surface Area Method; Ideal
Weight Estimation Method; dZ/dt Max Method
Magnetic Resonance Imaging
Artifact Frequency Removal
Signal Blanking
Artifact Projection Removal
Slew Rate Limiter
Median Filter Artifact Removal
Neurophysiology
Amplitude Histograms
Classify Spikes
Average Action Potentials
Dwell Time
Histograms
Generate Spike Trains
Locate Spike
Episodes
Find Overlapping Spike Episodes
Set Episode Width and Offset
Preferences: Detect Spike; Default Episode Width; Default
Episode Offset; Default # of Spike Classes
Noldus
Principal Component Denoising
Remove Common Reference Signal
Remove Mean
Remove Trend
Respiration
Compliance and Resistance
Penh Analysis
Pulmonary Airflow
Spectral Subtraction
Stim-Response
Digital Input to Stim Events Stim-Response Analysis
Waterfall Plot
Wavelet Denoising

AcqKnowledge File Portability

Use Specialized Analysis to analyze AcqKnowledge data files collected on Hardware Systems running on
Windows/PC or Mac OS. Open/save the following file formats:
Opening files for Specialized Analysis
The default file formats (Graph and .ACQ) are referred to as
“AcqKnowledge” files. The AcqKnowledge file format is the standard
way of displaying waveforms in AcqKnowledge. These files are stored in
a compact format that retains information about how the data was
collected (i.e., for how long and at what rate) and takes relatively little
time to read in (compared to text files, for instance). AcqKnowledge files
are editable and can be modified and saved, or exported to other formats
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File Compatibility
§ Mac AcqKnowledge 3.9and above can open and create PC-compatible Graph (*.acq) and Graph Template
(*.gtl) files. Variable sampling rate information and hardware settings are retained, and Journals can be read
from and written to PC files. Files must end on a multiple of the lowest channel sampling rate to be fully PC
compatible.
Saving files after Specialized Analysis
The default file format for the File>Save as command is to save files as an
AcqKnowledge file. Selecting Graph (MPWS) or .ACQ (MPWSW) from
the popup menu in the Save As dialog will save a file as an AcqKnowledge
file, which is designed to be as compact as possible. These files can only
be opened by AcqKnowledge, but data can be exported to other formats.
File > Save Selection As allows saving a portion of the file. When this
option is enabled, only data selected with the I-beam tool will be saved.
This allows saving of the selected area to another file and does not affect
the currently open file.
Saving Files AcqKnowledge 4

File Compatibility
Windows AcqKnowledge 3.9 and above files can be opened with Mac AcqKnowledge 3.9 and above, but some
advanced features may not transfer.
§ Mac AcqKnowledge 3.9 and above can save PC-compatible Graph (*.acq) and Graph Template (*.gtl)
files. Variable sampling rate information and hardware settings are retained, and Journals can be read from
and written to PC files. Choose the format “Graph (Windows)” to create PC-compatible files.
The Mac version does not save compressed PC files.
Files must end on a multiple of the lowest channel sampling rate to be fully PC compatible.
Excel Spreadsheet Export—The Specialized Analysis tools have been updated to automatically export their results to
an Excel spreadsheet if desired. The spreadsheet contents mirror the tabular Journal text output. All the spreadsheets
are saved as temporary files, so they need to be re-saved in order to be saved permanently.
·
Note

Also available for File > Save As, File > Save Journal Text As, and Find All Cycles journal.
Specialized Analysis scripts are complex and undo may not function for all steps.
Some of the specialized algorithms are very complex and processor intensive, so they may take a long (even
very long) time to return a result.
Most specialized analysis operations create additional channels in the graph, thus changing the underlying
data in the source channel. In this instance, attempting to acquire appended data into the source channel of a
graph that has had an analysis operation applied will result in a standard message: “You have modified or
edited data in a way that prevents appending acquisition. You can replace the existing data or abort.” This is
normal for analysis operations that have modified the underlying graph data. Under this circumstance, all
analysis operations will generate this message with the exception of the following:
· DWT/IDWT
· Detect and Classify Heartbeats
· HRV
· Power Spectral Density
· ICA/IICA
· Nonlinear Modeling
· PCA/IPCA

An option to perform analysis on the entire graph or on the focus areas only is presented in setup dialogs for most
Specialized Analysis tools.

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Detect and Classify Heartbeats

This robust QRS detector is tuned for human ECG Lead II signals. It locates QRS complexes and places an event
near the center of each QRS complex to identify the type of heartbeat event:
§ Normal: The beat was recognizable as a valid heartbeat falling in a human heartbeat rate.
§ PVC: The beat was shorter than the beats around it and may be a pre-ventricular contraction. These events can
be found in the “Hemodynamic > Beats” submenu of the event type listing.
§ Unknown: The beat wasn’t recognizable as a valid heartbeat. This may occur on the first beat prior to the
QRS detector locking onto the signal. It may also occur if tracking is lost due to changes in signal quality.
The Cycle/Peak detector may be used with these events to perform further cardiac analysis.
For information on the algorithm used in Detect and Classify Heartbeats, see page 442.
Watch the AcqKnowledge Detect and Classify Heartbeats video tutorial for a detailed demonstration of this
feature.
Locate Human ECG Complex Boundaries

Locate Human ECG Complex Boundaries performs ECG waveform boundary detection for human ECG Lead II
signals; ECG signals must be sampled at 5 kHz or below to be analyzed with this classifier. It will attempt to
locate the boundaries of the QRS, T, and P wave and will define events for each individual complex. It will
attempt to insert the following events; all of these complex boundaries can be found in the “Hemodynamic > ECG
Complexes” submenu of the Event Type listing.
Wave
QRS

T-wave

P-wave

Type
Onset
Peak
End
Onset
Peak

End
Onset
Peak
End

Event Placement & Description
Before the beginning of the Q wave
At the top of the R wave
After the end of the S wave
At the onset of T
At the peak of the T wave
Note: This may not be a positive peak if the T-wave is inverted. If the T-wave seems
to be bi-phasic, two T-wave events will be inserted and the event description
will indicate that the T-wave is bi-phasic.
At the end of T
At the onset of P
At the top of the P wave
Note: This may not be the absolute maximum, but rather the likely center of P.
At the end of P

The Cycle/Peak detector may be used with these events to perform further cardiac analysis.
For information about the algorithm used in Locate Human ECG Complex Boundaries, see page 442.

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Locate Animal ECG Complex Boundaries
Locate Animal ECG Complex Boundaries optimizes the ECG
waveform boundary detection for animal input. Smaller animals
such as mice often lack a detectable T wave, so in the setup dialog
the T wave boundaries are disabled by default. If appropriate to the
experiment, T wave detection can be applied by enabling the
“Define T wave boundaries” checkbox. The average heart rate can
also be customized to reflect the normal range of a particular animal
subject. (The default rate is 600 BPM.)
For information about the algorithm used in Locate Animal ECG Complex Boundaries, see page 441.
See the AcqKnowledge Locate Animal ECG Complex Boundaries video tutorial for a detailed explanation of
this feature.
Gastric Wave Analysis

Gastric Wave Analysis uses autoregressive time-frequency analysis to determine the classifications of gastric
waves present in an EGG signal. The single wave analysis determines the percentage of gastric waves that fall
within the frequency bands corresponding to normal, bradygastric, and tachygastric waves. The analysis also
indicates the percentage of waves that fall outside of these boundaries and are arrhythmias. The frequency bands
are expressed in units of “contractions per minute” and may be adjusted by the user. Presets for commonly used
subject and wave types are predefined; custom presets may be added.
Gastric Wave Coupling

Gastric Wave Coupling takes two EGG signals and uses autoregressive techniques to classify the contractions in
those signals according to user-configurable frequency bands (similar to single channel Gastric Wave Analysis).
In addition to providing classification information for the two signals, Gastric Wave Coupling provides a
measure of the percentage of coupling between the two signals—this measure that can be used to determine the
amount of slow-wave propagation across the stomach.
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See the AcqKnowledge Gastric Wave Analysis and Gastric Wave Coupling video tutorial for a detailed
explanation of this feature.
Chaos Analysis

The “Chaos” analysis package assists the user in exploring the chaotic nature of data, including measurement
selection and visualization of time domain attractors in the data.
Detrended Fluctuation Analysis

Modified root mean square analysis, useful for evaluating self-similarity in a long-term, non-stationary data
series. Source data is mean-adjusted and then integrated; it is then split up into n segments of equal length, and in
each segment, via linear regression, the best fit least squares line is computed. For a particular value of n and a
number of samples N, the characteristic fluctuation of the piecewise linear fit yn. is defined as:

F n

1
Nk

N

y k

yn k

2

1

F(n) is evaluated over a user-specified range for the number of divisions. n will equal the total length divided by
the number of divisions. A log-log plot of the interval width n in samples versus the corresponding value of F(n)
will be created. If a linear relationship appears to exist in this graph, then the source signal displays some form of
self-similarity. The slope of the line in this graph is related to the scaling exponent.
Ü For more information on Detrended Fluctuation Analysis, see http://www.physionet.org/physiotools/dfa/
Optimal Embedding Dimension

Indicates the number of times the dimensionality of the data is increased by adding additional copies of the data.
Many of the fractal measurements take an embedding dimension parameter. Increasing the dimensionality of the
data may improve the quality of the results. In general, embedding dimensions should always be less than 8.
After the most relevant time delay for the data has been selected, Optimal Embedding Dimension assists in
choosing the embedding dimension that appears to give the most accurate results. The embedding dimension is
chosen to be the earliest dimension in the search range where the fractal correlation dimension measure reaches a
local maximum. This indicates the lowest dimension where the data has the potential to exhibit the most selfsimilarity.
§ Since real data may not be fractal in nature, there may be no local maximum for the embedding dimension. In
this case, it is not possible to determine the optimal dimension.
Optimal Time Delay

This algorithm assists in picking a time delay that is most relevant for the data. It locates the earliest time delay in
the specified interval range where the mutual information measurement reaches a local minimum.

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Optimizing the time delay in this fashion picks the shortest delay where the signal exhibits the most independence
with respect to its time-delayed version.
The fractal dimension and other chaos-related measurements operate on a single channel of data. In the process of
extracting these measures, a signal is compared with a time-delayed version of itself to examine the patterns in
dynamics of the data. These measures take a fixed time delay setting. The Optimal Time Delay transformation can
be used to choose the best value for the parameter.
Plot Attractor

Assists in constructing X/Y plots for the attractors of time
delayed data. By visually examining the shape of the attractor
at a given time delay, To develop an intuitive sense for the
underlying nature of the data and the dynamics of the system.
Plot Attractor functions on the active channel of the graph. It
prompts the user for a time delay and then constructs a new
graph window with an X/Y plot of the attractor of the original
signal against the time delayed version of the signal. It does
not perform any additional computation aside from assisting
in the setup and configuration of the attractor plot.
Correlation Coefficient

The correlation coefficient is a statistical measure related to the degree of variance or covariance between two data
series. Given two data series x and y of length n, the correlation coefficient r is given by the formula:
(see http://mathworld.wolfram.com/CorrelationCoefficient.html)
The square of the correlation coefficient can be used to determine the proportion of variance in common between the
two signals. As the square gets closer to 1, the signals are a better statistical match for each other.
To derive the correlation coefficient, two channels of data are compared against each other.
· the channels must have the same length
· the channels must have the same waveform sampling rate
· all of the data of the entire graph for the two channels will be used to compute the correlation coefficient.
H

Electrodermal Activity

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Overview
The Electrodermal Activity (EDA) analysis routines are separated into three menu options that transform the tonic
EDA signal to create a phasic waveform, locate and score skin conductance responses, or perform a detailed eventrelated EDA analysis by combining event information from the Stim-Response: Digital Input to Stim Events routine
(see page 436) to the event-related EDA Analysis routine. The Event-related routine will automatically derive the
phasic waveform and locate SCRs.
The routines employ a scoring system that marks the waveform and the point of stimulus delivery. It’s easy to
manually adjust the automated scoring by relocating the event onset/peak/end before rerunning the analysis. The
event-related analysis provides a variety of measures from the SCR data, including classification of specific and nonspecific responses. The results are pasted into the journal file or Excel for further analysis.
Preferences must be established for each routine and can be adjusted at any time via the Preferences option (page 380).
The time to complete the analysis routine will vary based on the number of SCR responses and the sample rate of the
data.
Definitions
The prompts and results of the Electrodermal Activity analysis package use the following terminology and units:
µmho—the unit abbreviation for micromhos, used in channel labels and analysis results; micromho is equivalent
to microsiemens.
EDA (Electrodermal Activity)—the general area of skin conductance signals. Sometimes referred to by the older
term “galvanic skin response.”
Tonic EDA—continuous data acquired from an EDA electrode that includes all baseline offset. Sometimes
referred to as “skin conductance level.” Averaging the tonic EDA over a specific period of time results in the
average skin conductance level over an interval. Tonic EDA is recorded using BIOPAC equipment with the high
pass filtering set to off (DC mode).
Phasic EDA—a continuous signal indicative of localized changes in the tonic EDA signal. Sometimes referred to
as “continuous skin conductance response.” Phasic EDA can be thought of as AC coupled tonic EDA. The EDA
analysis package offers multiple ways of constructing phasic EDA including smoothing and high pass filtering.
The EDA analysis package performs the majority of its analysis on tonic EDA signals, so if phasic EDA is being
recorded directly it is recommended that a second channel be used to record tonic EDA.
Skin Conductance Response (SCR)—an individual localized change in the tonic EDA signal. An SCR may occur
in response to a stimulus or may occur spontaneously. In general, there are multiple SCRs present in a tonic EDA
signal and they can be detected as deflections from the localized baseline.
Reference
The Electrodermal Activity analysis package was developed to support the parameters established in:
M. E. Dawson, A. M. Schell, and D. L. Filion. The electrodermal system. In J. T. Cacioppo, L. G. Tassinary, and
G.B. Bernston, editors, Handbook of Psychophysiology: second edition, pages 200–223. Cambridge Press,
Cambridge, 2000.
Derive Phasic EDA from Tonic
Given a tonic EDA signal, this transformation uses baseline smoothing or high pass filtering (the method
currently set in Preferences) to construct a new Phasic EDA channel in the graph containing the estimate of the
phasic EDA. This routine is automatically included in both the locate SCR and Event-related EDA routines.
Phasic EDA refers to a continuous signal indicative of localized changes in the tonic EDA signal. This data is
sometimes referred to as “continuous skin conductance response.” Phasic EDA can be thought of as AC coupled
tonic EDA. The EDA Analysis Package offers multiple ways of constructing phasic EDA including smoothing
and high pass filtering. The EDA Analysis Package performs the majority of its analysis on tonic EDA signals, so
if phasic EDA is being recorded directly it is recommended that a second channel be used to record tonic EDA.

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Event-related EDA Analysis

Sample EDA Analysis Output

All SCR events are marked on the tonic waveform as
follows:
( open paren.

The point at which the phasic signal
crosses the SCR threshold level
established in EDA Preferences; see
page 380

blue waterdrop

blue marks the peak response of a
nonspecific, event-related SCR

red waterdrop

marks a specific SCR “SRR” with a
flag numbered with the stimulus event
type
The point at which the phasic signal
crosses the zero threshold level

) close paren.

The Event-related EDA Analysis transformation routine assists in the extraction of EDA measures that are linked
to specific stimuli. The stimulus event marks must be included in the file BEFORE using this analysis.
This analysis routine requires four elements:
1. Tonic and Phasic waveforms.
Tonic EDA Channel: A Tonic EDA signal must be present in the graph.
Phasic EDA:
Construct new: Given a tonic EDA signal, a phasic EDA will be automatically constructed using
baseline smoothing or high pass filtering (the method currently set in Preferences).
Use Channel: If the graph contains a phasic waveform, select the appropriate channel.
2. Stimulus delivery events.
Digital events with a common event type must be located BEFORE using this analysis.
The Event-related EDA Analysis requires that an event be defined in the graph at the location of the
delivery of each stimulus. This event may be defined using the Event Tool, hotkey insertion during
acquisition, or any other method of defining events. All of the stimulus delivery locations to be
extracted must have the same event type (e.g. “Flag”). To analyze multiple different event types, the
transformation script must be executed multiple times.
§ If using E-Prime, SuperLab, or some other stimulus delivery system and have the digital events
captured in the AcqKnowledge file, it’s recommended to use the Stim-Response: Digital Input to
Stim Events routine (see page 436). This routine will automatically classify and label the digital
events for use by the Event-related EDA analysis.
Stimulus event type: If using the Digital Input to Stim Events, select Stim/Response > Stimulus
Delivery. Stimulus delivery events are located by event type or by specific channel of the graph.
Stimulus event location: Specify the location as anywhere, global only, or on a specified channel.
See the Events section for details.
3. Skin conductance responses.
If the tonic EDA signal does not already have SCR events defined on it, SCR events will be
automatically constructed on the channel using the Locate SCRs transformation routine.
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4. Specified time window between the stimulus event and the skin conductance response.
The transformation takes a maximum allowable separation window between the stimulus event and
SCR response. Each stimulus delivery event is paired with the closest SCR event. SCRs that
correspond to a stimulus delivery are known as specific SCRs (abbreviated “SRR”). SCRs generally
occur within a certain timeframe after stimuli. The time window allows responses too close to stimuli
to be rejected and classified as non-specific.
Minimum separation: specify in relation to the stimulus event (includes time unit options).
Maximum separation: specify in relation to the stimulus event (includes time unit options).
Given a response time window [resmin, resmax], for each stimulus delivery event at a time t, SCR onset
events that are not presently matched as SRRs will be searched for in the window [t+ resmin, t+
resmax]. The SCR onset event within this window closest in time to [t+ resmin] will be paired with the
stimulus event and considered a SRR.
SRR are marked as a red waterdrop icon with a flag numbered with the corresponding
stimulus event type when “Output events for specific SCRs” is enabled.
Each SRR will be
matched to only one
stimulus delivery event. If
the closest SCR to a
stimulus is farther away
than this time interval, it
is not assumed to be a
response to the stimulus.
It may be a response to a
later stimulus or it may be
a non-specific SCR that
occurred spontaneously.
Output Events for Specific SCR
Enable this option to mark Specific skin conductance events as a red waterdrop icon with a flag numbered with
the corresponding stimulus event type. If the EDA graph channel already contains Specific SCR events when
applying the Output events option, the following prompt will appear:

Click “Replace” to remove and replace the existing Specific SCR events. Note that regular SCR (blue
waterdrop) events are not affected by applying the Output events option. To manually adjust the position of the
regular SCR events, select the SCR event by clicking it, open the Event palette, and edit the event time value in
the Location field. Alternatively, SCR events can also be repositioned by selecting the event, pressing the Alt
key and dragging to the desired position.

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Event-related EDA Analysis Output Options
Enhancements provide more options for multiple stimulus event types and unmatched events, including:
§ Labels and additional measures are available in the specific stimulus and SCR analysis table
§ Text and Excel tables may be optionally sorted either by time or grouped by stimulus label
§ A new table has been added listing stimulus events that were not paired with an SCR
§ The SRR/NS.SSR Rate analysis, which counts frequencies of SCRs in specific time periods, may
now be driven by time periods defined using pairs of events or a selection in the graph
§ A table has been added listing amplitude/frequency percentage statistics for all matched and
unmatched stimuli events (e.g. total stimulus count, percentage of stimuli that were pared with an
SCR, etc.)
§ Additional optional Specific-SCR events may be defined on the tonic EDA waveform at the
positions of specific SCRs with labels matching the stimulus to which they were responses. This
allows for further peak-detector based runs to perform additional data reduction.
Event Related EDA Event Types:
§ Waveform Onset
§ Waveform End
§ Skin Conductance Response
§ Specific SCR
Waveform Onset and Waveform End events are also available for other Specialized Analysis operations.
Amplitude Summary Output Options
For each specific SCR that is paired with a stimulus delivery event, the following measures are extracted in
table format and can be sorted by Time or by Event label. If text output is enabled in EDA Preferences, the
average value of SCL, Latency, SCR Amplitude, and SCR Rise Time will be included as the final row of the
table.
Name

Abbrev.

Description

Units

Stim Time
Stimulus
Delivery Time

The time within the recording where the stimulus delivery event
was located.

seconds

SCL
Skin
Conductance
Level

Amplitude of the tonic EDA signal at the time when the stimulus
was delivered.

µmho

seconds

Response
Latency

Latency

Time separating the stimulus delivery from the onset time of the
corresponding SCR.
This latency will always be less than the maximum allowable
latency specified as a parameter for the analysis.

SCR
Amplitude

SCR
Amplitude

Height of the corresponding SCR as determined by the change in
the tonic EDA amplitude from the time of SCR onset to the
maximum tonic EDA amplitude achieved during the SCR:
[EDA(tmax) – EDA(tonset)]

SCR Rise
Time

SCR Rise
Time

Time taken for the tonic EDA to reach its maximum value within
the SCR:
[tmax - tonset]

Absolute
SCR Size

SCR Size

Contains the SCR Size, which is the absolute amplitude of the
paired SCR event. This is the amplitude of the “SCR” event in the
triplet. Formula: EDA [tmax]

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Name

Abbrev.

Description

SCR Onset
Threshold

SCR Onset Contains the absolute amplitude of the waveform onset event of
the specific SCR. Formula:
EDA [tonset]

Stimulus
event label

StimLabel

Contains the label of the stimulus delivery event.

Units
µmho

N/A

The SCR Size and Onset Threshold values will be included for the textual table, graphical channel output, and
in the Excel spreadsheet. The stimulus event label will be included only in the textual and Excel spreadsheet
output; it is not possible to represent textual information in graph channels.
Sorting Options
The output table rows may appear in one of two orderings.
·

“Sort tables by time” - Consecutive rows will be arranged in order of increasing time.

·

“Sort tables by event label” - Case-sensitive lexicographical sort based on the StimLabel column; “AAAA”
will be considered as unique from “aaaa” / “AaAa”, etc.
SSCR/NSSCR Summary Count Options
In addition to the above measures extracted for each specific SCR, the analysis performs rate extractions for
specific and non-specific SCRs. By examining how the rate of SCR occurrences changes, long-term
experimental trends can be investigated. This analysis is placed into a second set of waveforms (or a second
table for text and Excel output).
Fixed width: fixed width window is specified as the “SCR count interval width” when performing the analysis.
The entire recording is split up into fixed-width epochs of this granularity with the first epoch aligned at the
start of the recording. For each fixed-width epoch, the following are extracted:
Name
Epoch Start
Time

Abbrev.
Start Time

Description
Time location in the recording of the start of the epoch being
examined.

Units
seconds

Specific SCR SRR
Rate

Frequency of the occurrences of specific SCRs within the epoch. Hz
Specific SCRs are those SCRs that were successfully matched to
a corresponding stimulus delivery event.

Non-specific
SCR Rate

Frequency of the occurrences of non-specific SCRs within the
epoch. These are SCRs that occur spontaneously and are not
paired with any known stimulus.

NS.SRR

Hz

Between event pairs: Select an event type from the pull-down menu. The software will locate the event
markers at the beginning and end of the region of interest and perform the analysis between the two points This
option is useful if the recording is broken into defined periods—such as baseline, event, and response—using
the event hotkeys.
Manually selected area: Highlight the area where NSSCR/SSCR rates
should be computed and then click “Do EDA Analysis” in the graph window.

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Amplitude/Frequency Percent Summary
The “Stimulus Matching Summary” table for Textual and Spreadsheet output provides overall summaries for
each unique event label for Stimulus Delivery events. The table has one line for each unique event label; the
labels are numbers starting with 1.
This table provides an overall average for amplitude, magnitude and % Frequency for the specific SCR
associated with Stimulus Delivery events. In this case, frequency is referring to the ratio of Stimulus Delivery
events to the occurrence of specific SCRs.
Assume we have a set S of all Stimulus Delivery events of an identical label.
This will be split into two subsets: Smatched consisting of all Stimulus Delivery events that have an associated
SCR with them, and Sns consisting of the non-specific stimulus events that do not have an associated SCR with
them. Given these sets, the following definition holds:
For an individual event, define the SCR Amplitude function:
The following are the definitions of measures that will be included in the table:
Name

Abbrev.

Description

Units

Amplitude

Amplitude

Average value of the SCR amplitude of the specific SCR events. Defined by the
following formula:

umho

Magnitude

Magnitude

Weighted average of the SCR amplitude of the specific SCR events over the entire
set of specific and non-specific events. Defined by the following formula:

umho

Matched

Matched

Total number of specific SCRs associated with a Stimulus Delivery event. Defined
by the following formula:

Nonmatched

Nonmatched

Defined by the following formula:
Non-matched = Stimulus Delivery Total count – Specific SCR Total count

Total

Total

Total count of Stimulus Delivery events. Defined by the following formula:

Frequency
(%)

Freq%

Percentage of stimulus events that were paired with an SCR. Defined by the
following formula:

Label

Label

Textual label of the events that are included in S.

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Locate SCRs

The Locate SCRs routine will identify skin conductance response and score the waveform. This analysis is useful
for analyzing spontaneously occurring skin conductance responses. The routine is automatically included in the
Event-related EDA routine. All SCR events are marked on the tonic waveform as follows:
(

open paren.

The point at which the phasic signal crosses the SCR threshold level established in EDA
Preferences; see page 380

blue waterdrop The peak response point of a nonspecific, event-related SCR
) close paren.
The point at which the phasic signal crosses the zero threshold level

This transformation requires a tonic EDA signal. If a phasic EDA has already been constructed for this tonic
EDA, it may be used; otherwise, the transformation will create a phasic EDA automatically according to the
settings in the Preferences.
Given a tonic EDA, the Locate SCRs transformation defines an event for each skin conductive response in the
tonic EDA. SCR location is a two stage process. First, all potential SCR occurrences are located on the signal.
Second, all potential SCR occurrences that are not large enough are rejected.
Potential SCR occurrences are detected by performing thresholding positive peak detection on the phasic EDA
signal (using H and P as set via Preferences):
1. Given a detection threshold H (expressed in µmho), search for a positive threshold crossing in the
phasic EDA signal. This position is recorded as the start of the potential SCR.
2. Continue examining the phasic EDA until the first negative threshold crossing of 0 µmho occurs. This
position is recorded as the end of the potential SCR.
3. Return to step 1 to continue searching for more potential SCRs.
After all of the potential SCRs have been located, the set of valid SCRs is constructed as follows:
1. Determine the overall maximum amplitude of the phasic EDA signal within all potential SCRs.
2. Given a percentage P, construct a threshold level T of P percent of the overall maximum phasic EDA
signal value located in step 1.
3. Examine each potential SCR. Find the maximum phasic EDA. If m < t, discard the potential SCR.
Mark the potential SCR as a valid SCR.
If the tonic EDA channel chosen for analysis already has SCR events defined on it, the SCR events will be
replaced with the newly detected SCR events. No existing SCR events will be erased without a confirmation.
Once SCR events have been defined, they can be used in conjunction with the Cycle Detector for performing
further data reduction. The “event count” measurement can be used to estimate SCR frequency during individual
time ranges of the experiment.
Events on Tonic EDA
After valid SCRs are located using the algorithm above, events are inserted into the graph that can allow for
further data analysis around the SCR positions. Three events are defined on the tonic EDA waveform for each
individual valid SCR:
1. “General > Waveform onset” event at the SCR onset time. This is the point where the threshold H was
crossed in the phasic EDA.
2. “EDA > Skin conductance response” event at the time where the tonic EDA reaches its maximum value
within the SCR (max in time range).
3. “General > Waveform end” event at the ending SCR time. This is the point where the zero threshold was
crossed in the phasic EDA.

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Events for SCRs will always occur as described above, in the order shown.
EDA Measurements
To perform Event-related EDA analysis, choose Analysis > Electrodermal Activity > Event-related EDA Analysis.
To take measurements from the skin conductance response analysis, set measurements for event count, event location
and/or event frequency. Set the source channel as the Tonic EDA channel and select the location (measurement
channel only, global events only, anywhere) and measurement parameters as desired. This method is useful for
spontaneously occurring skin conductance response analyses. Take measurements over a manually selected area or
use Find Cycle analysis to take automatically measurements over a user-defined time interval.

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EDA Preferences…

The following EDA Preferences can be configured and will be applied to all options in the analysis package:
· Display results as text, graph channels, or Excel
· Construct Phasic EDA using High pass Filtering or Smoothing Baseline Removal
o High pass Filtering—High pass filtering constructs phasic EDA by applying a digital IIR high pass filter
(f = 0.05 Hz, Q = 0.707) to the tonic EDA signal. This high pass filter essentially AC couples the tonic
EDA signal similar to using the high pass hardware filter available on the GSR100C module.

0.05 Hz High Pass Filter

Smoothing Baseline Removal

o
·

Smoothing Baseline Removal—Smoothing baseline removal constructs phasic EDA by subtracting an
estimate of the baseline conductance from the tonic EDA. Set the baseline estimation
Baseline estimation: The estimate of the baseline is generated using median value smoothing. This is more
computationally intensive than high pass filtering. Increasing the window will increase sensitivity and return
more responses.

Baseline window set to 4 seconds

·

Baseline window set to 8 seconds

SCR detection parameters: threshold detection level H and percentage P, see page 378.
o The default values are H = 0.02 µmho, P = 10, where H is detection threshold and P is percentage
o Setting H to 0 and P to 10% will approximate the SCR detection algorithm referenced in
K. H. Kim, S. W. Bang and S. R. Kim, “Emotion recognition system using short-term monitoring of
physiological signals,” Medical & Biological Engineering & Computing, vol. 42, pp. 419-427, 2004.
o Setting P to 0% will retain all potential SCRs (none will be rejected in the second phase).

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Electroencephalography

Compute Approximate Entropy

Approximate entropy is a statistical measure that attempts to quantify the predictability of a data sequence. A
perfectly predictable data series (such as a pure sine wave) has approximate entropy of zero. Several studies are
beginning to examine approximate entropy of EEG data and its relationship to external factors such as drugs and
sleep states.
The Compute Approximate Entropy script divides an EEG signal into fixed-width epochs and computes the
approximate entropy for each epoch. Derivation of the approximate entropy is a computationally intensive process
and may take several minutes or hours to complete. To obtain only the sub-ranges of the EEG data, use the “focus
areas only" option to restrict the approximate entropy computations to that data range only.
Delta Power Analysis

Delta power is the total power of the EEG signal that occurs within the delta frequency band as configured in the
Preferences. Delta power has been examined in a number of various EEG studies as an indicator of
sleep/wakefulness and other conditions. By examining changes in the delta power, it may be possible to correlate
delta power with effects of external factors.

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The Delta Power Analysis script divides an EEG channel into fixed-width epochs. For each epoch, the power
spectral density is computed and the total power within the delta frequency band is derived from the PSD. This
delta power value is then placed into the graph or into the journal as specified by the output preferences.
Delta power can be measured from either a filtered or unfiltered EEG channel.
Derive Alpha RMS

The Derive Alpha RMS script constructs an integrated RMS waveform from an alpha EEG signal (the alpha EEG
signal can be constructed with Derive EEG Frequency Bands). Alpha RMS is the windowed root mean square
value of the signal using a window width of 0.25 seconds. Individual channels are selectable for analysis.
Derive EEG Frequency Bands

The Derive EEG Frequency Bands script applies filtering to an unfiltered EEG lead signal to generate the
following five standard EEG bands: Alpha, Beta, Theta, Delta, and Gamma.
The frequencies for each band are specified n the analysis package preferences. Filtering is performed using the
digital filter, IIR Band Pass Low+High.

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EEG Frequency Analysis

EEG may be characterized in terms of frequency and the power within specific frequency bands. The EEG
Frequency Analysis script performs various feature extractions from EEG signals using FFT and other techniques
to examine the power within the EEG signals. This analysis may be performed for multiple EEG leads
simultaneously, allowing for either analysis of multiple leads or analysis of multiple EEG alpha, beta, theta, or
delta bands from a single raw lead.
The EEG Frequency Analysis script divides the EEG signals into fixed-width time epochs. For each individual
time epoch, AcqKnowledge’s Power Spectral Density function is used to estimate the power spectrum of that
epoch using a Welch periodogram estimation method. From this PSD the following measures are extracted for
each epoch:
Name

Abbrev.

Description

Units

Mean Power

MeanP

The average power of the power spectrum within the epoch.
(Units Note: V will be replaced with the voltage units in which
the EEG was recorded)

V2
Hz

Median
Frequency

MedianF

Frequency at which 50% of the total power within the epoch
is reached.

Hz

Mean
Frequency

MeanF

Frequency at which the average power within the epoch is
reached.

Hz

Spectral Edge

Spectral
Edge

Frequency below which a user-specified percentage of the
total power within the epoch is reached. This percentage can
be set using “Preferences” and defaults to 90%.

Hz

Peak
Frequency

PeakF

Frequency at which the maximum power occurs during the
epoch.

Hz

Watch the AcqKnowledge EEG Frequency Analysis video tutorial for a detailed demonstration of this feature.

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Seizure Analysis
Seizure Analysis is designed to enhance functionality of the Epoch
wireless EEG system commonly used for acquiring small animal signals.
Long term EEG recording is often used for studying seizure activity.
Unlike human EEG, EEG for non-anesthetized animals may contain a
variety of superimposed artifacts resulting from random motion and
scratching. Seizure Analysis offers a reliable means of differentiating
actual seizure activity from other types of motion artifact.
The Seizure Analysis tool consists of a configurable difference interval,
slope threshold, time epoch width and spike detector. Using the default
values found in the figure above, seizure activity is defined as follows:
1. Perform a difference on the EEG data with a 16 ms window
width. At this window width, normal EEG spikes in the signal
have a roughly logarithmic distribution.
2. Identify maximum threshold for normal spike distribution,
chosen at 270 microvolts on the difference signal.
3. Perform peak detection on the difference signal with the fixed
chosen threshold. Spikes above this threshold are considered candidate epileptic spikes and marked with a
check mark on the waveform.
After spikes are located seizures will be located using a spike frequency method:
1. Split data up into 10 second periods.
2. Count the number of spikes in each period. If more than 20 spikes occur within the period, the period is
marked as a seizure.
Using Seizure Analysis
1. Analysis > Electroencephalography > Seizure Analysis and set the EEG data results preferences if necessary.
(See page 387)
2. If more than one EEG channel is to be analyzed, as is often the case with the Epoch EEG system, the
following selection screen will appear. If there is only one channel of EEG data in the file, this screen will not
be displayed and the seizure analysis screen depicted above will appear.

3. Set the desired parameters for seizure detection and click OK.

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If the EEG Analysis Preferences are set to display
results as graph channels, two new channels of data will
be created. The first channel shows a tachogram of the
number of epileptic spikes identified within the Time
epoch. The second channel displays a square wave that
runs from 0 to 1; a 1 indicates that an epoch matches
the seizure threshold. In the default setting, 20 seizure
spikes have to be identified within a 10 second epoch
for the epoch to be classified as containing a seizure.
If the “Output focus areas for seizures” option is
checked, a focus area is created for each epoch that
contains a seizure. This option is useful for running
additional analysis routines and taking measurements
over just the areas of data that contain seizures.

Seizure Analysis Parameters
CONTROL

DESCRIPTION

Difference Interval

Alters the time window used to compute the difference for
slope detection. Default value is 3.2 samples.

Show difference output

The difference interval used for spike detection will be
displayed in the graph.

Difference threshold level

Adjusts the fixed threshold level used to locate peaks in
the difference signal corresponding to EEG spikes
associated with seizures. Default value is 270 microvolts.

Time epoch width

Adjusts the time width used for seizure detection. Default
value is 10 seconds.

Spike count threshold

Sets the number of spikes that must be present in the
specified time window (epoch) in order to be indentified
as seizure activity.

Analyze: entire graph

The entire graph is scrutinized for potential seizure
activity.

Output focus areas for seizures

In addition to normal output, the analysis will create focus
areas in the graph at each identified seizure period.

Analyze: focus areas only

Only focus areas will be scrutinized for potential seizure
activity.

Output events for seizure intervals

A pair of “waveform onset” and “waveform end” events
will be created at boundaries of identified seizure areas.

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Spike Event Output
For all types of seizure analysis output, this analysis will leave Stim-Response
events on the EEG channel wherever
spikes are detected according to the analysis parameters. These events allow for visual verification of spike detector
functionality. If any Response events are found on the EEG channels at the start of the analysis, then following dialog will
be presented:

Clicking “Yes” removes the existing events. Only Response type events will be removed from the EEG channels; other
types of events, or events on other channels will not be affected.
Watch the AcqKnowledge Seizure Analysis video tutorial for a detailed demonstration of this feature.
Remove EOG Artifacts

Some EEG recordings involve subjects performing various visual tasks such as reading or watching video. Under
these conditions, EEG may be susceptible to interference from the much stronger EOG signal arising from eye
motion, particularly if EEG is recorded from near the front of the skull. Remove EOG Artifacts helps remove EOG
interference from the EEG signals, recovering the EEG data for use in further analysis.
EOG removal is performed using a blind signal separation technique known as Independent Component Analysis.
ICA is used to split up statistically independent signals that have been mixed together during recording. Since EOG is
independent of EEG, ICA can be used to remove it.
In order to use Remove EOG Artifacts, a distinct EOG signal must be acquired in addition to the EEG signals. The
EOG signal is required to identify the components correlated to eye motion.
EOG artifact removal functions better when it is performed on multiple EEG leads simultaneously. Better results may
be obtained by including EEG leads that do not exhibit EOG interference since the increased number of leads allows
for more fine-grained signal separation. Good results can be seen with as few as two EEG leads and one EOG lead.
While this technique can be performed with a single EEG lead, the results will not be as dramatic.
Note ICA is a non-deterministic technique, so it may not be possible to automatically separate the signals for
every EOG/EEG data set. For ICA to be successful, it may be necessary to fine-tune the parameters of the
ICA search procedure to match the data, use a different electrode configuration, or use fewer or more
leads.

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Preferences…

Adjust the EOG ICA Tolerance level and the EOG ICA maximum number of iterations by accessing Transform >
Specialized Analysis > Electroencephalography > Preferences. EOG ICA Tolerance is used as the termination
condition of ICA signal separation. The EOG ICA maximum number of iterations is another termination
condition of ICA signal separation and represents the maximum point at which the search is aborted. For more
information on these settings, see the documentation for the Independent Component Analysis transformation.
Because ICA is a statistical technique, any filtered data produced with Remove EOG Artifacts should be carefully
verified against other information to ensure that the approximations produced via ICA represent information that
is truly correlated to the expected ECG.
The spectral edge percentage indicates the cutoff percentage of the total power at which spectral edges will be
placed. The default value is 90%.
The frequency bands of alpha, beta, delta, and theta may be modified to match different analysis protocols. The
default frequency ranges are:
· Alpha—8 Hz-13 Hz
· Beta—13 Hz-30 Hz
· Delta—0.5 Hz-4 Hz
·
·

Theta—4 Hz-8 Hz
Gamma—36 Hz-44 Hz

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Electromyography

Derive Average Rectified EMG

Average rectified value (ARV) is defined as a time windowed mean of the absolute value of the signal. ARV is
one of the various processing methods used to construct derived signals from raw EMG data that can be useful for
further analysis.
To perform ARV, a time window must be specified for the sliding mean. The default time window setting is 30
milliseconds, but this value can be adjusted depending on the desired amount of smoothing effects. It is advisable
to closely examine results for time windows larger than 30 milliseconds as it is possible for delay to be introduced
into the result.
The ARV is computed using the Integrate transformation with a Rectified Average over Samples configuration.
Derive Integrated EMG

Integrated EMG (iEMG) is defined as the area under the curve of the rectified EMG signal, that is, the
mathematical integral of the absolute value of the raw EMG signal. When the absolute value of the signal is taken,
noise will make the mathematical integral have a constant increase. Integrated EMG splits up the signal into
fixed-width timeslices and resets the integral at the start of each timeslice. To derive iEMG, the width of this
timeslice must be specified. Similar to ARV, timeslices longer than 30 milliseconds may introduce delay into the
result.
The integrated rectified EMG signal will appear like a “sawtooth” style wave. In addition to the true iEMG, this
script will output a second waveform whose value is the maximum value of the iEMG signal in each timeslice.
This Maximum iEMG is easier to interpret visually and approximates the envelope of the iEMG signal.

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Derive Root Mean Square EMG

Root Mean Square EMG (RMS EMG) is defined as the time windowed RMS value of the raw EMG. RMS is one
of a number of methods used to produce waveforms that are more easily analyzable than the noisy raw EMG.
To construct the windowed RMS signal, a time window must be specified for the sliding mean. The default time
window setting is 30 milliseconds, but this value can be adjusted depending on the desired amount of smoothing
effects in the RMS EMG. It is advisable to closely examine results for time windows larger than 30 milliseconds
as it is possible for delay to be introduced into the result.
RMS EMG is computed using the Integrate transformation in a Root Mean Square Average over Samples
configuration.
EMG Frequency and Power Analysis
Several frequency domain techniques may be used for data reduction of EMG signals. The EMG Frequency &
Power Analysis script extracts several measures derived from the power spectrum of an EMG signal. The EMG
signal is split up into a fixed number of time periods; within each window, the power spectrum is computed using
the Power Spectral Density transformation. For each time period, the following measures are extracted:
Name

Abbrev.

Description

Units

Median
Frequency

MedianF

Frequency at which 50% of the total power within the epoch
is reached.

Hz

Mean
Frequency

MeanF

Frequency at which the average power within the epoch is
reached.

Hz

Peak
Frequency

PeakF

Frequency at which the maximum power occurs during the
epoch.

Hz

Mean Power

MeanP

The average power of the power spectrum within the epoch.
(Units Note: V will be replaced with the voltage units in
which the EMG was recorded)

V2
Hz

Total Power

TotalP

The sum of the power at all frequencies of the power
spectrum within the epoch.
(Units Note: V will be replaced with the voltage units in
which the EMG was recorded)

V2
Hz

Locate Muscle Activation

When performing gait analysis, exercise physiology, or other research, identification of periods where the muscle
is active can allow for correlation of external factors to muscle activity.
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Locate Muscle Activation attempts to identify various periods of muscle activity using statistical methods. The
transformation requires a raw, unfiltered surface EMG channel. It takes a window width of w seconds, by default
0.25 seconds. It is important that the first w seconds of the EMG signal be “background noise”, that is, that the
muscle being examined is relaxed for the first quarter second. This quarter-second period is used to estimate
baseline parameters that affect the entire process.
Note The LMA analysis expects EMG to be an AC-coupled signal centered around zero without baseline offset.
If the signal is centered below zero, then no muscle activations are located. The Remove Mean function
from the Analysis menu can be used to center the signal around zero for most waveforms.
This transformation implements a variation of the Hodges and Bui detection algorithm as described in:
P. W. Hodges and B. H. Bui, “A comparison of computer-based methods for determination of onset of muscle
contraction using electromyography,” Electroenceph. Clin. Neurophysiol., vol. 101, pp. 511-519, 1996.
The variation implemented is a threshold-based algorithm roughly consisting of the following steps:
1. Determine mean value
and resting standard deviation of the first w seconds of the signal.
2. Construct a filtered ARV EMG signal, z. The window width w is used when constructing the ARV signal.
3. Extract the variance of the signal with respect to the noise with the formula

4. Using a threshold h, determine when the signal g lies below and above the threshold. Portions of time
above the threshold are periods of muscle activity.
5. Discard any transitions across the threshold if they are shorter in duration than a user-specified time, t.
There are two methods of specifying the threshold h. An adaptive method examines the signal g and chooses the
threshold to be the median of g over the entire waveform. Alternatively, the threshold can be specified manually.
Using a manual threshold can be useful in adjusting the detection to better match specific EMG data. A suggested
threshold is 2.5. By lowering the threshold, a larger quantity of data will be considered as muscle activity. By
raising the threshold, a larger quantity of data will be considered to be noise.
The transition discard time t is specified in seconds. The default value of t is 0.1 seconds. If muscle activity is
being inaccurately identified as inactivity for short periods within active times, try increasing the value of t. Do
not set t to be greater than the smaller of either the shortest duration of a single muscle contraction or the shortest
rest interval between consecutive muscle contractions.
There are two outputs from the Locate Muscle Activation script.
· A new waveform, Muscle Active, will be added to the graph. The value of this wave will be zero when
the muscle is at rest and one when the muscle is active. This wave can be used to quickly visually
examine the record for periods of activity.
· Events are also generated on the raw EMG waveform. A Waveform Onset event is placed at each
transition from inactive to active, and a corresponding Waveform End event is placed at each active-toinactive transition. These events can be used in conjunction with the Cycle Detector to perform further
data reduction based on muscle activity.
The detection of muscle activation onset and end from surface electrode EMG is an imprecise process. The output
of this location should be visually examined for misidentification of
activation periods that are too short, too long, overlapping, or missed.
Preferences…
The Preferences allow the type of output to be chosen for displaying
results: text, graph channels, or Excel.

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Ensemble Average

Ensemble Average assists in performing offline averaging. Offline averaging produces an average waveform from
a number of cycles, also known as an ensemble average. Averages of multiple channels can be extracted
simultaneously and be consolidated into a single graph window showing the results. Offline averaging is also
available as a function within the Find Cycle feature.
This option provides two methods for locating individual members of the ensemble.
Ü Peaks: Data-driven peak detection with positive or negative peaks in the data. This method automatically
derives appropriate threshold levels from a user-selected peak and is useful for constructing averages keyed
to periodic signals with strong spikes, such as ECG.
Ü Events: Place members of the ensemble surrounding events in the waveform. Events must be previously
defined by the user, either manually or through another automated process. This method is useful for
constructing averages keyed to any types of events in a graph.

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Epoch Analysis

Extracts basic measures from fixed-width time segments of data. A fixed-width time segment of data is known as
an epoch. The location of these fixed-width intervals can either be keyed off of locations of events in the graph or
tied to regular time intervals (e.g. occurring at a constant frequency). All of the standard AcqKnowledge
measurements can be extracted on an epoch-by-epoch basis with the exception of Calculate.
Epoch-by-epoch measurement results can be viewed either as channels of
data in the graph, a textual summary, or on an Excel spreadsheet; textual
summaries include a final row with an overall average of each extracted
measurement.
Times output by Epoch Analysis are always expressed in seconds; all other
units correspond to the current preferred measurement unit settings
accessible under Display > Preferences.

NOTE: The Expression measurement function MMT() is available in Epoch Analysis, but the results may not be
reliable.

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Focus Areas between Events and Segments
In addition to the standard focus area functionalities discussed on page 92, focus areas can also be used as an analysis
tool to define areas of interest between certain event types or between appended segments.
Define Between Events
The parameters for defining focus areas using this method are highly customizable, and can be based upon specific
event types or titles as well as various event locations in the graph. The following table explains the various focus area
start and end event options.
Focus area label basename:
Use to assign a title for the focus areas. Successive focus areas will use
the same title with the addition of incrementing numbers.
Event type:
Use to select the type of event for defining the focus area.
Location:
· Anywhere—all channel and global events are included in the
event matching criteria.
· Global—when selected; only global events are included.
· Channel—when selected; only events in an individual channel
are included. Select the desired channel from the combo box
menu.
Event labels must match:
When checked, only events with labels matching the edit field text will
be defined. When unchecked, all events of the selected type are
matched, regardless of label.
Define for Appended Segments
This method simply defines the time range between appended segments as focus areas. No configurable options exist
for this feature within the Analysis menu.
Hemodynamic Analysis
Hemodynamics is the study of blood and circulation related data. This analysis package concerns itself with
interpretation of ECG, blood pressure, and monophasic action potential data; ECG signals must be sampled at 5
kHz or below to be analyzed with this package.
IMPORTANT: These routines are designed specifically for human subjects and may not function well, or at all,
on animal subjects, particularly small animals.
The Hemodynamic analysis package consists of:
a) ABP Classifier
b) Arterial Blood Pressure
c) Baroreflex Sequence Analysis (licensed feature, see page 533)
d) Baroreflex Slope Analysis (licensed feature, see page 533)
e) ECG Interval Extraction
f) Estimate Cardiac Output from ABP
g) Left Ventricular Blood Pressure
h) LVP Classifier
i) MAP Classifier
j) Monophasic Action Potential
k) Preferences
The time units reported by all of these transformations are in seconds unless otherwise noted.
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ABP Classifier

Places systolic and diastolic events at appropriate locations on a continuous arterial blood pressure signal
recording using either invasive means or a continuous noninvasive pressure monitoring system. The ABP
classifier functions directly on the pressure data and may fail for signals that exhibit strong noise characteristics or
large baseline drifts. Pre-filtering the signal may improve classification accuracy.
Arterial Blood Pressure

Extracts various cycle-by-cycle measures from arterial blood pressure (ABP) and ECG signals. It can function on
an individual ABP signal or, when used in conjunction with an ECG Lead II signal, extract additional Q relative
measurements.
§ If the ECG and ABP signals have not been classified when this analysis is performed, events for diastolic,
systolic, and ECG boundaries will be inserted as necessary.
§ If systolic, diastolic, and Q events are already present on the signals, however, they will be used.
§ Enable the “Apply low pass filter to pressure signal” checkbox to reduce noise from the ABP signal.
§ Enable the “Also run estimated cardiac output analysis” to cascade cardiac output measures to the ABP result.
On a cycle-by-cycle basis, the arterial blood pressure analysis transformation extracts the following measures:
Name

Abbrev.

Description

Diastolic

-

Minimum pressure occurring during the cycle

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Ejection time

ET

Time interval between the diastolic pressure and the minimum of dP/dt

Heart rate

HR

Heart rate in BPM as extracted from the diastolic-to-diastolic time interval for a
given cycle

Maximum dP/dt

dP/dt max

Maximum amount of the change in the pressure during the cycle

Mean blood
pressure

MBP

Mean blood pressure:

Pdiastolic +

Psystolic - Pdiastolic
3

Minimum dP/dt

dP/dt min

Minimum amount of change in the pressure during the cycle

QA Interval

QA

Time interval between ECG Q wave and the diastolic pressure

Pulse Height

PH

Pulse height (a.k.a pulse pressure): Difference between max and min pressures
within an individual cycle: P systolic − P diastolic

Recovery
interval

%REC

Time required for the pressure signal to decrease by a user specified percentage of
the pulse height

Systolic

-

Maximum pressure occurring during the cycle

Time to peak
pressure

TTPK

Time interval between the diastolic and the systolic pressures

When textual output is used, the average of all of these measures will be output as the last row of the table.
ECG Interval Extraction

Extracts cycle-by-cycle time and voltage measurements for various points and intervals between waveforms in the
cycle on ECG Lead II signals. This interval extraction is based off of the waveform boundary locations with
additional logic for defining explicit Q and S wave events. QRS peak events as output for boundary location are
used as the R peak location.
§ If the ECG signal was not classified before running the interval extraction analysis, it will be classified
automatically.
This analysis extracts the following cycle-by-cycle measures:
Name

Abbrev.

Description

Corrected QT
interval

QTC

QT time interval divided by the square root of the RR interval

Heart rate

HR

RR time interval expressed in BPM

P height

P-H

Amplitude at the peak of the P wave in a cycle

PRQ interval

PRQ

Time between the onset of the P wave to the Q wave

QRS width

QRS

Time between onset of the QRS complex and the end of the QRS complex. Equivalent
to the time between onset of Q and end of S

QT interval

QT

Time between the beginning of the Q wave and the end of the T wave

R height

R-H

Amplitude of the R wave in a cycle

RR interval

RR-I

Time between consecutive R peaks in the waveform

ST interval

ST

Time between the S wave to the end of the T wave

At the end of the text table output, the average of all of the cycles will be displayed. Additionally, both text and
Excel output will indicate the number of cycles that did not have all three of the QRS, P, and T waves defined.
These are cycles where the classifier missed a boundary and are listed as “Bad cycles,” which may happen due to
noise or other artifacts in the signal.
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Estimate Cardiac Output from ABP
This analysis algorithm, based on the universally recognized Liljestrand non-linear compliance formula, derives an
estimate of cardiac output (CO) from an existing arterial blood pressure (ABP) signal. Using this method, it is
possible to obtain an accurate measure of this data in a noninvasive fashion. For optimal results, the analysis must first
be calibrated through the Estimate Cardiac Output from ABP setup dialog in which an initial resting cardiac output is
selected. Adding smoothing or a low pass filter to the signal may further improve results.
1. Select the desired Hemodynamics > Preferences settings. (See page 400 for details.)
2. Hemodynamics > Estimate Cardiac Output from ABP.
3. Select the channel containing the blood pressure signal.
4. Choose an estimated calibration cardiac output level based upon typical male, female, or custom parameters.
5. Select the entire graph or desired focus areas for analysis and click OK.
6. Follow the “Highlight a systole in the BP data” prompt and click OK.
7. Click “Systole Is Selected” to begin the analysis.

If no systolic/diastolic events exist in the selected BP channel, they’ll automatically be scored and added using the
ABP classifier analysis script. Cardiac output results are presented in graph, text or spreadsheet format, depending on
the desired extraction method set up in the Hemodynamics preferences.
Enable the “Also run arterial BP analysis” checkbox to cascade ABP measures to the cardiac output result.
For text and spreadsheet output, the following measures are extracted.
Name

Abbrev.

Units

Description

Start Time

--

Heart Rate

HR

BPM

Heart rate as extracted from blood pressure signal in BPM.

Estimated Cardiac
Output

CO

L/m

Estimated cardiac output as computed using the estimated calibration
constant and Liljestrand formula.

Estimated Stroke
Volume

SV

L

CO/HR

The time at the beginning of each cycle.

For graph channel output, the following channels are added to the graph:
Channel Label

Units

Description

Heart Rate - ch

bpm

Heart rate as extracted from blood pressure signal in BPM (e.g., time duration of the
cycle in seconds / 60).

Estimated CO - ch

L/m

Estimated cardiac output as computed using the estimated calibration constant and
Liljestrand formula.

Estimated SV - ch

L

Estimated stroke volume. Equal to: CO / HR.

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If focus areas only are being analyzed, a new set of three channels will be defined for each focus area.
Watch the AcqKnowledge Cardiac Output from ABP video tutorial for a detailed demonstration of
this feature.
Left Ventricular Blood Pressure

Extracts various cycle-by-cycle cardiac measures of left ventricular blood pressure data, optionally in conjunction
with an ECG Lead II signal. Examines the LVP signal, ECG, and derivative of the LVP signal.
§ If the LVP and ECG signals have not been classified before this analysis is executed, they will be classified
automatically.
§ Derivatives of the LVP signal can be pre-existing or can be constructed automatically.
§ If an ECG signal is not included, only pressure related measures will be extracted.
The analysis outputs the following information on a cycle-by-cycle basis and the textual output cites the average
of all of these cycle-by-cycle measurements:
Name

Abbrev.

Description

Contractility
index

CI

maximum value of dP/dt during the cycle divided by the pressure at that time
location

Developed
pressure

DP

Amplitude interval between end diastolic pressure and systolic pressure

dP/dt Max

-

Maximum change in pressure over the cycle

dP/dt Min

-

Minimum change in pressure over the cycle

End diastolic
pressure

LVEDP

End diastolic pressure for the cycle. This is not necessarily the minimum pressure
during the entire cycle.
LVEDP is located on the LVP signal using the method set in the preferences.

Minimum
pressure

MIN

Absolute minimum pressure occurring during the entire cycle. This is not
necessarily equivalent to the end diastolic pressure

QA Interval

QA

Time interval between the Q wave of the ECG and the end diastolic pressure

Rate

-

heart rate in BPM as extracted from the time interval between consecutive end
diastolic pressure locations

Recovery time

%REC

Time it takes for dP/dt to increase from the minimum dP/dt location to a user
specified percentage of that minimum value

Systolic pressure

SYS

Maximum pressure occurring during the entire cycle

Tau

-

Monoexponential time relaxation constant tau computed on a cycle by cycle basis.
See “Computation of Tau” on page 398 for specifics.
X

Tension time
index

TTI

X

Integral of the pressure between end diastolic and the time of minimum dP/dt

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Computation of Tau
There are many different methodologies used to extract the time constant from LVP data. The time constant is
extracted from a best fit parameter of a model to the trailing edge of LVP data on a cycle by cycle basis. This
analysis uses a monoexponential model of zero asymptote for computing tau.
The relaxation period is defined as the range of data between the time of minimum dP/dt in the cycle to the point
where the LVP pressure signal drops below the previous LVEDP level. Within this range, the following model is
fitted to the data using the simplex search method:
t

P0 e

t

where P 0 is the value of the LVP signal at the time of dP/dt minimum and t is the time coordinate shifted such
that t is 0 at the time of dP/dt minimum. The best fit value from this model is used as the value of the relaxation
time constant.
LVP Classifier
Operates on left ventricular blood pressure (LVP) data to define events at the systolic pressure and the left
ventricular end diastolic pressure for each cycle.

The location of these points is performed using filtered derivatives of the original LVP signal. Pre-filtering the
signal (low pass of 50 Hz or less) or smoothing the signal before running the classifier may improve accuracy.
The LVP classifier locates LVEDP (left-ventricular end diastolic pressure) by examining the derivative of the
pressure signal based upon the location method specified in Preferences:
§ Adaptive threshold of 0 plus a percentage of the peak to peak change in pressure. The percentage is userspecified; the default is 1%. If the LVP signals do not have “flat” valleys, this percentage may need to be
increased to fine-tune positioning of LVEDP.
§ First zero crossings before contraction.
Watch the AcqKnowledge LVP classifier video tutorial for a detailed demonstration of this feature.

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Monophasic Action Potential

Performs classification of MAP data acquired from a human or animal subject and extracts various cycle by cycle
intervals. Locates upstroke, maximum, 100% recovery, and user-specified recovery points on the action potential.
§ Classification is performed using the action potential with its smoothed derivative; pre-filtering noise with
low pass filters may improve classification.
§ If upstroke, maximum, and plateau events are already defined on the MAP signal, the classifier is not invoked
and only recovery events are defined.
Plateau position
To better handle animal subjects and different potential morphologies, there are two methods for locating the
plateau position in monophasic action potential data; use Preferences to set the method. Each method defines
recovery percentage time locations depending on the signal between its maximum and the beginning of the
plateau. The plateau is located by examining the derivative of the MAP immediately following its maximum
value after an upstroke.
§ The first method uses an adaptive threshold of zero plus a percentage of the peak to peak change in the
derivative between the maximum and the first zero crossing after the maximum. If the signal remains above
the upstroke voltage in this interval, a quick algorithm is used to locate 100% recovery and user-specified
percentage levels.
§ The default percentage is 0.1%, which will place the plateau position very close to the second zero crossing.
This slight window around zero helps place plateau start events better for MAP data that has plateaus that
continue increasing after their starting position.
§ Searches for the second zero crossing after the maximum. If the signal drops below the voltage level of the
upstroke in this interval, a different (slower) algorithm is used to ensure the recovery percentage is relative to
the upstroke voltage and not the minimum occurring between the maximum and plateau.
The analysis outputs the following information on a cycle-by-cycle basis and the textual output cites the average
of all of the cycle-by-cycle values:
Name
100% recovery
period
dV/dt maximum
dV/dt minimum
End diastolic
voltage
Max voltage
Minimum
voltage
Plateau voltage

Abbrev
100%
REC
dV Max
dV Min
EDV

Description
Time interval from the upstroke for the signal to recover back to the upstroke voltage
level
Maximum change in voltage over the cycle
Minimum change in voltage over the cycle
The value of the signal at the beginning of the upstroke

MAX
MIN

The maximum value of the signal over a single cycle
The minimum value of the signal over a single cycle. This may be less than the
upstroke voltage depending on the morphology of the action potential
The value of the signal at the start of the plateau after the completion of the upstroke

Rate

-

Stroke amplitude

AMP

User recovery
period

%REC

PLAT

This is the heart rate in BPM as extracted from the time interval between consecutive
upstrokes
Voltage interval between the plateau and the upstroke voltage
Time interval from the upstroke for the signal to recover a specific percentage of the
interval between the upstroke and the maximum voltage between the upstroke and the
plateau
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Watch the AcqKnowledge Monophasic Action Potential video tutorial for a detailed demonstration of this
feature.
MAP Classifier
The classifier portion of Monophasic Action Potential only – defines upstroke, plateau, and percentage recovery
events on MAP signals without performing the additional MAP data extraction.

The start of the plateau is located using either the second zero crossing of the derivative or a percentage of the
cyclic peak-to-peak distance of the derivative. The plateau location method can be configured in Preferences.
Preferences

Display results as
Several of these transformations produce large amounts of cycle-by-cycle derived measures. Results can be
displayed as a tab delimited table in the journal, as waveforms in the graph, as an Excel spreadsheet or various
combinations. Results are displayed as text-only by default.
LVEDP location method – see page 398
§ adaptive threshold of 0 plus a % of pk-pk change in pressure
§ first zero crossings before contraction on the dP/dt signal
MAP Plateau location method – see page 399
§ adaptive threshold of 0 plus a % of pk-pk change in the derivative between the max and the first 0
crossing after the max
§ second zero crossing after the maximum
X

X

X

X

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ABP Location method (Arterial Blood Pressure)
§ Adaptive template matching
This arterial blood pressure cycle location method uses adaptive template matching (see page 314). A
single cycle is selected, systolic to systolic, which sets an example template. Subsequent blood pressure
cycles are located by correlation to this template with the template adapting to the signal. This may
function better if there is artifact in the pressure signal, however may not be as suitable for signals that
have significant changes in heart rate. Location may also improve if a different cycle is chosen as the
initial template. Adding smoothing or a low pass filter to the signal may improve results for Estimated
Cardiac Output, ABP Classifier and Arterial Blood Pressure.
§ Tracking peak pressure level
The Tracking peak pressure level ABP location method is similar to the cycle detector's peak location
method. This method sets a detection threshold from a selected systole and adjusts the threshold based on
a customizable tracking percentage. The default tracking percentage is 60%. If the blood pressure signal
is highly variable, this tracking percentage may need to be lowered. If the tracking percentage is set too
high, blood pressure cycles may be missed.
HRV and RSA Analysis
AcqKnowledge includes flexible options for extracting a wide range of heart rate variability (HRV) and respiratory
sinus arrhythmia (RSA) measures. This analysis feature will:
·

Extract HRV measures over user-defined areas of data, such as fixed time trials (“epochs,”) events and
focus areas.

·

Obtain RSA measures using frequency-based HRV.

·

Automatically compute HRV using geometrical and statistical methods.

Multi-epoch HRV – Statistical

This analysis computes statistical measures of heart rate variability in user-specified time intervals. These
measures (RMSSD, SDSD, and pNN50) can be extracted by fixed time intervals, time between event boundaries
or focus areas. Output from the script is a spreadsheet containing these statistics and the time intervals over which
they are computed. ECG complex events are also scored in the source graph. See Application Note 129 for a
detailed explanation of HRV statistical analysis measures.
The following table describes options in the Multi-epoch HRV Statistical Analysis setup:
Control

Description

ECG Channel:

Selects the channel to extract the statistics from. The ECG channel should be selected.

Extract HRV
statistics for:

Select how the time ranges used for extracting statistics are applied. The options are Fixed
time trials, Time between event boundaries and Focus areas.

Epoch width:

Indicates time duration and time units for each epoch.

Start first epoch
at:

Chooses location for starting first epoch. (Beginning of graph, current cursor location or a
specific time point in the graph.)
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Multi-epoch HRV and RSA – Spectral

This routine performs RSA and HRV analyses on specified time slices along an ECG waveform, whether by markers,
fixed time intervals or focus areas. Then the HRV parameters of VLF, LF, are teased out of the journal, formed into a
table, and written back into the journal or to an Excel spreadsheet. The following table describes the HRV and RSA
Spectral Analysis options:
Control

Description

HRV Preset

Selects the heart rate variability preset to be used in the analysis. (This must first be predefined in the main HRV analysis dialog for conveying PSD, frequency bands, etc.) For more
information, see Single-epoch HRV – Spectral.)

ECG Channel:

Selects the channel to extract the statistics from. The ECG Lead II channel should be
selected here.

Extract HRV and
RSA by:

Selects how the segments to be analyzed should be located. Available options are by:
·

·

Periodic time intervals – this option segments the data into fixed width epochs that
occur at regular frequency intervals. It is equivalent to the “fixed time interval” option
of epoch analysis.
Fixed-width intervals around events – “Fixed width intervals around events” is akin to
the “at events” option of Epoch Analysis. It searches for individual events and
analyzes a fixed interval of time with that event either as the beginning point or the
endpoint of the time window.

·

Time between event boundaries – allows the segments to be located between two
different individual events. The boundaries should ideally be two different types of
events. If set to the same type a prompt will appear, asking whether the ending
event of a pair should be immediately reused as the start of the next time interval.
· Focus areas – this method extracts the HRV for each focus area defined within the
graph.
See page 402 for specific setup descriptions for the above options.
Output type:

Select the analysis output format – Text, Excel, or both.

Output events at
analysis
boundaries:

Defines new markers at the time boundaries of each analyzed data segment. This is useful
when performing validation of the analysis.

If Periodic time intervals are chosen, the following setup criteria are available:
· Epoch width: – sets the duration and time units for each epoch
·

Start first epoch at: – choose location for starting first epoch. (Beginning of graph, current cursor location
or a specific time point in the graph.)

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· Time between epochs: – indicates the time separating one epoch to the start of to the next.
If Fixed width intervals around events is chosen, the following setup criteria are available:
· Event type: – choose the specific type of event to be used in the analysis.
· Before events: – when selected, the event marks the end of the analysis time interval.
· After events: – when selected, the event marks the beginning of the analysis time interval.
· Epoch width: – sets the duration and time units for each epoch.
If Time between event boundaries is chosen, the following setup criteria are available:
· Start event: – select the starting event type at the beginning of each time segment.
· End event: – select the ending event type at the end of each time segment.
R-R Poincaré Plot

Poincaré plots are constructed from ECG Lead II data. A Poincaré plot is an XY plot with RR intervals in seconds
on one axis and on the other axis the sequence delayed by one beat (RR vs. RR+1). This plot may be used to
visually inspect for patterns in the sequence similar to an attractor plot. The RR intervals are measured in seconds.
This generates a new dot plot graph window in XY mode, no textual output is generated. Click the
button to
exchange the X and Y axis (flip the plot diagonally.) Use “Plot recent data only” to isolate a subset of the most
recent data points. Enter the desired number of data points to be displayed and check the “Plot” box. Or, with the
box checked, enter the desired value and hit the Enter (Return) key.
Applying the R-R Poincaré plot option also scores the ECG source graph with QRS events.
Beginning with AcqKnowledge 5.0.3, R-R Poincaré Plot analysis has been extended with SD1 and SD2 metrics.
SD1 and SD2 are two standard Poincaré plot descriptors. SD2 is defined as the standard deviation of the
projection of the Poincaré plot on the line of identity (y = x), and SD1 is the standard deviation of projection of
the PP on the line perpendicular to the line of identity (y = − x)
This places SD1 and SD2 and their ratio into the output graph Journal and creates a data view with the values of
x1 and x2.
To further reading about Poincaré, see Filtering Poincaré Plots by Jaroslaw Piskorski and Przemyslaw Guzik.

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Respiratory Sinus Arrhythmia (RSA Time-series)

IMPORTANT—Respiration analysis assumes a bidirectional airflow signal that records both
inhale and exhale. Unidirectional respiration signals cannot be analyzed at this time.
Respiratory Sinus Arrhythmia is used to explore the connection between respiration and changes to heart rate.
Variations in the heart rate can be directly correlated with vagal tone. The RSA index can be used to investigate
changes in this connection during recording.
This RSA index is computed using the peak-valley method as outlined in:
Grossman, P., van Beek, J., & Wientjes, C. (1990). A comparison of three quantification methods for
estimation of respiratory sinus arrhythmia. Psychophysiology, 27, 702-714.
This method uses both a recorded ECG Lead II signal and a respiration signal. By using respiration information,
this analysis method can provide breath-to-breath analysis that does not require parameter tweaking for individual
subjects.
While designed for use with the RSP100C/TSD201 respiration module and transducer combination, it should be
possible to use other estimates of respiration. The respiration signal is used to locate periods of inhalation and
exhalation. Inhalation begins at valleys in the signal while expiration at peaks. Any respiration estimate that
exhibits this morphology should be sufficient.
The RSA index outputted by this analysis is linearly scaled as per the recommendations in Grossman et. al. For
comparison to other methods or studies using logarithmic scaling, Transform > Math Functions > Ln
transformation can be used after analysis to convert results to logarithmic scaling.
In AcqKnowledge versions 4.4.1 and higher, selecting the “Generate logarithmic RSA” checkbox will
automatically output the logarithmic result.
RSA results are triggered from the respiration cycle. The RSA analysis outputs the following measures:
Cycle
Index of the respiration cycle in the analysis.
Time
Location of the start of the respiration cycle on the time axis.
Min Rate
Minimum heart rate occurring during the inspiration window of the respiration cycle, expressed
in milliseconds (IBI).
· If a respiration cycle is invalid, this measure will be set to 0.
Max rate
Maximum heart rate occurring during the expiration window of the respiration cycle, expressed
in milliseconds (IBI).
· If a respiration cycle is invalid, this measure will be set to 0.
RSA
RSA index for the respiratory cycle, expressed in milliseconds. This is the max rate minus the
min rate. This is output in linear scaling.
If a respiration cycle is invalid, this measure will be set to 0.

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Single-epoch HRV – Spectral
Single-epoch HRV – Spectral (formerly referred to as Heart Rate Variability in AcqKnowledge versions 4.3.1 and
earlier), is the examination of physiological rhythms that exist in the beat-to-beat interval of a cardiac signal. Singleepoch HRV assists in performing frequency domain analysis of human ECG Lead II data to extract standard HRV
measures. The HRV algorithm in AcqKnowledge 3.9 and above conforms to the frequency domain algorithm
guidelines as published by the European Heart Journal (1996) 17, 354-381.

Single-epoch HRV processing in AcqKnowledge consists of three stages:
1. The RR intervals are extracted for the ECG signal.
§ A modified Pan-Tompkins QRS detector is used.
2. The RR intervals are re-sampled to a continuous sampling rate in order to extract frequency information.
§ Cubic-spline interpolation is used to generate this continuous time-domain representation of the RR
intervals.
3. The frequency information is extracted from the RR intervals and analyzed to produce standard ratios. Power
sums are reported in units of sec2.
§ A Welch periodogram is used to generate the Power Spectral Density (equivalent to Transform > Power
Spectral Density).
The initial implementation of the HRV algorithm was primarily for use with long duration recordings. HRV algorithm
improvements allow for further customizations to the algorithm:
§ Windowing type for FFTs used to construct the PSD may be changed between Hamming, Hanning, and
Blackman.
§ Overall window length for segmenting source data for individual FFTs to include in PSD average may be
modified .
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§
§
§
§
§
§
§

Length of the individual FFTs in the average can be manually specified.
Scaling has been changed for PSDs, which are now scaled relative to the sampling frequency.
Summary of power in individual frequency bands has been changed .
Instead of a straight sum, an average power value is now reported .
Power at endpoints is halved (e.g. divided by 2).
Sympathetic/Vagal ratios may optionally include the very low frequency band in the total power estimate
The modifications to the HRV algorithms that affect its power spectrum estimation have also been applied to
the PSD transformation.
After selecting Analysis > HRV and RSA > Single-epoch HRV – Spectral, choose the appropriate tab(s) and establish
settings.
Preset controls, Transform entire wave checkbox, and OK/Cancel buttons apply across all of the tabs.
Preset—The preset menu can be used to save a variety of HRV settings, including: beat detection parameters, spline
resampling frequency, and frequency band ranges. Choose a preset from the popup menu to apply its settings. To
construct a new preset with the currently displayed settings, choose Add New Preset. A default preset for adult human
subjects is supplied.
RR intervals
Select a method to locate R waves: QRS Detector or Events.
QRS detector

The heart rate variability implementation has a built-in QRS detector. The detector does not run on raw source
data; it uses a modified Pan-Tompkins algorithm to normalize the ECG data to 1, whereby the peak amplitude of
the highest R-wave represents 1. Use the tachogram output to examine the output of the QRS detector.
§ R wave threshold—The detection threshold must be specified in terms of percentage of maximum R peak
level; this helps to clarify the units in which this threshold is expressed. The default threshold level of .5
should place the threshold in the middle of the R-wave, which should function on a wide range of data sets. If
the R-wave amplitude varies a lot, it might be necessary to adjust the threshold level.
o R wave threshold is expressed in normalized units, which are in the range (-1, 1): positive for
positive R wave peaks. The maximum voltage in the signal maps to 1.0 and the minimum voltage
in the signal maps to -1.0.
Pan J and Tompkins WJ. A Real-Time QRS Detection Algorithm. IEEE Transactions on
Biomedical Engineering 32(3):230-236, 1985.
Events

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R-wave peaks will be located using events already in the graph of the channel of data to be analyzed. This
assumes a single event is placed at each R-wave peak and that all of the R-peak events are of the same event type.
When using events, the built-in QRS detector is not used; the exact positioning between the events on the channel
is used to extract the RR intervals.
By using events, it is possible to use other QRS detectors within AcqKnowledge for performing HRV analysis. It
is also possible to apply spectral HRV-style analysis to data in other domains as long as intervals can be reduced
to events.
Spline resampling frequency
For highest accuracy, set to no less than twice the topmost frequency of the very high frequency band.
Frequency Bands

Enter the start and end of each specified frequency band to adjust the boundaries of the frequency analysis. They
are preset to the frequency ranges recommended by the European Heart Journal (1996) 17, 354-381. Output of
derived parameters is presented in a dialog and may also be pasted as text to the Journal.
§

Very high frequency band, usually used in rat studies, is disabled if the spline resampling frequency is less
than the upper bound of the very high frequency range.

PSD Options

PSD Options establish parameters for the power spectral density transformation used to compute the spectrum
from the interpolated tachogram; the options contained in this tab mirror the controls of the Analysis > Power
Spectral Density transformation detailed on page 331.
The use of linear detrending in each individual segment of source data prior to the windowed periodogram
analysis can be enabled or disabled. When disabled, the algorithm may be tuned to correspond to
implementations that do not apply linear trending, such as MATLAB, which uses windowing only. The same
PSD options are available via Analysis > Power Spectral Density so users can regenerate the spectrum from
either the raw or interpolated tachogram output as necessary.
After the user modifies the parameters for the PSD transformation, those parameters will become the new
default values each time the dialog is displayed. When the application is relaunched, the default settings will
be used (user changes are not persistent).

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Improvements to PSD Options (AcqKnowledge 4.3 and higher)
l
l

The PSD output is now scaled so power values are scaled by the sampling rate. That is: PSDnew =

PSD old
fs

Reporting a sum for a frequency range when computing the power in an individual band has been changed.
Given a frequency range f low , f high define the set S of all samples of the PSD where
S = PSD ( f low ),¼ , PSD f high . Define the sum of the power within the frequency range as:

{

(

)}

S |S | ö ( f high - f low )
æ S i=|S |-1
÷´
. This applies the scaling factor to a sum of the
s ( f low , f high )= çç 1 + å S i +
2 ÷ø
|S | - 1
i= 2
è2

l

frequencies in the frequency range, with the magnitudes at the endpoints divided by 2. Previous versions
would perform a direct sum of all amplitudes within the frequency band.
Result reporting has been changed for the overall ratios. The VLF section is now included in the ratios. A
new VLF ratio has been introduced. Define s vlf = s vlf low , vlf high , s lf = s lf low ,lf high , and

(

s hf = s (hf low , hf high ) . The new VLF ratio is: ratiovlf =
defined as: ratiolf =

s lf
s vlf + s lf + s hf

)

s vlf
s vlf + s lf + s hf

old

=

s hf
s lf + s hf

old

=

)

. The new sympathetic ratio is

. The new vagal ratio is defined as: ratio hf =

previous algorithm defines the sympathetic ratio as: ratiolf
the vagal ratio as: ratio hf

(

s lf
s lf + s hf

.

Visit the online support center at www.biopac.com

s hf
s vlf + s lf + s hf

. The

. The previous algorithm defines

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409

Output

Create standard result presentation graphs or assess
performance of the HRV algorithm. Output options
allow access to intermediate computation data for
algorithm validation and/or measurements.
RR Interval table

·

If the combined output formula is selected, the analysis output will contain an additional line of text: “VLF
Ratio” with the corresponding percentage.

Spectrum

Displays the power spectrum density (PSD) estimation from which the PSD summations and
sympathetic/vagal ratios are computed.
Raw tachogram

Plots the raw R-R intervals found by the QRS detector. Perform statistical HRV measures on the R-R
intervals without exporting the textual R-R table to excel.
Interpolated tachogram

Plots the resampled R-R intervals after cubic spline interpolation is applied and extracts the PSD from
this data.
IMPORTANT—Recording good data is essential for performing HRV analysis. The protocol for data acquisition,
filtering, artifact detection and correction in Application Note 233 results in great improvements in HRV analysis.
“Results reveal that even a single heart period artifact, occurring within a 2-min recording epoch, can lead to
errors of estimate heart period variability that are considerably larger than typical effect sizes in
psychophysiological studies.” —Berntson & Stowell, 199
· See Application Note 233 Heart Rate Variability—Preparing Data for Analysis Using AcqKnowledge
(online at www.biopac.com)
H

H

Watch the AcqKnowledge HRV Analysis video tutorial for a detailed demonstration of this
feature.
The note explains how to optimize ECG R-R interval data for Heart Rate Variability studies by using a template
matching approach. It also explains how to identify erroneous R-R interval values caused by signal artifact and shows
methods for correcting the errors by using the tools in the AcqKnowledge software. The note explains how to:
A. Record good ECG data
B. Prepare data for the tachogram
1. Filter the ECG data
2. Transform the data using Template Correlation function
C. Create a tachogram
D. Identify problems with the tachogram data
E. Correct tachogram data

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Impedance Cardiography Analysis
The Impedance Cardiography analysis package assists in the analysis of cardiac output and other hemodynamic
parameters using noninvasive bioimpedance monitoring techniques; signals must be sampled at 5 kHz or below to
be analyzed with this package. This analysis offers a variety of approaches for estimation of cardiac measures.

Body Surface Area
Determines the body surface area estimation in square meters for a subject of a given height and weight, using the
formula set in Preferences. It can be used to calculate body surface area independent of any of the other analysis
routines, which may be useful for validation purposes or other derived calculations.
Body Surface Area equation
Use the Preferences option to select an algorithm for estimating body surface area of a subject and deriving stroke
volumes from impedance data.
Method

Formula

Boyd

BSA = 0.0003207´ Height(cm) 0.3 ´Weight(g)0.7285-0.0188 log(Weight(g ))

DuBois and DuBois

BSA = 0.20247´ Height(m) 0.725 ´ Weight(kg) 0.425

Gehan and George

BSA = 0.0235 ´ Height(cm) 0.42246 ´ Weight(kg) 0.51456

Haycock

BSA = 0.024265´ Height(cm) 0.3964 ´Weight(kg) 0.5378

Mosteller

BSA =

Height (cm ) ´ Weight (kg )
3600

dZ/dt Derive from Raw Z
This is a convenience utility for working with impedances recorded using the BIOPAC EBI100C amplifier or the
raw impedance output of the BIOPAC NICO100C module. When computing derivatives from raw impedance
signals from an EBI100C, this will apply appropriate filtering for a thoracic impedance signal and properly invert
the derivative to match traditional dZ/dt presentation.
dZ/dt Classifier
Places events at common inflection points on a dZ/dt waveform to derive other measures.

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The classifier will attempt to locate the following points on the ICG signal:
§ B point – opening of aortic valve (set location in Preferences)
§ C point – Maximum left ventricle flow (set location in Preferences)
§ X point – Closing of aortic valve (set location in Preferences)
§ Y point – Closing of pulmonal valve
§ O point – Widest opening of mitrial valve
The algorithm for locating these points on the ICG signal examines local minima and maxima in the dZ/dt signal
as well as values of its second derivative. Filtering is applied to the second derivative signal to improve accuracy.
§ Pre-filtering the dZ/dt signal may improve accuracy slightly.
In a particular cardiac cycle, if there is not enough definitive change in the ICG signal to locate a particular point,
the point will be omitted. This may most commonly occur with the Y point since its inflection between X and O is
subtle and may be lost.
The location routine, as with impedance cardiography measurements in general, is sensitive to motion artifacts. It
is intended to function on signals acquired from subjects at or near perfect rest. Swings in the dZ/dt signal may
cause the classifier to fail. It is recommended that motion artifacts be removed before running the dZ/dt classifier
or any other ICG analysis tools that may invoke the classifier on an ICG signal. If artifacts are present within the
signal, the template matching cycle location method will exhibit better behavior than the fixed threshold method.
The choice between these two methods can be made with the Preferences option of the analysis package.
B-point Location—Use Preferences to set the dZ/dt B-point location method.
There is no standard method generally accepted for programmatically locating B-points on an ICG waveform.
The appropriate choice of B-point location method may depend on the data or on subjective preference. On
average, all five methods will produce similar results for clean data. ICG Preferences has five options for Bpoint location:
§ Second derivative classification – Given a C peak, it searches within a 150ms to 100ms time window
before the C peak for the maximum of the second derivative of impedance (
). The B point is placed

Z

§

at this maximum.
Third derivative classification – Given a C peak, it searches for the maximum value of the third derivative
of impedance (
) within 300ms before the C peak. The B point is placed at this maximum.

Z

§

§
§

Cycle-by-cycle ‘Isoelectric’ crossings – Given a cycle defined by two C peaks, the mean of the dZ/dt
signal is computed over the cycle. The B point is then placed at the closest time to the right C peak that is
still underneath this baseline zero level.
R to C polynomial model - Location of B point based on locations of R and C points according to
polynomial equation found in Lozano et al. (2007). Psychophysiology, 44:113-119.
Min derivative in C-QRS interval – Start at C, move backwards in time 35 ms, start looking for minimum
of derivative of dZ/dt, stop at peak of QRS + 25 ms. Minimum dZ/dt derivative in window (35-(R+25))
ms is B.
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C-point Location—Use Preferences to set the dZ/dt C-point location method.
In several of the ICG analysis scripts, the B, C, X, Y, and O points will need to be located on the dZ/dt
waveform. The starting point of this process is locating individual cycles on the dZ/dt waveform to define the
C points. Use Preferences to set the cycle location method:
§ Template Matching – the user is expected to select a representative cycle of the dZ/dt waveform. The
entire cycle should be selected (e.g. visually to approximate a C-C interval, a X-X interval, etc.). The
entire dZ/dt signal is then correlated with that representative cycle, and individual cycles are picked out
from locations of maximum correlation.
§ Fixed Thresholding – the user is prompted to select one of the C peaks of the dZ/dt waveform. The
voltage level of this peak is then used to compute an Ohms/sec thresholding level. Peak detection is
then run on the dZ/dt waveform using that voltage level as the threshold.
Since ICG is subject to many artifacts such as respiration components and motion artifacts, the default
method used is template matching. For extremely clean ICG signals, however, fixed thresholding can
be used effectively as well and will provide a quicker analysis.
§ Adaptive template matching – the user is prompted to select a representative cycle of the dZ/dt
waveform. This is used as a basis for an adaptive match to locate cycles. Adaptive template matching
will adapt to changes in the dZ/dt waveform as conditions change within the experiment. Two
parameters may be set. The window size is the number of ICG cycles to use for estimating the next
template. Smaller values will track changes more quickly; larger values will reduce interference from
artifact. The correlation threshold is the value above which a match is found. It refers to the normalized
cross correlation of dZ/dt with the template and should be between 0 and 1. Values closer to 1 will
require precise matches and skip artifacts. Values closer to 0 will use looser match constraints and may
be required if the ICG is changing rapidly.
X-point Location
There are two methods that may be used to locate the X point of the ICG waveform at the closing of the aortic
valve. The choice of appropriate X point location method is dependent on the electrode configuration that is
used to acquire the ICG signals. In certain electrode configurations, the dZ/dt minimum may actually occur
closer to the A-wave complex than to X, making the first (and default) option of searching for the first turning
point a more reliable solution. It’s recommended to acquire a phonocardiogram in conjunction with ICG to
help determine which method will be more accurate at locating X.
§ Search for the first turning point in the dZ/dt signal that occurs after the C point location and place X at
the first positive zero crossing in the second derivative of impedance (d2Z/dt2).This is the default X point
location method.
§ Locate the X point at the minimum value of dZ/dt over each cardiac cycle.
§ Start at C, move forward in time 150 ms, start looking for minimum of dZ/dt, stop at 275 ms. Minimum
in window is X.

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ICG Analysis

The ICG Analysis routines include 20 derived impedance and hemodynamic measures that correspond to various
values that are generated by other industry-standard impedance cardiography analysis tools. Many users tend to be
interested only in a subset of the various measures produced by the analysis (e.g. only heart rate and cardiac output);
the extra measures can “clutter” the output and frustrate users who have to delete them manually.
The ICG Analysis output options feature adds a new step to the ICG Analysis where the user may toggle the output of
individual measures on and off. This allows users to suppress generation of all output for a measure including the
graph channels, column in the Excel spreadsheet, and column in the text output.
ICG Analysis performs a full impedance cardiography analysis on data, extracting intervals and derived cardiac
measures. The minimal set of signals required to run this analysis is an ECG Lead II signal and either a raw
impedance signal or a dZ/dt signal.
§

If a raw impedance signal is present from an EBI100C or NICO100C and no derivative has been constructed,
the analysis will automatically construct the appropriate derivative and perform classification.
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§

If both a raw impedance and a dZ/dt signal are present, the baseline impedance will be derived on a cycle-bycycle basis to improve the accuracy of the analysis.
§ If no raw impedance signal was acquired, a default fixed baseline impedance can be used.
§ If a NICO100C amplifier is used, it is recommended that both the raw impedance and dZ/dt signals be
acquired to improve analysis accuracy.
§ To automatically apply motion filtering to the dZ/dt signal, use Preferences to enable Motion Filtering (see
page 418).
§ ICG Preferences must first be selected in order to generate the main ICG Analysis setup window.
In addition to the minimal set of signals, it is also possible to use arterial blood pressure, central venous pressure,
and pulmonary arterial pressure signals to improve the quality of the algorithm results. If any of these signals are
not present, default fixed estimated values can be substituted for the mean pressures instead of deriving pressures
on a cycle-by-cycle basis.
ICG Analysis may potentially perform classification of both the dZ/dt and the ECG Lead II signals. The various
notes for understanding the limitations of these classifiers apply and should be understood to properly interpret
failures in the analysis.
ICG Analysis will produce the following information on a cycle-by-cycle basis:
At the end of the textual table an average of all of the cycle-by-cycle values will be appended.
X

X

Name
Acceleration index

Abbv.
ACI

Description

Units

Maximum blood acceleration

1 / sec^2

m^2 / min

Cardiac index

CI

Normalized cardiac output

Cardiac output

CO

Volume of blood pumped each
minute

l / min

Heart rate

HR

Heart rate in BPM as computed
from the RR interval.

BPM

Formula

d 2Z
dt 2 max
TFI
CO
BSA
SV ´ HR
60
RRi

kg m

(MAP - PAP) ´ CO ´ 0.0144

kg m / m^2

(MAP - PAP ) ´ CI ´ 0.0144

Left cardiac work

LCW Work exerted by the left ventricle
each minute

Left cardiac work index

LCWI Normalized left cardiac work

Left ventricular ejection
time

LVET Time interval between B and X.
Time interval between aortic valve
open and close.

sec

Mean blood pressure

MBP Mean blood pressure as measured
on the arterial blood pressure
signal, or fixed estimate if no ABP
signal is present.

mmHg

Pdiastolic +

Mean central venous
pressure

CVP Mean central venous pressure over
cycle, or default value if no CVP
signal is present.

mmHg

Not applicable

Mean pulmonary arterial
pressure

PAP Mean value of the pulmonary
arterial pressure of a cycle, or
default value if no PAP signal is
present.

mmHg

Not applicable

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Not applicable

Psystolic - Pdiastolic
3

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Name
Pre-ejection period

415
Abbv.

Description

PEP Time interval between the Q wave
of the ECG and the B point of the
ICG.

Units

Formula

sec

Not applicable

sec

Not applicable

Time interval between systole and
aortic valve open.
RR interval

RR-i Time interval between R peaks in
the waveform.

Stroke index

SI

Normalized stroke volume

Stroke volume

SV

Volume of blood pumped by left
ventricle in a single beat

(ml / beat)/ m^2

ml / beat

SV
BSA
Set equation in Preferences:

Kubicek—Estimates SV from the
derivative of the impedance signal
and blood resistivity:

SV = r ´

L2 dZ
´
´ LVET
Z 0 2 dt max

Note

may be either the absolute
maximum or the BC delta in
amplitude, as set in Preferences.
§ Sramek—Estimates SV from the
derivative of the impedance signal and
the estimated volume of electrically
participating fluid (VEPT):

SV =

VEPT dZ
´
´ LVET
Z0
dt max

o In the ICG analysis routines,
VEPT is estimated using a
truncated cone model.

(0.17H )
VEPT =

3

4.25

§ Sramek-Bernstein—Estimates SV
from the volume of electrically
participating tissue scaled according to
body habitus. The SV equation is:
d (VEPT ) dZ
SV =

Z0

´

dt

´ LVET

max

where

d (VEPT ) =

weight actual (0.17 H )3
´
weight ideal
4.25

Ideal body weight is computed using the
method set in the Preferences. To best
match the original Sramek-Bernstein
equation, use the Met Life Tables ideal
body weight method.
Systemic vascular
resistance

SVR Afterload; arterial flow resistance

dynes sec /
cm^5

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CO

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Name

Abbv.

Description

Units

Systemic vascular
resistance index

SVRI Normalized afterload

dynes sec m^2 /
cm^5

Systolic time ratio

STR Ratio between electrical and
mechanical systole

Thoracic fluid content

TFC Electrical conductivity of the chest
cavity

Thoracic fluid index

TFI

Mean value of the raw impedance
over the cycle, or fixed baseline
value if no raw impedance signal is
present.

Ohms

Velocity index

VI

Maximum velocity of blood flow
in the aorta.

1 / sec

none

1 / Ohms

Formula

80 ´

MAP - CVP
CI

PEP
LVET
1
TFI
Not applicable

dZ
dt max
TFI

Note

may be either
the absolute maximum
or the BC delta in
amplitude, as set in
Preferences.

Ideal Body Weight
Body Weight is derived from a person’s height, gender, and (for the Met Life method) frame size. It describes the
ideal weight based upon various estimates. Ideal body weight is subject to much interpretation, so a number of
methods are provided. Ideal Body Weight results are always expressed in kilograms.
Use Preferences to set the Ideal Body Weight computation method; the selected method is also used for ICG
Analysis.
Method

Formula
Men
50 kg + 2.3 kg per inch over 5 feet
Women 45.5 kg + 2.3 kg per inch over 5 feet
The weight is taken from the standard Metropolitan Life tables, which are based on gender,
height, and frame size. The Metropolitan Life tables specify weight ranges; the ideal body
weight is computed as the average of the endpoints of each weight range. Ideal weights are
based on height with shoes on and are only defined for heights between
Men
5' 2''and 6' 4''
Women 4' 10''and 6' 0''
Men
56.2 kg + 1.41 kg per inch over 5 feet
Women 53.1 kg + 1.36 kg per inch over 5 feet
Men
52 kg + 1.9 kg per inch over 5 feet
Women 49 kg + 1.7 kg per inch over 5 feet

Devine
Metropolitan Life
Tables

Miller
Robinson

PEP Pre-ejection Period
The pre-ejection period is the time interval between the electromechanical systole and the onset of ejection of
blood from the left ventricle of the heart. This can be derived from standard ECG data and ICG data as the
interval between the Q point on the ECG and the B point on the ICG. The Pre-ejection Period analysis tool helps
extract PEP measurements from ECG Lead II and ICG data. PEP can also be computed using the full ICG
Analysis tool on page 413.
To use Pre-ejection Period analysis, both an ECG Lead II and an ICG (dZ/dt) signal must be present. If either of
these signals requires classification, the analysis will run the appropriate classifier to define the relevant events on
the signals. To automatically apply motion filtering to dZ/dt, use Preferences to enable Motion Filtering (see page
418).
PEP analysis will output the following information on a cycle-by-cycle basis and the final line of the textual
output will be the average of all of the cycle measurements. All time unit output is in seconds unless
otherwise noted.
X

X

X

X

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Abbrev.

Description

Heart rate

BPM

The heart rate for the cycle as indicated in BPM. Derived from the RR interval.

Pre-ejection
period

PEP

Time interval between the Q wave of the ECG and the B point on the ICG for the cardiac cycle.
If the PEP cannot be computed for a particular cycle, it will have the value “----” in the textual output
or 0 in the graphical output.

RR interval

RR-i

Time interval between R peaks of a single cycle of cardiac data.

dZ/dt Remove Motion Artifacts

Applies SFLC motion artifact removal to a dZ/dt signal. Uses cycle information from an ECG signal to construct
a sinusoidal model of the ICG signal containing only components that are correlated to the heart rate.
IMPORTANT
Motion artifact removal will affect the amplitudes of the dZ/dt signal, so results derived from a motion filtered
dZ/dt signal should be additionally verified for accuracy.
This tool performs the same type of filtering as the ICG Analysis and Pre-ejection Period tools when the Motion
Filtering preference is enabled.
VEPT

Uses the truncated cone method to compute the volume of electrically participating tissue (VEPT) in cubic
centimeters of a subject. At the prompt, enter the height of the subject in the units set under Preferences. This
input can be used to calculate VEPT independent of other analysis routines, which may be useful for validation
purposes or other derived calculations.

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Preferences
Display results as
§ Textual tables in the journal
§ Channels of data inserted into the graph.
C-point location –see page 412
B-point location – see page 411
X-point location – see page 412
Stroke volume equation – see page 415
§ Kubicek, or Sramek, or Sramek-Bernstein
X

X

X

X

X

X

X

X

dZ/dt Max method – Baseline drift in ICG signals
can introduce drift artifacts into stroke volume,
cardiac output, and other measures that are sensitive
to changes in dZ/dt max. The Preferences offer two
settings. “Max dZ/dt in cardiac cycle” will extract the
maximum amplitude of dZ/dt as the max value. This
is the traditional way of measuring dZ/dt max. A
second estimate option, “change in voltage from B to
C” will take the amplitude delta between B and C as
the estimate of dZ/dt max. This will produce different
stroke volume results, but is useful for removing
motion artifact and improving consistency.
Body Measurement Units system for inputting
§ English system: body height in feet and
inches, distance between measuring electrodes
in inches, and body weight in pounds
§ Metric system: body height in meters and
centimeters, distance between measuring
electrodes in centimeters, and body weight in
kilograms.
Body Surface Area equation – see page 410
§ Boyd; DuBois and DuBois; Gehan and
George; Haycock; or Mosteller
Ideal Body Weight method– see page 416
X

X

X

X

Motion Artifact Removal
The Pre-ejection Period and ICG Analysis transformations have the ability to optionally apply motion
filtering automatically to the dZ/dt signal. Motion filtering is performed using an SFLC keyed to the R waves
of an ECG signal. The SFLC filtering approach is similar to performing cycle-by-cycle averaging of the dZ/dt
signal. This motion filtering approach may cause errors to be introduced in derived calculations, so any results
with motion filtering turned on should be validated additionally.
Filter Magnitude Level – relaxed, aggressive, and custom.
§ “Relaxed” uses a SFLC step size of .001. This allows the filter to adapt moderately quickly to changes in
the dZ/dt signal.
§ “Aggressive” uses a SFLC setting of .0001. The filter will adapt less quickly to changes in the ICG signal,
allowing better filtering out of motion artifacts at the expense of a lessened response to changes in
underlying ICG morphology.
§ “Custom” allows for an arbitrary SFLC step size. The step size must be greater then zero and much less
than 1 for the filter to converge.

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Magnetic Resonance Imaging

Magnetic resonance imaging, or MRI, is often used to study the brain and other organs in the body. As access
increases to MRI machines, researchers are beginning to combine MRI with traditional physiological signal recording.
The strong magnetic fields used by MRI equipment can cause profound artifacts in physiological recordings, which
can make the analysis of physiological recordings acquired in an MRI difficult. Some artifacts are external
interference while other artifacts can be caused by currents being induced in electrode leads or even in the body itself.
Artifact Location and Trigger Signals
Most of the MRI analysis options require information to identify the positions of various artifacts. Event positions
can be used or a “trigger signal” waveform in the graph can be used to identify periods when the MRI is active.
Some MRI machines have a TTL output that is synchronized with periods where the MRI is on.
· Whenever possible, this trigger signal should be acquired with the hardware unit along with the
physiological data.
Trigger detection off of an MRI trigger signal waveform is performed using fixed level thresholding on the
waveform data. The threshold level is set to be the minimum value of the entire trigger signal plus 1/10th of the
peak-to-peak distance of the trigger signal. The threshold is kept data dependent to allow for artificial trigger
signals to be derived from data if the MRI unit does not provide its own. The trigger signal may be acquired on
either an analog or digital channel.
Event driven artifact location can be useful when trigger signals are not available from the MRI or are not
recorded. A cycle detector analysis can be used to place events at the onset of each artifact, or these events may be
placed manually. Event based detection is also useful for applying the procedures for artifacts that are not directly
related to the MRI trigger signal, such as for removing the cardiac interference from EEG data caused by the
magnetic field of the MRI machine.
For more information on cycle detector analysis, see the Find Cycle section on page 341.
Artifact Frequency Removal
MRI > Artifact Frequency Removal

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Two large sources of interference in MRI recordings are the current induced by the MRI magnetic field and the
RF pulses used for triggering molecule alignment. While the overlap of this interference may be difficult to
separate in the time domain, the MRI interference may have a distinctive signature in the frequency domain.
Artifact Frequency Removal is a frequency domain adaptation of the ensemble projection removal of the Artifact
Projection Removal transformation. It attempts to cancel out MRI artifact by removing the frequencies most
strongly associated with the MRI signal.
For each channel of data to be denoised, either the MRI trigger signal or event positions are used to locate periods
of MRI activity for constructing an ensemble average. The FFT of this ensemble average is computed, and the
magnitude of the average FFT is set as the reference. Cyclic mean removal is applied to each period of artifact to
compensate for baseline drift or signals with expected DC offset. A second pass is then made through the data.
For each individual artifact, the FFT of that artifact is computed and the projection of that FFT onto the average
FFT is removed. After projection removal, negative Fourier components are discarded and a time-domain signal
is reconstructed using the inverse Fourier transform. This reconstructed, filtered signal is used to replace the MRI
artifact in the original data.
Application of projection removal in the frequency domain has similar limitations to applying it in the time
domain, that is, it assumes that the MRI interference is stationary (which is not necessarily the case). Variations in
the MRI interference may cause this method to fail.
IMPORTANT Artifact Frequency Removal requires an MRI triggering signal or artifact onset events to locate
artifact positions.

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Artifact Projection Removal

Artifact Projection Removal attempts to remove the noise components from the artifacts within a signal. An
ensemble average is made for each period of MRI artifact in a channel. Cyclic mean removal is applied to each
period of artifact to compensate for baseline drift or signals with expected DC offset. As the artifacts are averaged
together, the actual interference with the physiological signal caused by the MRI should become the dominant
feature if a sufficient number of artifacts are present. A second pass is made through the artifacts to remove this
average MRI artifact from each individual period.
The average artifact is removed using the Remove Projection transformation. This performs a vector projection of
the signal onto the averaged artifact estimation and subtracts this projection. This is an improvement over straight
subtraction of the average artifact as vector projection can compensate for changes to amplitude that may occur
over time.
Artifact projection removal cannot compensate for MRI interference that varies in frequency due to changes in
orientation of electrode leads within the MRI or other factors that may alter the MRI artifact.
Artifact projection removal is an adaptation of a denoising technique described in:
M. Samonas, M. Petrou and A. Ioannides, “Identification and Elimination of Cardiac Contribution in SingleTrial Magnetoencephalographic Signals,” IEEE Trans. Biomed. Eng., vol. 44, no. 5, pp. 386-393, 1997.
IMPORTANT Artifact Projection Removal requires an MRI triggering signal or artifact onset events to locate
artifact positions.
Median Filter Artifact Removal

Median Filter Artifact Removal provides a basic artifact removal suitable for slow moving signals such as
respiration, GSR, or temperature. It performs a windowed median transformation on the source channel with a
window width of 1/10th of the acquisition sampling rate.
This median filtering approach is explained in the BIOPAC MRI application note AH223.
Median Filter Artifact Removal does not require an MRI triggering signal.

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Signal Blanking

MRI artifact can grossly distort low level physiological signals, and this distortion can be several orders of
magnitude larger than the signal of interest. A common practice for analyzing the physiological data is to discard
the MRI artifacts and only examine the portions of the signal in between the MRI artifacts. One approach for this
is outlined in BIOPAC MRI application note AH223.
Signal Blanking provides an alternate approach for discarding MRI artifacts from the signal. Using the MRI
triggering signal or artifact event locations, this analysis option will locate the periods of MRI activity and
“blank” the physiological signal during this period.
Two types of “blanking” can be performed:
· Set value to zero – The waveform is set to zero during each artifact.
· For integrated measures, zeroing the signal may be preferable as it will have no effect on the running
sum.
· Connect endpoints – For each artifact, a selection is made and the values within the interval are replaced with
a line connecting the signal value before the MRI artifact to the signal value at the end of the interval.
· For statistical measures or DC coupled signals, connect endpoint (linear interpolation within the
interval) may be preferable to avoid causing the output to trend towards zero.
IMPORTANT Signal Blanking requires an MRI triggering signal or artifact onset events to locate artifact
positions.

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Neurophysiology
The Neurophysiology analysis package assists in the analysis of spikes within extracellular microelectrode recordings,
such as those recorded using an MCE100C module. All of these analysis options require a continuous recorded single
channel of microelectrode data.
· A spike is a deviation from the baseline caused by a neuron action potential. Frequently extracellular spikes will
resemble exponentials. The point of maximum value of the spike will be used to locate neuron firing.
· A spike episode consists of a fixed time window around a spike that aims to capture the underlying neuron
firing time. The episode consists both of the rise time (the time taken to reach maximum) and the relaxation
period around the spike.
Amplitude Histograms

IMPORTANT

To run this analysis option, the signal must first be transformed by the Classify Spike Episodes
option or the Locate Spikes option. (See pages 424 and 425.)
Amplitude histograms show the population density of the maximum amplitude of neuron firing events. They may be
used to interpret changes in neuron firing due to drug response or as rough indicators of the approximate number of
classes of action potentials in a signal. Amplitude histograms can be generated on classified or unclassified signals.
· On classified signals, an overall amplitude histogram will be created for all of the spikes in addition to a single
amplitude histogram per class (reflecting only the episodes of that class.
· On unclassified signals, a single amplitude histogram will be created from the maximum voltage within all of
the spike episodes.
Average Action Potentials

IMPORTANT

To run this analysis option, the signal must first be transformed by the Classify Spike Episodes
option or the Locate Spikes option. (See pages 424 and 425.)
After a classification has been completed for a spike signal, to assign spike episodes to different groups, users
may wish to view the average shape of the waveforms of each class. Examining the shape of the different classes
provides visual feedback as to the efficiency of the clustering, can allow for identification of certain classes as
noise or artifacts, and helps to determine if the identified classes are indeed unique. Average Action Potentials can
be generated on classified or unclassified signals.
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·

On classified signals, the resulting ensemble averages will have multiple channels.
o The first channel will be the overall average of all of the spike episodes.
o The remaining channels show the average of the members of each individual spike class.
· On unclassified signals, a graph will be produced with a single channel showing the average of all of the spike
episodes.
Classify Spikes
IMPORTANT If cluster events from a previous spike
classification are already defined on the
recorded waveform, this option will erase
them and replace them with the new
classification of the potentials.

This analysis option will automatically classify action potentials in microelectrode data and divide them into
different spike classes.
If the Locate Spike Episodes option wasn’t used to find spikes before this option was selected, the Locate Spike
Episodes option will be automatically performed prior to the clustering.
A single-feature k-means clustering classifier is used, and the entire data set is used for the clustering portion of
the algorithm. The determining feature is the Sum criteria— that is, the sum of all of the data points within the
waveform segment; this was one of the first features used in early action potential classifiers.
The clustering may not produce meaningful classes, so results should be examined for accuracy.
This style of classifier is for rudimentary spike analysis. For more advanced classification techniques, use the
clustering algorithm in the Find Cycle detector. (See page 352.)
Dwell Time Histograms

IMPORTANT

To run this analysis option, the signal must first be transformed by the Classify Spike Episodes
option or the Locate Spikes option. (See pages 424 and 425.)
A dwell time histogram shows the population density of the duration of a neuron firing event. Dwell times can be
approximated for an action potential by measuring the absolute value of the time interval between their maximum
and minimum voltage levels reached during the firing of the neuron. After the minimum value in the firing
recording has occurred, the neuron will be returning to its resting state, so the time difference is a good
approximation for the firing duration. The dwell time histogram plots this time difference versus number of action
potentials that have similar time differences. Examining varieties in dwell times can help to illustrate drug
responses or to perform rudimentary classification of action potentials.
Dwell times will be defined as the time difference between the positions of the maximum signal value and
minimum signal value within a spike episode. Since dwell time histograms can be used for classification
purposes, they can be run on classified or unclassified microelectrode signals.
· On classified signals, an overall dwell time histogram will be constructed for all of the spikes in addition to a
single histogram per class, showing times of only the spikes in that class.

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· On unclassified signals, a single dwell time histogram will be created for all of the spikes. When run on a
classified signal.
Find Overlapping Spike Episodes
IMPORTANT To run this analysis option, the signal must first be transformed by the Classify Spike Episodes
option or the Locate Spikes option. (See pages 424 and 425.)
In many extracellular recordings, it is frequent for there to be more than one neuron firing in response to the same
stimulus. This can result in overlapping spike episodes when both neurons fire in close succession. Some types of
analysis and spike classification are not able to produce meaningful results if too many overlapping episodes
occur. “Find Overlapping Spike Episodes” can be used to locate overlapping episodes. After the spikes have been
located in a signal, this option can be used to iterate only to those that are overlapping.
“Next Overlap” and “Cancel” buttons are available in the toolbar of the graph window to allow for iteration
through the episodes.
Note This option is “view only.” Overlapping episodes are not affected by the analysis and will need to be
manually removed manually to delete them from the file.
Generate Spike Trains

IMPORTANT To run this analysis option, the signal must first be transformed by the Classify Spike Episodes
option or the Locate Spikes option. (See pages 424 and 425.)
Spike trains are good visual indicators of when action potentials are firing and are good synchronization waves for
further analysis and data reduction. A spike train is a channel in a graph whose value is 0 when there is no spike
and 1 when there is a spike.
Spike train generation will operate only on signals whose action potentials have already been classified.
· A single spike train will be generated as a channel in the graph for each class of action potential in
the signal. Be sure to choose “Graph Channels only” or “Text and Graph Channels” in the
Neurophysiology Preferences. (See page 426.)
· If text output is enabled, the spike trains will be pasted as tables in the journal with one table per
spike class.
· If spreadsheet output is enabled, the tables will be placed side by side so index 1 of the tables lines
up for each action potential.
Locate Spike Episodes
Neurophysiology > Locate Spike Episodes

This option provides the basic spike detection for a microelectrode signal. Spike detection is performed using the
following steps:
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1. Obtain mean value of the entire signal.
2. Obtain standard deviation of the entire signal.
OR: Obtain an Amplitude/Half Width Discriminator of the entire signal. See Neurophysiology Preferences
for more information (page 426).
3. Detect spikes where the signal rises above a fixed threshold determined by adding a multiple of the standard
deviation to the mean.
4. Position the episode around the threshold crossings according to the width and offset entered previously.
A “Spike Episode Begin” event will be placed at the start of each spike episode and will be located offset
milliseconds away from the threshold crossing. A “Spike Episode End” event will be placed at the end of each
episode.
· If text output is enabled, a table of the start time of each episode will be placed in the graph’s
journal.
· If spreadsheet output is enabled, a new spreadsheet will be created with the start time of each
episode.
Spike episodes may also be located manually by using the Cycle Detector to define “spike episode begin” and “spike
episode end” events in the graph.
Set Episode Width and Offset

The first time spike detection is performed on a graph, the episode width and offset need to be entered. This width
and offset is remembered and is used for all future spike detections in the graph performed by “Locate Spike
Episodes” and other transformations. The width and offset that are entered are retained even if the file is saved
and reopened.
Use this option to view or change the current width and offset.
Preferences

Preference

Display results as:

Description

Determines whether analysis results will be displayed as graph channels,
textual tables in the journal, or Excel spreadsheets. Not all of the output
types are applicable for each Neurophysiology analysis option.

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Default
Setting

Text output to
journal only.

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Preference

Locate spikes
using:

Description

Default
Setting

Choose how spikes are searched for in the signal.
Mean + Stddev—uses fixed level peak detection with a level that is
computed from the mean value plus a configurable number of standard
deviations of the data.
Amplitude/Half-width Discriminator—allows for basic isolation of spike
shapes that have peak voltages within a configurable range and spike halfwidths within a configurable range; uses the amplitude of the spike as well
as the width of the spike to determine what constitutes a valid spike event.
Half-width For a given spike, the discriminator searches from the
maximum value of the spike to both the left and right of the
maximum for the sample positions where the value has
dropped below 50% of the maximum. The time interval
between these sample positions is defined as the estimate of
the half width. The acquisition sampling rate can be increased
to improve accuracy of the spike half width estimates as
neuron firing events involve high frequency components.

Mean +
Stddev

Each time the discriminator is run, the user must input the amplitude low
and high values as well as the minimum and maximum spike width. The
discriminator searches for spikes in a signal x as follows:
1. Performs regular peak detection on x using a fixed threshold. This
locates the local maxima occurring after each threshold crossing of
the low amplitude area. This results in a sequence p of potential spike
locations.
2. For each potential spike location p, computes the half-width time
interval.

where

t50r is the first time > p such that
t50l is the first time < p such that

Accepts the spike for each potential spike location p as a valid spike s if,
where a is amplitude and t is time window:

For each valid spike location s, positions the spike episode
start output at s+offset
end output at s+offset+width
The spike discriminator generates output only for spikes that fall within the
bounds of the amplitude and offset windows. If a spike
candidate falls outside the windows, no output is generated.
Spike stddv
amplitude
multiplier:

Spikes are located in the signal by looking for locations where the signal
deviates from its baseline by a certain number of standard deviations. This
multiplier is set in this preference.

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Preference

Description

Default
Setting

Default Episode
Width

The first time that any of the spike detection is run on a graph, the time
width of each fixed width episode must be specified. This preference
provides the default value that is seeded in the dialog.
The episode width for an individual graph does not need to match this
default.

10 ms

Default Episode
Offset

Each fixed width episode is located around one of the spikes in the signal.
The offset allows for the episode to begin before (or after) the spike
threshold crossing so the leading edge of the spike can be captured.
Negative numbers indicate episodes are to start before the spike threshold
crossing, positive numbers indicate episodes that start after.

-2 ms

Default Number of The Classify Spikes script requires the user to input the number of classes
Spike Classes
into which the spikes will be partitioned. This preference allows the default
number to be modified.
The number of classes that wind up being used does not need to match this
default.

2

Noldus Format
Supports import and export of files in Noldus Observer format. Noldus is a popular Human Behavioral analysis
software package and the AcqKnowledge Noldus feature allows behavioral markers to be imported from Noldus into
AcqKnowledge and AcqKnowledge marker information to be exported into Noldus. The following options are
available:
Export Events to Noldus XT

AcqKnowledge events can be exported to Noldus by “all types” or based upon selective criteria.
Import Markers from Noldus XT
The Import markers feature will read the Noldus file data and define the events in the active AcqKnowledge graph.
For each range of behavior, a pair of global markers will be added with labels correlating to the behavior type as well
as the start of and end of the behavior.
Watch the AcqKnowledge Noldus Observer import and export video tutorial for a detailed demonstration of
this feature.

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Principal Component Denoising

Removes noise from certain types of signals. For principal component denoising to be effective, more than two
signals should be used as sources and all source channels must have identical waveform sampling rates. PCA
denoising is most effective on signals that are known to contain a high degree of similarity, such as multiple ECG
leads or multiple EEG leads. PCA denoising should not be used on signals of different types or units as all of the
principal components may be needed to fully capture the differences in the signals.
Ü To determine if PCA denoising will be effective on a particular set of data or to compute a appropriate
variance percentage for denoising, examine the principal components directly with “Transform > Principal
Component Analysis” before selecting this option.
Given a set of signals, a principal component analysis is performed. The strengths of the components are then
analyzed, and the original signals are reconstructed from a subset of the principal components that capture a
certain percentage of the total variance of the signals. This essentially eliminates one or more of the higher-order
principal components. For certain types of signals, these principal components are the ones that model the noise
inherent in the signals.
1. Check the “Denoise” column for the channels to be denoised.
2. Enter the overall percentage of the variance.
3. After the percentage is entered, the denoising process will begin.
Remove Common Reference Signal (for Mobita Hardware only)
Mobita hardware uses a common reference amplifier design with unipolar lead capture. With this type of
amplifier design, there are common signals superimposed on all channels. When mixing unipolar and differential
signals, the average of all of the unipolar signals must be subtracted from them in order to extract the unipolar
signals. As this is a common operation for Mobita data processing a Specialized Analysis option has been created
to make this process easier. (Note that this feature is only intended for use with AcqKnowledge data acquired with
Mobita hardware.)

To remove the common reference signal, select the channels to be averaged and click OK. The signals with the
subtracted averages will be outputted to additional individual graph channels.

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Remove Mean
Remove Mean allows for mean subtraction to be performed for the selected area (or entire wave if no data is
selected). It will result in the mean value being the new zero value for the waveform.
Remove Trend

Remove Trend helps to remove baseline drift or other linear trends from data. This tool makes it easier to apply
trend removal to only specific segments of a waveform. Given a selected segment of data, or an entire waveform,
it computes the trend between the two endpoints (similar to the Slope measurement) and then removes this trend
from the selected area such that the endpoints of the selection lie at the same voltage.
Linear Regression
Use linear regression to estimate the trend to be removed from the waveform.
Slope between endpoints
§

Left keeps the starting point of the selection fixed at the same voltage. The software adjusts the data from
left to right such that the right endpoint is aligned with the initial starting voltage.

§

Right keeps the ending point of the selection fixed at the same voltage. The software adjusts the data
from right to left such that the left endpoint is aligned with the initial ending voltage.
Respiration

IMPORTANT—Respiration analysis assumes a bidirectional airflow signal that records both inhale and
exhale. Unidirectional respiration signals cannot be analyzed at this time.

The respiration analysis package helps to analyze respiration- and airflow-related data. Other tools exist for
respiration related analysis including AcqKnowledge transformations and the Respiratory Sinus Arrhythmia
analysis in the Hemodynamics analysis package.
Compliance and Resistance
Compliance and Resistance analysis can be used to extract pulmonary resistance and pulmonary compliance in
addition to basic airflow measures. This analysis requires an airflow signal and a pressure signal. The analysis
will extract all of the measures of the Pulmonary Airflow analysis for the airflow signal. It also will locate apnea
periods after exhalation using the same user-configurable threshold method as the Pulmonary Airflow analysis.
IMPORTANT— The flow signal must be recorded correctly for Compliance and Resistance analysis to
work. Compliance and Resistance analysis assumes positive flow indicates inhalation and negative flow indicates
exhalation (the flow conventions of the recommended connections for a BIOPAC TSD107 pneumotach or a
TSD117 airflow transducer).

·

If the flow signal was recorded with exhalation positive instead of inhalation positive,
multiply the flow signal by -1 to invert the signal.

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Pulmonary resistance is computed using the isovolumetric method. On both sides of the tidal volume peak for a
breath, the position where the volume reaches a user-specified percentage of the tidal volume is located. The
pulmonary resistance is defined as the difference in pressure divided by the difference in flow at these two
isovolumetric positions. Due to the discrete nature of sampled data, these points may not be exactly equal in
volume. To improve the accuracy of the isovolumetric method, increase the sampling rate used to acquire data.
Dynamic pulmonary compliance is extracted on a breath-by-breath basis by dividing the tidal volume by the
change in pressure between the exhale start and inhale start locations of the breath.
Individual breaths are defined as the period between consecutive Inhale Start events. Airflow units are assumed to
be the standard liters/sec and pressure units mmHg. For each breath period, the analysis will define the following
events:
· Inhale Start event on flow signal at start of inhale
· Exhale Start event on flow signal at start of exhale
· Apnea Start event on flow signal at beginning of apnea period (if present)
· Recovery events on volume signal at isovolumetric positions to left and right of tidal volume peak
If Inhale Start and Exhale Start events are already present on the flow signal at the start of analysis, those events
will be used to define the breath periods. Apnea Start and Recovery events will always be regenerated by the
analysis.
The analysis will extract the following measures from the data:
Name

Abbrev.

Description

Units

Cycle

Index of the breath in the data, beginning at 1.

Time

Starting time of the inhale of the breath.

seconds

Peak Inspiratory
Flow

PIF

Maximum absolute flow occurring during the inhale portion of
the breath.

liters/sec

Peak Expiratory
Flow

PEF

Maximum absolute flow occurring during the exhale portion of
the breath.

liters/sec

Tidal volume

TV

Total volume of air inhaled during the breath.

liters

Minute volume

MV

Volume of air that would be inspired during a minute given the
tidal volume and breathing rate of this breath.

liters/
minute

TV * BPM
Breaths per minute BPM

Breathing rate.

60
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Name

Abbrev.

Description

Units

Inspiration time

IT

Time interval between the start of inhale and the start of exhale.

seconds

Exhalation time

ET

Time interval between the start of exhale and either:

seconds

●

start of apnea (if apnea present)

●

start of subsequent breath (if no apnea present)

Total breath time

TT

Time interval between the start of inhale and the start of inhale
of the following breath. This is the sum of the inhalation time,
exhalation time, and apnea time.

seconds

Apnea time

AT

Time after end of exhalation where the airflow signal remained
within the apnea threshold defined at the start of the analysis.

seconds

Pulmonary
resistance

RES

Change in pressure divided by change in flow at the isometric
volume locations:

mmHg/
(liters/
sec)

Pulmonary
compliance

Cdyn

Tidal volume divided by the change in pressure between exhale
and inhale locations in the breath:

liters/
mmHg

If text output is being generated, an additional row will be added containing the average values of the measures.
Time and count are not output as waveforms in the graph since they can be found in the horizontal axis.
Penh Analysis
Penh Analysis script assumes standard recording methodology for a full body plethysmograph. Positive flow is
treated as exhalation and negative flow is treated as inhalation.

Penh Analysis extracts measures from data recorded in a full body plethysmograph. It operates on a single
channel of data recorded from an airflow transducer connected to the plethysmograph. The analysis takes a single
parameter: the Rt percentage. This percentage is used to locate the plateau, or “pause,” in the airflow signal. The
pause begins at the time when the Rt percentage of the exhalation volume has been reached. The Rt percentage
may be adjusted by the user and is set to a default of 65%. This analysis will place Inhale Start and Exhale Start
events on the airflow signal. If these events are already present when the analysis starts, the user-defined inhale
and exhale events will be used instead.

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This allows for the analysis to be repeated after manual inspection and correction of inhale and exhale locations
and allows for different methods to be used to define the breathing boundaries.
The following Penh Analysis options for enhancing data accuracy are also included:
Flow threshold – Using this setting allows breath detection to occur only when a subject’s inspiratory flow
exceeds a user-defined setting in units of liters per second. For example, if the threshold is set to 1.5 L/sec, the
inspiratory flow must exceed 1.5 L/sec for each valid breath. If the setting is left at 0, all breath activity will be
included in the output.
Breathing rate artifact rejection – Using this option will discard any respiration cycles that fall outside the
boundaries of a user-defined minimum and maximum respiration rate. This is useful for eliminating unwanted
signals resulting from small zero crossing spikes or other high frequency noise in the breath signal. This option is
enabled by default and set to the average range of a mouse breathing rate.
Show analyzed area waveform – this option adds a new waveform to the graph indicating the time areas
included in the analysis output. This analysis waveform can be useful for visually assessing the effectiveness of
modifying the artifact rejection settings.
Penh analysis will place Recovery events on the airflow channel at the time positions where the corresponding
percentage of the volume has been exhaled. The percentage used for the analysis is displayed in the label of the
Recovery events.
For each exhalation period, the Penh Analysis will extract the following:
Name

Abbrev.

Description

Cycle

Index of the exhalation cycle in the data, beginning
at 1.

Time

Starting time of the exhale for the cycle.

Units

Seconds

This is the location of the Exhale Start event.
Peak inspiratory
flow

PIF

Maximum absolute airflow occurring in the
inspiration cycle immediately preceding the
exhalation cycle.

Airflow
channel units

This measure is recorded as an interval, so its value
is always positive.
Peak expiratory
flow

PEF

Maximum airflow during the exhalation cycle being Airflow
examined.
channel units

Exhalation time

Te

Total time elapsed between the start of the
exhalation cycle and the end.

Seconds

This is the time interval between the Exhale Start
and following Inhale Start events.
Relaxation time
interval

Rt

Time required for the subject to exhale the specified Seconds
percentage of the total exhaled air.
This is the time interval between the Exhale Start
and the subsequent Recovery event.

Pause

Numerical factor describing the characteristics of
the plateau at the end of the expiration cycle.
Computed using the formula:

Te
−1
Rt

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Name
Enhanced pause

Abbrev.
Penh

Description

Units

Pause scaled to be relative to the strength of the
inhale and exhale. This helps take breathing
variability into account. Computed using the
following formula:

The Penh analysis excludes the following exhale cycles from the analysis:
· Exhale cycles that do not have a preceding inhale (may occur for partial cycles at the start of the data
recording).
· Exhale cycles that do not have a corresponding recovery time (often occurs during apnea).
· Cycles that fall outside the boundaries of the selected flow threshold and artifact rejection parameters.
In addition, during periods of apnea, the analysis may produce invalid results, such as zero width recovery times.
These results may be excluded from the analysis by either using waveform editing to remove apnea periods,
discarding all events during apnea periods and rerunning the analysis, or deleting the corresponding rows from the
Excel output.
Pulmonary Airflow

The Pulmonary Airflow analysis follows the flow conventions of the recommended BIOPAC connections for a
TSD107 pneumotach or a TSD117 airflow transducer. Positive flow is assumed to indicate inhalation; negative
flow is assumed to indicate exhalation.
The Pulmonary Airflow analysis extracts basic parameters from a calibrated airflow signal, such as would be
recorded using a pneumotach or airflow transducer. In addition to inspiration and expiration, Pulmonary Airflow
also can be used to examine apnea. Apnea is defined in this analysis as pauses in breathing that occur after an
exhalation.
When performing the analysis, an airflow signal ¦ is chosen. An apnea threshold a f is also entered. Inhalation is
defined to begin at the point where
. Exhalation is defined to begin at the point where
. Apnea is
defined to be the period between exhalation and inhalation where the flow lies within the apnea threshold:
. At least two consecutive samples must occur within the apnea threshold for a period of apnea to be
defined. This allows for valid transitions from exhalation to inhalation to occur even if one of the samples in the
transition happens to fall within the apnea threshold due to sampling.
The Pulmonary Airflow analysis will generate a tidal volume waveform if it is not present in the graph. It also
will add Inspire Start and Expire Start events on the airflow signal if they are not present. New Apnea Start events
will be defined each time the analysis is performed.
Individual breaths are defined as the period between consecutive Inhale Start events. Airflow units are assumed to
be the standard liters/sec.
For each breath period, the analysis will extract the following:

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Name

435

Abbrev

Description

Units

Cycle

Index of the breath in the data, beginning at 1.

Time

Starting time of the inhale of the breath.

seconds

Peak Inspiratory Flow

PIF

Maximum absolute flow occurring during the
inhale portion of the breath.

liters / sec

Peak Expiratory Flow

PEF

Maximum absolute flow occurring during the
exhale portion of the breath.

liters / sec

Tidal volume

TV

Total volume of air inhaled during the breath.

liters

Minute volume

MV

Volume of air that would be inspired during a
liters / minute
minute given the tidal volume and breathing rate
of this breath.
TV ∗BPM

Breaths per minute

BPM

Breathing rate for the breath.

BPM

60
TT
Inspiration time

IT

Time interval between the start of inhale and the seconds
start of exhale in the breath.

Exhalation time

ET

Time interval between the start of exhale and
either:
●

start of apnea (if apnea present)

●

start of subsequent breath (if no apnea
present)

seconds

Total breath time

TT

Time interval between the start of inhale and the seconds
start of inhale of the following breath. This is
the sum of the inhalation time, exhalation time,
and apnea time.

Apnea time

AT

Time after end of exhalation where the airflow
signal remained within the apnea threshold
defined at the start of the analysis.

seconds

If text output is being generated, an additional row will be added containing the average values of the measures.
Time and count are not output as waveforms in the graph as they can be found from the horizontal axis.
Preferences

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Spectral Subtraction
Spectral subtraction is a denoising technique that operates on data projected into the frequency domain. It is
frequently used in speech analysis denoising applications. Spectral subtraction examines a reference noise signal and
performs a Fourier transform to get the noise frequency distribution. To denoise a signal, the Fourier transform of the
signal is performed. The noise estimate frequency distribution is then subtracted from the source signal. The resulting
processed spectrum with the noise frequencies removed is then reconstructed into a time domain signal using the
inverse Fourier transform.
Spectral subtraction performs noise removal on the entire channel in a single Fourier transformation, which allows for
denoising where the noise is stationary; there is no provision for sliding window spectral subtraction at this time.
The spectral subtraction is performed using a formula with two adjustable parameters. Given a frequency spectrum
Fnoise and a mixed signal Fmix, the denoised frequency spectrum is computed using the following formula:

where
Alpha is the “scaling factor” and can be used to adjust the strength of the noise estimate.
Gamma (g) is the “power factor” and can be used to vary how the noise is removed.

g = 1 allows for pure subtraction
g = 2 allows for Euclidean distance formulas
and so on
Fdenoise that is less than zero is discarded and replaced by zero to maintain a valid set of Fourier coefficients for the
reconstruction.
When spectral subtraction is being used in practice, the noise signal may not always match the length of the signals to
be denoised. To define the subtraction formula, the spectrum of the noise must have the same number of points as the
spectrum to be denoised. If there is a length mismatch, the noise spectrum is resampled automatically to match the
length of the spectrum to be denoised. Cubic spline interpolation is used during the resampling to provide a better
estimate of the overall noise spectrum.
Stim-Response

The Stim-Response analysis package can aid in analysis of stimulus-response studies. It allows for measurements to
be extracted in tabular format for multiple stimulus classes. Stim-response configuration enhancements in
§ Measurement configuration is preserved across launches of the application.
§ Measurement presets may be accessed directly from the specialized analysis routine.
§ Additional checking for invalid channels and measurement expressions that cannot be applied to the source data
The Event-related EDA Analysis routine uses the stimulus events to categorize specific and non specific responses.
Responses are matched to the appropriate stimulus events using a user defined time window. See the Electrodermal
Activity EDA Event-related analysis section for further information.

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Digital Input to Stim Events
Digital Input to stim events identifies and labels stimulus events corresponding to any combination of digital inputs. A
light bulb icon is placed in the global events bar, the event is labeled with the stimulus event type, and the mouse-over
tag includes the event time. All event information is accessible and exportable from the Event Palette.

The Digital input to stim events function works with TTL trigger information coming from applications such as EPrime®, SuperLab®, DirectRT®, MediaLab®, Inquisit®, and Presentation. It converts TTL data acquired on the
digital channels of a hardware device into stimulus events. The system also works with analog and calculation channel
signals coming from switch transducers. Unlike TTL signals, a voltage threshold level is used to determine the
transition from low to high.
This analysis option converts TTL or switch data acquired on hardware
“Specific channels only” dialog
into stimulus events. Stimulus delivery events are defined in the graph for
each low to high transition of the digital data, the indications of stimulus
delivery. The digital channels are interpreted as a binary number. Each
stimulus event placed into the graph has the corresponding number
included with its label. This allows further analysis to distinguish between
different types of stimulus events by using the Cycle Detector’s label
matching capability.

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Digital line decoding can be two byte (using all 16 digital lines) or
single byte (on either the low eight or high eight digital lines). Big
endian bit and byte ordering are used, with digital line 0
representing the least significant bit.
When the stimulus labels are constructed, all numbers are zeroprefixed. All stimulus events will have the same number of base-10
digits with leading zeros, regardless of magnitude. This provides
each stimulus event type with a unique label that can be used with the Cycle Detector (which uses substring
matching).
Some systems that trigger digital lines such as parallel ports may not be able to do so instantaneously; they may
require a time window before the transition from one state to another is fully complete. A “transition latency” time
window can be given to the analysis, specified in microseconds, milliseconds, seconds, minutes, hours, or samples. If
non zero, any transitions that are separated by less than this latency are treated as a single transition and only one
stimulus event is inserted. The decoded value used for the transition is the maximum value observed during the
transition latency window. In the following example graph, the three digital TTL inputs correspond to one event, as
marked by the red icon in the global events bar. A transition latency of .5 seconds will consider all three as part of the
same event since the transitions occur within .5 seconds of each other.

Watch the AcqKnowledge Digital Input to Stim Events video tutorial for a detailed demonstration of
this feature.
Stim-Response Analysis
Stim-Response Analysis allows for extraction of measurements within fixed width intervals occurring at Stimulus
Delivery events. Stimulus events must be present to perform this analysis. The Stimulus Delivery events may be
defined either manually, with the Cycle Detector, or using the Digital Input to Stim Events analysis option. The
information that can be extracted includes the majority of the measurements available from the graph window
measurement toolbar, matching the Epoch Analysis options.
Unlike Epoch Analysis, the Stim-Response Analysis splits the analysis based upon the event labels. Stimulus Delivery
events with different labels are interpreted as different stimulus types. Analysis results for each individual stimulus
type are summarized in separate tables. Each independent text table has its own average of the measurements over that
stimulus type.
Additional options are available for positioning the fixed width interval where measurements should be made:
· At each stimulus event – The measurement interval is aligned so the start of the measurement matches the time of
the Stimulus Delivery event.
· At fixed interval offset before or after stimulus – The measurement interval begins a fixed amount of time either
before (for pre-stim studies) or after the time of the Stimulus Delivery event. This allows measurements to be
made at a time relative to each stimulus onset and may be useful for measurements focusing on a specific time
range (e.g. P300).

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At matching response event – This option assumes that a second set of Response events have been defined for
each stimulus either manually or using the Cycle Detector. Each Stimulus Delivery event is paired with the
closest Response event occurring after it. The fixed width measurement interval is aligned so the start of the
measurement window is the time of this matching Response event.
· To use the “at matching response event” window positioning option, Response events must be defined in the
graph. Response events are in the “Stimulus/Response” event submenu. These events are not defined
automatically.
· Response events can be inserted manually into the graph using the Event tool.
· Response events can be inserted using the event output of a data-driven Cycle Detector analysis.
Note If EDA/SCR signals are being analyzed in response to stimulus delivery, also examine the “Event-related EDA
Analysis” transformation located under Analysis > Electrodermal Activity.
Watch the AcqKnowledge Stim-Response Analysis video tutorial for a detailed demonstration of this feature.
Waterfall Plot
Assists in configuring the Peak Detector for 3D surface generation. 3D surfaces showing cycle-by-cycle graph
data are commonly known as waterfall plots. Cycles are located in the graph using the same sequence of steps as
the Ensemble Average transformation script, and cross sections for the plots can be selected on the basis of events
or peaks (see figures below). Instead of generating an averaged graph, however, a number of 3D surfaces are
rendered is a separate plot window. One surface is generated for each selected graph channel.
·

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Wavelet Denoising

Sample output
Wavelet Denoising applied to heart
sounds data may help clarify S1 and
S2, as shown:

Wavelet Denoising uses the forward and reverse wavelet analysis operations to project source data into the
wavelet domain, modify the wavelet coefficients (called “shrinking” the coefficients), and then reconstruct the
data from the modified coefficients. Wavelet Denoising allows for noise to be removed from a signal while
minimizing effects on portions of the signal that strongly adhere to a wavelet’s shape.
To perform wavelet denoising:
1. Choose the wavelet type to use for the denoising (Biorthogonal 4.4, Symlet 4, Coiflet 6, or Daubechies 8).
Certain signals may work best with different wavelet types.
2. Enter the number of iterations to use in the wavelet decomposition.
Different numbers of iterations will have different effects on the results.
3. Choose which type of thresholding should be used to shrink the wavelet coefficients.
§ Hard thresholding replaces coefficients below the threshold with zero while leaving all other coefficients
unmodified.
§ Soft thresholding zeroes out coefficients below the threshold and subtracts the threshold for coefficients that
are above it.
Soft thresholding may be useful for reducing edge effects, but hard thresholding will affect amplitudes less.
4. Choose the threshold level to use for shrinkage.
§ Fixed threshold for all levels. If a fixed threshold is selected, an additional window will appear into which
the threshold can be entered.
§ Adaptive threshold level based on the number of coefficients in the DWT iteration (a VIS shrink
procedure).

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ECG Analysis Algorithm References
AcqKnowledge 4 software implements the open source ecgpuwave ECG boundary location software and the open
source OSEA QRS detector and beat classification library for ECG analysis.
H

H

Automated ECG Waveform Boundary Location
Ü ecgpuwave ECG boundary location software

AcqKnowledge 4 software incorporates the ecgpuwave ECG boundary location software. Ecgpuwave is an
implementation of a waveform boundary detection algorithm primarily developed by Pablo Laguna at the
University of Zaragoza in Spain. This algorithm incorporates a variant of the Tompkins QRS detector, but
contains additional rules that allow it to automatically extract the following characteristics of an ECG signal
on a cycle by cycle basis: onset of P, P peak, end of P, onset of QRS, peak of QRS, end of QRS, onset of T,
peak of T, and end of T.
The algorithm is tuned to human ECGs through comparison with manual classification. Particularly, it seems
to be within the standard deviation of human examiners for the onset and end of T waves, a particularly
difficult feature to extract from an ECG complex. It also has the ability to take multiple ECG leads into
account to reduce errors and misclassifications and appears to function for one to twelve lead ECGs. The
algorithm is well documented in a number of papers. This algorithm development was sponsored by several
government agencies including CICYT in Spain and the NIH.
The ecgpuwave tool is distributed from the PhysioNet NIH servers (http://www.physionet.org). This is a tool
written in Fortran that will read WFDB formatted files. It will then output a series of annotations in WFDB
format indicating the locations of the various ECG complexes within each cycle. It also depends on another
tool, sortann (available from PhysioNet), to perform post-processing. This software reads and writes
PhysioBank formatted files.
AcqKnowledge can automate the process of running ecgpuwave on source data and import its output back
into AcqKnowledge. To run ecgpuwave on an ECG signal from within AcqKnowledge, select the ECG
channel as the active channel and then choose “Analysis > Locate Human ECG Complex Boundaries”*.
AcqKnowledge will execute ecgpuwave on that signal and read in its waveform boundary location output,
placing events on the channel. This output will only be visible when events are shown.
Alternatively, save the file to PhysioBank format, run ecgpuwave manually from a Terminal, save the
annotations to “atruth” and then reopen that PhysioBank file to see the ecgpuwave results. This is the same
process that AcqKnowledge performs.
Source code for ecgpuwave detector is released under a GPL license and can be found on the AcqKnowledge
CD.
H

H

H

*To apply the proper algorithm for animal subjects, choose “Analysis > Locate Animal ECG Complex
Boundaries.”

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OSEA QRS Detector
Ü OSEA QRS detector and beat classification library

Since the release of software version 3.9, AcqKnowledge incorporates the open source OSEA QRS detector
and beat classification library.
The OSEA library is a set of routines provided by EP Limited (http://www.eplimited.com). This C++ based
software library provides robust QRS complex detection and rudimentary beat classification. This library is
well documented and tested. The QRS detector uses a standard Tompkins-based filtering and derivative
detection algorithm and has been in development since about 1985; the beat classifier development began in
1997. This algorithm development is sponsored by the NIH.
This algorithm is fairly robust against arrhythmias, baseline drifts, discontinuities, and other artifacts in the
ECG signal. It achieves a 90% success rate on identifying QRS complexes on sample arrhythmia databases.
The algorithm is tuned to human ECGs.
The QRS detector is optimized for 200 Hz sampled data. If the sampling rate is lower or higher, data will be
internally resampled to 200 Hz before processing. The sampling rate difference may result in slightly different
placement of beat events for different sampling rates.
QRS detection can be performed by selecting the desired channel of ECG data and choosing Transform >
Specialized Analysis > Detect and classify beats. AcqKnowledge will execute the OSEA beat detector on the
source data and output a sequence of events on that channel of ECG data. This output will only be visible if
events are shown.
Source code for the QRS detector is released under an LGPL license and can be found on the AcqKnowledge
CD.
H

H

H

Open Source Licensing

The ecgpuwave and OSEA algorithms are available as open source, which means that their source code is
publicly available. The source code can only be used, however, under conditions of their licenses.
§ ecgpuwave is under the GPL license
§ OSEA is under the LGPL license
For the full text of both licenses, visit the Free Software Foundation (http://www.fsf.org).
H

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Chapter 18

Display Menu Commands

Overview
The Display menu includes a number of features that control how the waveforms appear on the screen and how much
data is displayed at a time.

Display menu and Show sub-menu

Although most of these options change the appearance of the data, they do not modify the data itself.
See the following shortcut options for Display menu commands:
§ Toolbar shortcuts, page 57
§ Context-sensitive shortcuts—page 69
X

X

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Tile Waveforms
Tiling is an operation performed on all waveforms to visually separate them on the screen. Tile Waveforms adjusts
the vertical offset to center waveforms in the display; if there are multiple waveforms displayed in chart mode, the
waveforms will be centered in their “tracks.” Tiling does not adjust the scale of the waveforms; it only affects the
midpoints of the visible portion of the waveform. Tiling does not affect the vertical scale factor previously set for each
channel (whereas Autoscale may affect the vertical scale factor as well as the offset).
In Scope mode:
· Tiling staggers the midpoint of the channels to visually separate them on the screen while
maintaining their scales.
·

Waveforms are spaced evenly along the vertical axis of the screen, and each waveform is centered
vertically in its division.
To apply tiling only to the selected waveform, hold down the CTRL key on Windows or the Option key on Mac OS
before selecting Tile Waveforms.
When grids are locked, tiling will retain the appropriate heights and percentages.
When grids are unlocked, the scale may be slightly larger in order to optimize the tick marks displayed on the vertical
axis.

Before Chart mode tiling

After Chart mode Tiling

Before Scope mode tiling

After Scope mode Tiling (red lines for illustration only)

Note that the waveforms are centered relative to the horizontal divisions of the plotting area; the range and midpoint
of the second waveform (blue square wave) are indicated in the figure above.

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Autoscale Waveforms
The primary use of Autoscale is to make all of the data of
the channel within the current time range visible on the
screen.
When Autoscale Waveforms is selected, AcqKnowledge
determines what the “best fit” is for each displayed
waveform. The percentages and midpoints are identical
whether grids are locked or unlocked.
The software adjusts the vertical offset so that each channel is centered in the window (or within the channel track in
chart mode) and adjusts the units per division on the vertical axis so that the waveform fills approximately two-thirds
of the available area. In chart mode, the waveforms are autoscaled to fit their sections. In scope mode, the screen is
evenly divided into horizontal “bands” and each waveform is scaled to fit the division without overlapping.
Ü The autoscaling algorithm for Chart mode and X/Y mode is:
1. Find maximum value of the channel in the time area, max.
2. Find minimum value of the channel in the time area, min.
3. If grids are locked, adjust scale such that max-min occupies 75% of the channel's track in Chart mode, or 75%
of the entire plotting area X/Y mode.
4. Adjust the midpoint so (max-min)/2 is at the vertical center of the channel's track in Chart mode, or vertical
center of the entire plotting area in Scope and X/Y modes.

Before autoscaling LVP channel

After autoscaling LVP (red lines for illustration only)

Ü The autoscaling algorithm for Scope mode is:
1. Divide the plot height into m equal sections of height h each.
2. Assign each visible channel to one of these plot sections.
3. If grids are locked, Scale the waveform such that the range between the max and min values will occupy 75%
of h.
4. Place the midpoint between the max and min at the center of the waveform's section.
In scope mode, the screen is evenly divided into horizontal “bands” and each waveform is scaled to fit the
division without overlapping.
Note: Autoscaling a single channel in Scope mode results in that channel occupying 1 /
(num_visible_channels) of the overall waveform plotting area. It will be placed in the region of the graph that
corresponds to its position in Chart mode.
See following page for examples of autoscaling in Chart and Scope modes.

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Autoscale Single Waveform
Use this option to perform the above autoscaling operations on a single selected channel rather than on the entire
graph.
Optimize Ranges (MP36R Hardware only)
When Optimize Ranges is selected, the Vertical Scales will be automatically adjusted for all channels that have a
Range Guide (green band) showing, such that the range limits are set to the upper and lower viewable limits of the
Vertical Scales. This allows the total Range of each input channel to be displayed. This menu item is active when data
is present AND at least one data channel has an active Range Guide.
This item is also selectable using the toolbar icon
or the right-click mouse shortcut. When selected with the icon
or the right-click, this item only optimizes the Range Guide of the active channel. To optimize the ranges for all
channels using this toolbar button, hold down the Ctrl or Alt key while clicking it.
Note: The Range Guide is the green vertical band that appears in the Vertical Scale region for analog input channels
only (not for duplicated, copied/pasted, or Calculation channels); see page 77.
Optimize Ranges and Range Guide are not available in MP160 or MP150 hardware.
Overlap Waveforms
Overlapping waveforms places all of the waveforms at the same scale and midpoint so that the plotting location of a
specific voltage on screen is at the same spot for every channel. Overlapping is useful for examining closely
associated waveforms, such as the calculated diastolic, systolic and mean calculation channels “overlapped” with the
raw blood pressure waveform from a continuous blood pressure signal.
In scope mode, when Overlap Waveforms is selected, the waveforms are “overlapped” into one screen. All of the
currently displayed waveforms are arranged in the graph window with the same vertical scale and offset so all the
displayed waveforms will fit on the graph; their magnitude reflects their size relative to the other waveforms. The
overall chosen scale for all the displayed waveforms will be a function of the pk-pk value of the combined waves.

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447

After Overlapping in Scope (red lines for illustration only)

Compare Waveforms
Compare Waveforms displays all of the channels with the same amplitude scale. Compare Waveforms automatically
sets the vertical scale to be the same for all channels and adjusts each channel offset so that all displayed waves are
centered in the display. The scale for all the displayed channels is determined by the channel with the largest pk-pk
range in the display interval. Compare Waveforms is useful for gauging the relative amplitudes of a number of
channels by placing them all on the same amplitude scale and discounting the effect of waveform offset (or baseline).
Ü In Chart mode, Compare Waveforms functions on each channel in its track.

Ü

In Scope mode, the channel scaling is similar but disperses the channels through the plot area similar to
tiling. For a graph with m channels being plotted:

Autoscale Horizontal
The Autoscale Horizontal command is a convenient way to display the entire data file (in terms of duration) on the
screen. When this is selected, the display will be adjusted so that the duration of the entire waveform fits in the graph
window. For long waveforms, this can take some time to redraw.
An Autoscale Horizontal function cannot be reversed with Edit > Undo. To revert to the previous display settings, use
the Display > Zoom back command.
Show All Data
The Show All Data command enhances the view by autoscaling first horizontally, then applies an “autoscale all
waveforms” operation. This enables all data vertical and horizontal data in the entire graph to be displayed for easy
viewing.
Show Default Scales
This option will resets a graph’s vertical and horizontal scaling parameters to the default settings used when the graph
was first opened.

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Zoom Back / Forward
Zoom functions can affect the horizontal scale, the vertical scale, or both. Zoom restoration is functional for the Zoom
tool, Autoscaling, and the Tile, Overlap, and Compare Waveform options. Zoom scales are stored until another zoom
function is performed. Multiple levels of Zoom are supported.
§ Zoom Back will restore settings one level at a time; This selection can be used to restore the original
zoom scales. Essentially, Zoom back acts as an “undo” command for the zoom forward command and any
other function that changes the amount of data displayed (either in terms of time or amplitude)
§ Zoom Forward will redo a zoom function after it has been undone; repeat this selection to restore the
latest zoom scales.
Zoom functions will work without limitation, until another Zoom is performed.
Reset Chart Display
The Reset Chart Display option redistributes the chart displays evenly after the boundaries have been changed so that
each channel’s vertical size is the same. This function, which only works in Chart Mode, can be useful for expanding
a display region for analysis and then returning to the original display.

Before Reset Chart Display

…and after

Reset Grid
To return to the original grid, choose “Display > Reset Grid.” This will reconstruct the default, unlocked grid of four
divisions per screen with solid light gray grid lines.
Adjust Grid Spacing
To modify the horizontal and/or vertical grid spacing, choose “Display > Adjust Grid Spacing.” This will generate a
dialog for modifying the locked axes of the selected waveform. See page 81 for details.
X

Set Wave Positions...
By default, channels are arranged on the screen based on their channel numbers, with the lower number channels
being displayed at the top of the screen. The Set Wave Positions option allows waveforms to be placed in a user
defined order.
Ø In chart mode this will result in vertical ordering of the individual waveforms.
Ø In scope mode this will result in vertical ordering of the individual waveforms after a tiling or autoscaling
operation.
It’s also possible to set any waveform to ignore the autoscaling and tiling functions. This is useful for selectively
applying autoscaling to certain graph channels of interest while omitting others.
The waveform positioning function is selected through the Set Wave Position in the Display menu. The following
dialog will then appear, with a scrolling list of all stored channels:

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If more channels are present than those displayed, scroll through the list by clicking on the vertical scroll bar at the
right. The list will scroll when moving past the top or bottom and clicking and dragging the waveform positions.
The “Tile” checkbox to the left of each channel enables tiling and autoscaling for each channel when checked. Click
the checkbox to toggle the enable.
The on-screen position of the waveforms is the same as the ordering shown in the above dialog (from top to bottom).
The waveforms can be repositioned by reordering the channel labels as they appear in this dialog. To change the order
of any waveform, select the channel label (e.g., CH1, ECG) and then click the Move Down or Move Up button.
Repeat this operation until the waveforms are in the desired order.
Ø Click OK to apply the selected order to the display screen.
Ø Click Cancel to revert all waveform positions to those set before the dialog was opened.
Set Channel Visibility
Set Channel Visibility offers an alternate means of showing and
hiding channels. Simply check or uncheck the channel “Show”
checkboxes to show or hide them. All channels can be shown or
hidden simultaneously by holding down the Alt key while clicking
the left mouse button. See also: Show/Hide Channels on page 91.
Wave Color
Select Display > Wave Color and then set the desired color of any
waveform. In scope mode, the vertical scale, channel text, channel
units and measurement popup menus take on the same color as the
selected waveform. When adding new waveforms, AcqKnowledge
assigns waveform colors in the following order: black, red, green,
blue, magenta, burgundy, and custom.

Or, click the right mouse button to bring up a menu, select Color, and then select the desired waveform color from the
color palette menu.

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Active Slice Color

To change the Active Slice Color in Stacked Plot mode (see page 36), use Display > Show > Active Slice and then
select Drawing options.
Horizontal Axis
Horizontal Axis generates the Horizontal Scaling dialog. Set the axis in
terms of time, frequency, or arbitrary units, and set the horizontal sample
interval (the amount of time between two sample points) and the first
sample (sample offset).
Time domain scaling has two options to store and display data:
· (ss.sss) —absolute seconds; the time scale for an event occurring 30
seconds into the record would be 30.00 seconds
X

X

· (HH:MM:SS) —hours:minutes:seconds; the time scale for the same event would be 00:00:30.
Set the Time Unit precision via Display > Show > Selection palette, then press Enter (return) to accept changes.

The Frequency Units option plots data from a Fourier analysis or other data with a frequency base (rather than a time
base). This option is only available when frequency units are present in the graph. As with the time options, this
feature is typically used for importing text files from other applications. For instance, when importing a text file with
1,000 sample points that covered a frequency range from 0 Hz to 100 Hz, set the interval to 1000 Hz/100 samples, or
0.1 Hz per sample in the box to the left of the interval text box. Similarly, if the frequency range was 20 Hz to 100 Hz,
set the offset to 20 Hz. Arbitrary base units can also be attached to the data (rather than a time or frequency base
When the horizontal axis corresponds to wavelength, and the data consists of 100 samples covering a range from 1 to
10 Angstroms, the interval should be 0.1 units per sample.
Arbitrary units are generally useful for changing the time base (or other horizontal scale) of data that has been
imported into AcqKnowledge as a text file. For instance, to analyze data imported from a text file that contains 30
seconds of data that was collected at 100 samples per second (100 Hz), the first step would be to open the file
(following the directions on page 265).
When arbitrary units are selected, two additional text boxes appear at the bottom of the dialog. The upper Units text
box is used to provide a name for the horizontal scale units and the lower Units text box is used to provide an
abbreviated label for the horizontal units.

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By default, AcqKnowledge assumes that the data was collected at 50 Hz, and would therefore plot the data so that a
60 second record was displayed that appeared to be collected at 50 samples per second. To change this to reflect the
rate at which data was actually collected, change the sample interval box in the horizontal scaling dialog. When data
are displayed on a 50 Hz time base, the sample interval will read 0.02 seconds per sample. This means that there is a
0.02-second “gap” between sample points in the record. To display data at 100 samples per second, change the
interval to 0.01 seconds per sample.
To determine the sample interval for other sampling intervals, divide 1 by the rate at which data was sampled (in
terms of samples per second). Thus, a sampling rate of 0.5 Hz would translate into a sample interval of 2.00 seconds
between samples, and data collected at 100,000 Hz (100 kHz) would have an interval between sample points of
0.00001000 seconds.
TIP:

To confirm that AcqKnowledge is storing data in the same time base it was collected in,
choose Channel Info from the Display menu. This will generate a dialog that describes
(among other things) the sampling rate AcqKnowledge uses in analyzing the data. Once
data has been saved as an AcqKnowledge file, X-axis base information is automatically
saved along with the data. AcqKnowledge also saves X-axis in Frequency (FFT) or
Arbitrary (Histogram).

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Show
Selecting Display> Show generates a submenu controlling the data display options and other additional information
appearing in the graph window. To enable an option, select it in the submenu. A checkmark appears next to the
enabled menu items. The three display modes and the two plotting modes are mutually exclusive, but the remaining
items can be enabled independently.
Show Option

Shortcut

Explanation

Annotations

Toggle show/hide of text annotations.

Channel
Buttons

When the Channel Buttons option is selected, the channel boxes appear just above
and below the graph area.
Channel Buttons with Channel 1 selected
These buttons are useful for selecting channels and “hiding” channels by positioning
the cursor over the channel box, holding the ALT key on the Windows or the
Option key on the Mac, and clicking the mouse button.

Channel Input
Values

When enabled, adds real-time display of channel amplitude values above the graph.
(“Show textual value display” must be enabled in the Vertical Axis settings.)

Chart

Activates the Chart display mode (see page 34).

Display Mode
Toolbar

Activates toolbar shortcuts for Chart, Scope, X/Y, Stacked Plot, Horizontal Split
View and Data View.

Dot plot

Dot Plot allows viewing of data in a “dot” format. This is useful for demonstrating
the concept of discrete digital sampling by dividing the waveform up into data
points or “dots.”

Dot size

Dot size is enabled after Dot Plot is selected.
Dot size specifies how large each dot will be. Each dot
is measured by the number of monitor pixels it
occupies.
Each “dot” corresponds to a sample point. (For
example, data collected at 100 samples per second
would display 100 dots per second.)

X

X

Events

Displays the event marker region at the top of the graph window. See page 225 for
Events.

Event Bar

Enables Event Bar display on toolbar.

Event Palette

Displays the Event Palette (see page 228 for Event Palette details.)

Focus Areas

Enables Focus Area display. See page 92 for Focus Areas.

Focus Areas
Bar

Enables Focus Area Bar display on toolbar.

Grid

Superimposes a Grid on the graph window (see page 48). To change grid precision,
use the axis scaling dialog of the horizontal or vertical axis.

Grid Options

Activates the Grid Options dialog (see page 83 )

Hardware

Show/Hide Hardware “Connected to:” dialog in the graph display; includes
network access.

Journal

Activates the Journal (see page 50).

Last Dot Only

Plots only the most recently acquired data point. Only available in X/Y mode.

X

X

X

X

X50

X

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Show Option

Shortcut

Explanation

Line Plot

Right-click
menu

Connects each sample point with a line to create the waveform. Waveforms that are
displayed in line plot mode match a true analog plot (as closely as possible). This is
the default display mode for most waveforms, except histogram plots, which are
displayed in Step Plot mode (see 327). The line options can be changed by clicking
the right mouse button, which will generate a menu displaying several commonly
used features.
X327

Line Thickness

Right-click
menu

X

Line thickness is enabled when Line or Step plot are
enabled. Use to specify the plot thickness in pixels.

Sine wave set to thickness of 5 pixels

Main Toolbar

Controls visibility of Main Toolbar buttons (Grid, Show/Hide, Preferences and
Customize Toolbar).

Measurements

Displays the measurement popup menus and windows above the graph window (see
pages 47 and 94).
X

X

X

X

Scaling Toolbar

Controls visibility of Scaling Toolbar shortcut buttons (Autoscale Vertical,
Autoscale Horizontal, Show All Data, Center Data Vertically, Center Data
Horizontally).

Scope

Activates the scope display mode (see page 34).
X

X

Selection
Palette
Many tools within the AcqKnowledge environment are based around the selection.
The selected range of data in the graph is used as the source for measurements,
waveform editing, transformations, and other operations. The Selection Palette is a
floating dialog that can be used to precisely enter the selection.
· The Selection Palette can be used to adjust the selection at times when it is
not possible to use the selection tool in the graph window, such as when
transformation dialogs are being displayed for the graph.
· The selection palette offers a way to change the selected area without
having to cancel the transformation setup and lose any parameters typed in
the dialog.
To display the Selection Palette, choose Display > Show > Selection Palette. This
dialog contains two edit fields that display the location of the left and right edges of
the selection using the measurement units currently displayed in the horizontal axis.
As the selection is changed, the new selection boundaries are shown.
The Selection Palette also can be used to manually type in the edges of the
selection. Double-click the edges and type in the new horizontal position of the edge
of the selection. Press “Return” to adjust the selection to that time location and
update measurements and the visible display on the screen.

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For graphs displayed in X/Y mode, the Selection Palette can be used to adjust the
X-axis range of data plotted on the screen. Limiting the time range can be useful for
generating X/Y plots for different intervals of the graph for comparison, such as
examining PV loops from different time periods of a recorded signal.
Click the small arrow in the top right of the selection palette for the following
additional options:

Spectrum
Analyzer
Palette

· Mark Selection—Use this option to bracket a selected area with event
markers.
· Paste edges in Journal—This option pastes a line of text into the Journal
that includes the left and right edge measurements of the selection.
· Create Focus Area—This option turns data highlighted by the selection
palette into a labeled Focus Area.
· Time units—Use this submenu to change the time units used in the
selection palette. The following time units are available: Match units on
axis; Hours; Minutes; Seconds, Milliseconds, Microseconds and Samples.
The Time units submenu will be dimmed unless the graph displays
time/arbitrary measures).
· Frequency units— Use this submenu to change the frequency units used in
the selection palette. The following frequency units are available: Match
horizontal axis, Kilohertz, Hertz, Millihertz and Samples. The frequency
submenu will be dimmed unless the graph displays frequency-based
measures.
Note Changing time/frequency units in the selection palette can be helpful during
zoom operations when the units displayed in the horizontal axis may not be
the most convenient for inputting new selection boundaries.
· Arbitrary Units—Use this submenu to change the arbitrary units used in
the Selection Palette display (Units or Samples).
Provides a dynamic display of the frequency decomposition of data, in real time or
post-acquisition. See page 458 for details.
X

X

Timers

Enables display of stopwatch and elapsed timer toolbar.

Location
Palette

AcqKnowledge 5 supports import of GPS location data into AcqKnowledge graphs.
This is useful for correlating a subject’s geographic location with physiological data
acquired during extended exercise studies where a subject might wear a long-range
wireless device, such as BIOPAC’s Mobita and BioHarness loggers. The Location
palette, like the Selection and Spectrum Analyzer palettes, is a floating dialog that
can be dragged, resized or repositioned as desired.
In order for the Location palette to be operational, the subject must first log data
with a compatible GPS tracking device, such as the BIOPAC GPSTRACK. The
resulting GPS data can be imported from the tracking device into the
AcqKnowledge exercise study graph, which populates the Location palette in a
navigable map format. The resulting map shows the physical location of the subject
throughout the exercise.

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After Import:
· Browsing GPS graph data with the I-beam selection tool will relocate
the red navigation arrow to the map location occupied by the subject at
that exact point of the experiment.
· The map view is zoomable, and any of three different map servers can
be selected in the preferences.

Location palette showing coordinates, zoom and recenter tools
To log GPS data:
1. Attach the GPSTRACK device to the subject and turn on the power.
2. Run the experiment. (For example, subject walks, runs, or bicycles an
assigned geographical route during an exercise study where data is being
acquired into AcqKnowledge via a wireless logger.)
3. At the conclusion of the experiment, turn off the GPSTRACK and remove it
from the subject.
To import GPS data into AcqKnowledge:
1. With the exercise study graph open in AcqKnowledge, launch the Location
palette (Display > Show > Location Palette).
2. Connect the GPSTRACK to the computer’s USB port.
3. Click the arrow in the upper right corner of the Location palette and choose
“Import Location Data.” The GPSTRACK used will appear in the “Import
from:” menu.

4. Click OK to import location data into the graph. The imported location data
will be saved with the graph. Be sure to select the correct GPS device or file
format. (AMCO AGL 3080, Columbus GPS, *txt or *.gpx format.)
Explanation of Options:
· Import Location Data – Use this option to import logged GPS
data into AcqKnowledge graph.
· Erase log after data is imported – If selected, the log file on the
GPS device will be deleted following import.
· Export Location Data – Use to export GPS data in graph to a text
file format.
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·
·

Remove Location Data – Removes all location data from graph.
Reconnect to Map Server – Use to connect/reconnect to any of
three supported map servers (Nokia Ovi Maps, Google Maps, Open
Street Map)
The default Map Server may also be selected in the Location Preferences (Display
> Preferences > Location).
Limitations:
When using Edit > Merge to merge graph files from multiple hardware units: If only
one graph file contains embedded GPS data, the GPS data will be copied into the
merge output graph. If more than one graph has GPS data, no GPS information will
be present in the merge output graph.
Data snapshots will archive any GPS data present in the graph and retain it in the
snapshot. When the snapshot is restored, the archived GPS data will be extracted
into the newly created graph window, showing the data from the snapshot.
GPS data in a graph file is read-only and cannot be modified directly within the
software. To modify the GPS information, the data must first be exported, edited
externally, and then re-imported.
Stacked Plot
Options

Displays options that can help visually distinguish
the active slice from other slices being drawn in
Stacked Plot mode. See page 37 for details.
X

Step plot

X

Displays waveforms in a “step” plot, meaning that the lines connecting sample
points are drawn either vertically or horizontally. Step plot is most useful for
displaying histograms and similar plots, but since it displays data much as it appears
to a digital processor (like the MP and other hardware units), it can also be useful
for examining the effects of various sampling rates.
NOTE: Step plot is mutually exclusive of line plot.

Toolbar

Displays the toolbar (shortcut) icons across the top of the display (see page 57).

X/Y

Activates the X/Y display mode (see page 34).

X

X

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Customize Toolbars

Use the Customize toolbar feature to create custom toolbars for easy access to post-processing Analysis, Transform,
and Script actions. Toolbars are dockable and custom toolbar placeholders can be named independently of toolbar
actions.
§

Actions – Menu list of available Analysis, Transform, and Script functions

§

Toolbars – List view of custom toolbar placeholders

§

Current Toolbar Actions – List view of available actions from Analysis and Transform menu
Button

Function

Explanation

Add toolbar button

Adds placeholder for new toolbar. (More than one toolbar action can
be grouped under one placeholder).

Remove toolbar button

Removes placeholder for toolbar.

Rename toolbar button

Allows existing custom toolbar name to be edited.

Up arrow

Moves a toolbar action up the list.

Left arrow

Removes a toolbar action from the list.

Right arrow

Adds a toolbar action to the list.

Down arrow

Moves a toolbar action down the list.

Clear button

Removes all toolbars from Toolbars and Current Toolbar actions list.

OK button

Enforces addition or removal of toolbars from list or application
toolbar region.

Apply button

Applies changes without closing Customize Toolbar window.

Cancel button

Dismisses any toolbar changes without applying.

NOTE: If a Scripting license is present, the standard items of the script menu, as well as all user scripts in the menu
will be available as buttons to be added into custom toolbars.

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Spectrum Analyzer Palette Details

Spectrum Analyzer breaks time domain signals into their respective frequency components to provide a dynamic
display of the frequency decomposition of data, in real time or post-acquisition. Spectra can be generated in real time
based on the most recently acquired data or post-acquisition based on the selected area of a saved data file.
· Spectrum analyzers can be useful for locating and correcting noise sources in a system as well as other
frequency domain analysis.
· The Spectrum Analyzer displays the FFT of a portion of data of a single channel.
The spectrum analyzer applies to all graph windows displaying data in the time domain. Viewing the underlying time
domain data at the same time as the spectral information also provides useful visual feedback with regards to signal
quality. The palette allows for continuous availability of the spectrum analyzer across multiple graphs and for
positioning alongside original data. The channel is always indicated by the popup menu within the spectrum analyzer
itself. The graph whose data is analyzed will always be the topmost graph; this is the graph whose window is highest
in the Z ordering.
Mode:
Real-time
Analyzes the most recently acquired data in a graph. The analyzer generates full FFT output so, in
linear units, it is the regular FFT multiplied by two. The analyzer extracts the spectrum based on a
sliding window of samples at the tail end of the signal and periodically refreshes the spectrum plot
during acquisition. The analyzer uses a fixed width window size. The first spectrum will be generated
after the number of samples needed to fill the initial window has been acquired. If no data is being
acquired, the analyzer will not display any frequency information and will appear to be off.
Selection
Analyzes the highlighted section of the active channel of a saved graph (post-acquisition). Select the
channel to be analyzed from the channel popup menu.
Palette popup

(upper right) Displays the spectrum analyzer palette popup menu for
performing other operations on the spectrum including extracting the
spectrum to a new graph window and copying spectrum data to the
clipboard or journal. Options are dimmed if there is no spectrum
available.
New …
New Graph with Spectrum constructs a new graph window
with the contents of the spectrum. This allows for more detailed examination of the
spectrum than is possible with the tools in the spectrum analyzer palette.
Paste…
Paste Spectrum to Journal makes a textual representation using the current Journal
preferences and copies the text into the graph journal of the graph whose data is being
analyzed. This will prompt to create a journal if none exists.

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Copy…

Channel
Real-time

Selected

Plot display

Auto Vert
Auto Horiz
Settings

Copy Spectrum to Clipboard makes a textual representation using the current Journal
preferences and copies the text to the Clipboard.
Settings… Displays the spectrum analyzer settings dialog. Equivalent to using the Settings button at
the bottom of the palette; see Settings below for details.
Indicates which channel of the hardware setup or graph is being analyzed. The “Channel” popup
menu contents vary with the analyzer mode:
Channel popup menu lists active channels whose “Acquire” checkboxes are checked in Hardware >
Set Up Channels. The channels will be listed as “{A,D,C}{0-16}, chan_title” where chan_title is
replaced with the manually entered title in the channel setup window.
The channel popup menu matches the channel menu of measurements in the topmost graph window.
The menu starts with “SC, Selected Channel” which, when chosen, uses the data of the active channel
of the graph. The remainder of the menu lists the channel numbers and labels of the channels within
the topmost graph.
Plot of the spectrum of the corresponding data.
§ Vertical axis units match the source channel (displays either “dbV” or linear)
§ Horizontal axis displays frequency and is always displayed in “Hz.”
If there is a valid data selection that can be used to compute a spectrum, the spectrum will be
displayed in this area. If there is no valid data selection, no axes will be displayed and the plot will be
replaced with the text “Not Available.” The following conditions cause spectra to be unavailable:
§ graphs that contain no data (either no channels or only empty channels)
§ graph is being displayed in XY mode
§ graph uses either frequency or arbitrary units for its horizontal axis
When operating in selected area mode, the following additional conditions also cause spectra to be
unavailable:
§ selection contains no data on the active waveform
§ selection is a single-point selection (not enough data to compute FFT)
When operating in real-time mode, the following additional conditions also cause spectra to be
unavailable:
§ no data acquisition is in progress
Click to autoscale the spectrum to fit all amplitudes within the visible spectrum plotting area.
Click to autoscale the spectrum to fit all frequencies within the visible spectrum plotting area.

Plot color Colorwell that changes the color used to draw the spectrum in the palette. Click to display a standard
color picker.

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Window

Width specifies the window size used when performing analyses in real-time mode. The spectrum
will always reflect the frequency characteristics of the most recently acquired data of the graph, using
this window size as the number of sample points to use. This popup will list various powers of two,
ranging from 256 to 4096 samples.

FFT Options
Padding—used whenever the number of input points is not an exact power of two. Data can be
padded either with zero or with the amplitude of the last data point.
Remove mean—Subtracts the mean value of the data is prior to frequency analysis. This helps
remove the zero frequency component caused by DC offset.
Remove trend—Connects the endpoints of the data with a line and removes this linear trend from the
data prior to frequency analysis. This can help compensate for drifting baselines.
Units—control whether the data is displayed using a logarithmic scale or a linear scale.
Window—enables the standard AcqKnowledge FFT windowing options, to adjust the data to remove
effects resulting from the discontinuities of data at the two edges. See page 333 for details about FFT.
Value

Click the crosshair icon
to display the frequency and amplitude values of the spectrum when
moved within the spectrum display. The mouse cursor will change to a crosshair when inside the
spectrum plot. The frequency and amplitude values corresponding to the mouse position are displayed
above the spectral plot. Hold the mouse button down to display the amplitude of the spectrum at the
horizontal mouse position, along with a crosshair cursor highlighting the exact location shown on the
spectrum. If the active spectrum is compressed (that is, if multiple samples exist for a particular
horizontal position), the value extracted will be the maximum value displayed at that pixel position.

Zoom

Click the magnifying glass
to perform zoom operations. Click and drag the mouse cursor (which
will change to a magnifying glass) in the plot display to select the area to zoom in on. Alternately,
click either of the axes of the spectrum palette to display a dialog used to enter display ranges
manually. Enter the start and end points of the desired range for each axis. There are no grids in the
spectrum analyzer palette, so the axis scaling dialogs of graphs are not applicable. Note: adaptive
scaling will be disabled for the spectrum display when either the zoom tool or the axis endpoint entry
dialogs are used.
TIP: To zoom out, hold the Alt key (PC) or Option key (Mac) while clicking mouse
over zoomed area.

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Channel Information
The Display > Channel Info…item generates an information dialog for the selected channel.
Channel Information may also be displayed by right-clicking in the channel and selecting “Channel Info…” from the
contextual menu.

Line Freq: Files created with AcqKnowledge 4 and 5 include the line frequency (50 Hz or 60 Hz); files created in
earlier versions will display “Unknown.”
Channel: Use this popup menu to select the desired channel for displaying information.
Type:
Use this popup to set the primary signal type if it is not specified in the selected channel. Defining a
signal type here will place an Analysis Shortcut button into the channel. For more information about
Analysis Shortcuts see page
Subtype: Use this popup to set the secondary signal type in the selected channel. This can be a derivative of the
primary signal.
Interval: The time between sample points, which is the reciprocal of the sampling rate. The sampling rate can be
modified by using the resample function (described on page 322), by changing the interval horizontal
scale (see page 450), or by pasting data collected at one sample rate into a graph containing data sampled
at a different rate.
Length:
Indicates the overall length of the channel in samples and in time. The waveform length is generally the
same for all channels but there are exceptions:
· Downsampling a channel during acquisition
· Transform > Resample Waveform/Graph
· Edit operations – Cut, Copy, Paste, Clear
Min:
Provides the minimum value for the waveform data.
Max:
Provides the maximum value for the waveform data.
Mean:
Provides the mean value for the waveform data.
X32

X

The fields below the statistical information contain transformation histories, time/date stamps, parameters, and values
for selected channels.
Modification History: Any change to the Type or Subtype will be logged and saved in this field. The date and time
of the Type and Subtype are also recorded.
Parameter and Value If a transformation is applied to the data, the transformation type and its settings and values
are also recorded in this field.
Paste Selected Channel to Journal
Pastes transformation modification history for selected channel to Journal.
Paste All Channels to Journal
Pastes transformation modification history for all channels to Journal.
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Preferences...
To generate the Preferences dialog, select Display > Preferences on Windows or AcqKnowledge > Preferences on
Mac. Use Preferences to control measurement options, how waveforms are displayed, and other AcqKnowledge
features. Select an option in the list on the left of the Preferences dialog and then set the respective preferences
displayed on the right.
See page…
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Measurements Preferences
§ Measurement rows—determines how many measurement rows will be displayed in the graph window.
o Use Display > Show > Measurements to hide the measurements; see page 452 for details.
§ Measurement columns—determines how many measurement columns will be displayed in the graph window.
§ Precision—controls the accuracy of digits displayed right of the decimal (1-8) for all measurement results. For
example, with the precision set to 3, a measurement result might be 125.187.
§ Use linear interpolation—toggle to enable/disable measurement interpolation.
§ Time/Frequency units—sets the measurement unit to use for time and frequency pop-up measurements. This
locks the units for the measurement result display (i.e., if seconds is selected, a result of 70 seconds will display
as “70 seconds” rather than “1.16667 minutes”).
o Best match—Scales units to best match the interval for time and frequency based on the total file. For
example, won’t set a 3 hour file to display in msec.
§ Include for Journal/Clipboard options
§ measurement name (i.e., BPM, Delta T, Freq, etc.) with the values.
§ measurement units (i.e., volts, mmHg, and so forth) after the numeric values.
§ measurement parameters used to compute the measurement function result, such as the location and
operator used for Calculate measurements.
§ channel numbers at the top of each column of data.
§ timestamp—Automatically insert the time of day and the date when pasting measurements or wave
data. This timestamp can be correlated with selection events to reconstruct the selected area.—useful
for GLP auditing.
§ Use a separate line for each measurement in the journal/clipboard
§ Mark selection with events in graph—Automatically insert a pair of Global Selection Begin and Selection
End events at the selection boundaries when pasting measurements or wave data. These events will be
timestamped with the time of day and the date when the paste occurred. This timestamp can be matched to the
result of “Include timestamp” to recreate selected areas for reconstructing measurement results or re-executing
wave data exporting—useful for GLP auditing.
§ Journal Table Export Options – Sets the options for how multiple measurement rows are displayed in a
Journal table.
o Put all values in a single table row – Extends multiple measurement rows horizontally into one table
row.
o Use one table row for each measurement row – Divides the measurements into multiple table rows in
the same manner shown in the measurement toolbar.
Waveforms Preferences
In the center of the dialog are two options that control how waveforms are displayed on the screen.
§ Gray non-selected waves—When enabled, the active wave will be drawn in a solid color and any non-selected
waveforms will be drawn using lighter, dotted lines (or with lighter colored dots if dot plot is in use). This can
help emphasize the selected waveform when viewing data in Scope mode.
§ Draft mode for compressed waves—allows for some (“compressed”) waveforms to be plotted in “draft”
mode, which results in faster plotting time, although the display is not exact. A waveform is considered
compressed when more than three sample points are plotted per pixel on the screen. For example, on a VGA
display that is 640 pixels wide, a compressed waveform would be any type of waveform displaying more than
2000 samples (approximately) on the screen at any one time. Using the default horizontal scale (which plots
eight seconds of data on the screen), any data sampled at more than 250 samples per second would be
considered “compressed.”
§ Scaling/Transformations—the following options determine how data will appear on the screen after it has
been transformed (e.g., filtered or mathematically operated on). Neither option affects how data appears on the
horizontal axis, although both options change how data is presented along the amplitude (vertical) axis.
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Duplicate before transformations will create a new channel showing the data as it originally
appeared before the transformation was applied. This will preserve the original view for comparison
to the transformation.
o Autoscale after transformations will automatically rescale all waveforms after a transformation to
provide the “best fit” along the amplitude axis.
o Tile after transformations tiles all visible waveforms after any transformation, and is mutually
exclusive of the autoscale command. Tiling visually separates the waveforms on the screen.
§ Mark waveform edits with events—Insert an event at points where waveform edit commands have been
applied.
§ Include time value—copies the horizontal scale values along with the waveform data when data is copied to
the clipboard. This means that horizontal scale information is retained when AcqKnowledge data is pasted into a
spreadsheet or similar application.
§ Include timestamp—Automatically insert the time of day and the date when pasting measurements or wave
data. This timestamp can be correlated with selection events to reconstruct the selected area.—useful for GLP
auditing.
§ Mark selection with events in graph—Automatically inserts a pair of Global Selection Begin and Selection
End events at the selection boundaries when pasting measurements or wave data. These events will be
timestamped with the time of day and the date when the paste occurred. This timestamp can be matched to the
result of “Include timestamp” to recreate selected areas for reconstructing measurement results or re-executing
wave data exporting—useful for GLP auditing.
Event Summary Preferences
For the event summary that can be pasted to the journal, choose a method to group the events (i.e., type or channel), to
sort the events (by time or label) and indicate whether to include all events or include only visible events in the
summary. There is also an option to include a header row at the top of the summary.
Access Event (Marker) preferences under Display > Preferences > Event summary; see page 225 for details.
Graph Preferences
§ Display Style can be set to Windowed or Tabbed view. Tabbed graphs can be navigated by clicking on the
identifying tab at the top of the application window, or by clicking Ctrl+Tab. A tabbed graph may be moved to
it’s own window by right-clicking on the desired graph and choosing “Move Tab to New Window” (below
right). The default setting for AcqKnowledge is tabbed view. When set to Windowed, multiple graphs appear as
separate windows, which can be positioned as desired.
o

Editing > Interpolate pastings instructs AcqKnowledge to interpolate/extrapolate time base
information when working with data sampled at two different rates. AcqKnowledge will interpolate
data to fit the sample rate of the destination window. When doing this, data should be copied to a
higher resolution window.
Maximum levels of undo—Set the maximum number of undo operations. Unlimited may be memoryintensive, depending on the detail of each operation.
Link selections between data views for new graphs – automatically synchronize selected areas of data views
between graphs for a new graph.
o

§
§
§
§
§
§

Enable cursor tools during acquisition – Allows access to cursor
tools while recording is in progress.
Show append boundary dividers – Controls visibility of append
event boundary dividers.
Axis controls – Controls visibility of set screen vertical axis controls.
Chart Track Divider Appearance –Users may change the color
used to draw the dividers between channels tracks The Preferences >
Graph panel contains "Chart Track Divider Appearance" options.
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§
§
§
§
§
§

Default uses operating system specific dividers, which is a light color.
Custom activates a colorwell for choosing a solid color to be specified for all dividers. The preference setting
and color are shared by all open graphs and data views, as this is an application-level preference.
Plotting Background Colors – Customizable background colors for active graph channels are also available.
Normal activates a colorwell for choosing background color of the non-selected channels.
Selected channel activates a colorwell for choosing background color of the selected channel.
When closing… determines the degree of closing and what prompts, if any, for multiple data views.

§

Recently Used—set the number of recently used Transform and Analysis options to list in the Transform >
Recently used sub-menu; provides quick access to common options. Recently used items can also be launched
using keystroke the combinations appearing in this menu.
Journal Preferences
The Journal Preferences dialog contains options controlling the format of data when it is pasted into the journal or
clipboard.
§ Change font type and size.
§ Wrap Journal text—Wraps text to window size.
§ Tabs: Specify the tab interval to make columns more readable when a high precision setting is set.
Auto-paste results—Toggle the checkbox to enable/disable the option to paste results to independent journals.
Display Style— Choose whether Journal window is fixed, dockable on any edge of graph, or independently floating.
Hardware Preferences
§ Always work with no data acquisition hardware connected sets the default communication for no connection
so the connection error is not displayed each time the software is launched.
§ Line frequency is specified during software installation and can be changed here. (50 Hz for Europe, 60 Hz for
the Americas.) Every time data is recorded, the line frequency setting is saved along with the data. If no line
frequency data was saved, the line frequency setting for the installed/active version of AcqKnowledge will be
used.
§ Default analog channel display units – Use to set default channel units to volts or millivolts.
· Volts – displays in Volt units, visible range +/-10V (MP160/150 default)
· mV – displays in Millivolt units, visible range +/- 50 mV (MP36 default)
§ Data Acquisition Hardware Priority launches a dialog allowing the default hardware device ordering to be
set. This ordering is used to establish hardware communication when the application is first launched or if none
of the previously-connected MP devices are available.
§ Restore data acquisition hardware configuration on launch – when checked, communication with the last
known hardware unit will be reestablished. When unchecked, the application will search for available new
hardware units.
§ When creating new graph windows use sets the default channel and hardware options for new graphs.
· Minimal channel setup – new graphs will use the application’s factory default channel settings for the selected
hardware.
· User-defined default channel setup – all new graphs are created with the user’s default settings. To remove
established default settings, click the “Clear Default Setup” button.
· Channel setup of last active graph – the settings of the most recently created active graph will be applied to all
new graphs.

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§ Use linked acquisitions whenever possible: Use this option to automatically set up linked acquisitions if
multiple hardware and multiple graphs are detected.
§ Merge data automatically: Automatically merges data from multiple acquisitions into a single graph using the
Resample and Data alignment options selected in the Preferences.
§ Resample merged data to:
· highest acquisition sample rate—merged graph data is upsampled to the highest selected sample rate among
the linked graphs.(Example, if one graph is being acquired at 500 s/s and the other 2000 s/s, the 500 s/s graph
will be upsampled to 2000 s/s.)
· lowest acquisition rate—merged graph data is downsampled to the lowest selected sample rate among the
linked graphs.(Example, if one graph is being acquired at 500 s/s and the other 2000 s/s, the 2000 s/s graph
will be downsampled to 500 s/s.)
If these preferences are not selected, linked acquisitions must be set up manually in the linked acquisitions
dialog (MP menu > Set Up Linked Acquisitions).
§ Auto-connect to BioNomadix Loggers will search for any BioNomadix Loggers that may be attached to the
computer and attempt to connect to the unit.
Performance Preferences
§ Use all available memory instructs AcqKnowledge to attempt to use all the available memory for loading data.
Otherwise, a variable sized buffer is used to load portions of large data files. This option works best if there is
enough free memory to load the entire data file.
§ CPU allocation sets the priority for CPU (system resource) allocation. For a data focus, move right, for a
function focus, move left.
· If buffer overloads occur, move indicator toward Better data transfer for high speed acquisition.
· To allow autoscale during acquisitions or jumping between hardware units, resizing displays, or working
in other programs, move toward More responsive.
Networking Preferences
Enable networking to allow applications running on other computers attached to the same network to gain access to
data from AcqKnowledge as it is being acquired. Data is sent to other applications over a network using TCP
(recommended) or UDP connection during acquisitions.
All channel types may be exported (analog, digital, and calculation) channels. AcqKnowledge will continue to
function normally while data transfer is in progress, displaying the new data in the graph window and performing any
autoscrolling.
Respond to auto-discovery—Toggle the checkbox to enable/disable response during network data transfer.
The network data transfer feature is not intended for strict real-time delivery. It also does not provide direct control
over the MP160/150 unit. Perform all hardware configurations manually using the AcqKnowledge interface.
Enable Remote Monitoring to allow acquisitions on the computer to be viewed remotely over a network through a
client/browser interface. Acquisitions can be started and stopped remotely and graph data viewed while recording is in
progress. This is handy if the AcqKnowledge computer recording the experiment is in one area and the researcher
monitoring the experiment is in another.
For applications that require low latencies, high-data throughput, or direct hardware configuration and control, use
BIOPAC Hardware API.
Other Preferences
§ Show menu tooltips enables display of tooltips describing menu item functions. Tooltips appear when menu
items are moused over.
§ Create Data Snapshots after acquisitions toggles the snapshot (embedded archive) feature, which stores
snapshots of original acquired data along with the graph file for easy comparison of results to original
waveforms or to intermediate stages of analysis; see page 51 for details.
IMPORTANT: Archive functions do not create a new file—they are not backup functions.
Original data is copied and pasted to the end of the original file.
This feature cannot be used to recover lost or damaged original data.
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When this Preference is enabled, a date-stamped archive of the data in the graph will be created each time the
acquisition is stopped. In Append mode, the entire graph is backed up with each Append, old data as well as the
newly acquired data.evt_.
§ Reset toolbar positions—Resets location of toolbars to default setting.
§ Create configuration file— Create default menu configuration file to customize menu display. See page 588
for customization details.
§ Maximum number of files in File > Open Recent—Sets the number of files that will appear in the ‘File >
Open Recent’ list.
§ When application is launched:—Chooses between display of Startup Wizard or a new empty graph following
application launch.
§ Default audio device—Use this option to select the default audio device to be used by the application.
Window Preferences
§ Always keep the following windows on top: — Sets options for keeping any of the following windows active
above the main application window: Input Values, Manual Control, Stimulator Control, Media Capture
Preview, Media Capture Viewer, Media Playback Viewer, Gauge View.
Focus Areas Preferences
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§
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X

Show background—Sets option for main graph visibility in the background of the selected focus area.
Color (background)—Sets background color of focus areas. Click color square to change color of focus area
background. (This option not active if “Show background” is unchecked.)
§ Opacity—Sets transparency level of background. (0 is transparent, 100 fully opaque.)
§ Show borders—When checked, borders will appear on both sides of the focus area.
§ Color (borders)—Click to change the color of focus area borders.
§ Width—Controls width of focus area borders.
§ Show Labels—Controls visibility of Focus Area labels. Labels can be shown or hidden.
§ Label Position—Controls where the Focus Area labels will appear in the graph. Options are at the top part of
the waveform or the bottom part of the waveform.
Location Preferences
§ Default Map Server – selects the map server used to display GPS tracking data in the Location Palette. The
available map servers are Nokia Ovi, Google Maps or Open Map.

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Video Capture Preferences
Video preferences are available in AcqKnowledge 5.0.3 and higher, and offer configuration/setup options for video
cameras and AVI compression. Click the Camera “Configure” button to launch the following dialog for setting frame
rate, compression, quality, output size and more.

Resetting All Preferences to Factory Default
All preferences can be reset to the default factory configuration by holding down the Shift key while launching
AcqKnowledge. The following prompt will appear:

It is important to note that accepting this option will reset ALL application defaults to the factory configuration.
Scroll options
The Scroll options help navigate through large data files. Right-click below
the horizontal scroll track to generate the contextual menu with scroll options.

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Size window...
The Size Window function is useful for setting exact dimensions
for the size of the graph window. Use this to create consistently
sized windows for pasting into documents. The two text box fields
are used to enter interior screen width and height, both of which are
scaled in terms of pixels.

Each operating system may add additional dimensions as necessary to put in window adornments depending on the
appearance configuration preference of the user (e.g. extra space for title bar of the window, any additional space put
around the edges of the window frame, etc.).
When the Reset chart boundaries box is checked, the boundaries between the waveforms will be reset so that each
channel “track” is the same size.
When Use as default for new windows is checked, the user-modified dimensions are applied as the default graph
window size.
When “Retain current dialog settings” is checked, the dimensions used when the dialog was previously dismissed are
applied to all subsequent graphs.
Cursor Style

This option allows the active cursor tool to be adjusted via the Display menu.
Create Data View
Creates a new Data View for the active (frontmost) graph and names the new window “Data View of ‘Filename’” For
Data View details, see page 41.
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Create Focus Area
This option becomes available only when an area of data is selected, and brings up a Focus Area naming dialog. For
full details on using the Focus Area feature, see page 92.
Organize Data Snapshots
Arrange data snapshots (as created via Edit > Create Data Snapshot).

Show All Data Snapshots
1
2
3
1
2
3

Manual Archive: description and time
Original file
Auto-Archive: time only

To view the embedded snapshot(s)/archive(s) associated with a graph file, choose Display > Show Original Data/All
Data Snapshots. This will open a new graph window for each archive/snapshot associated with the graph. The time
portion of the Filename for each graph is from the computer clock (saved with semi-colons because a file with colons
in the filename cannot be saved). The “Snapshot from…” graph will open with no Start button.
Each embedded archive is essentially a “snapshot” of the original acquired data that is stored with the graph file so the
archive can be viewed at a later time to compare results to original waveforms or intermediate stages of analysis.
Append events are not preserved in the snapshot/embedded archive file. For details on creating snapshots/embedded
archives, see page 51.
Load All Data Into Memory
Use with large files to improve plotting performance, measurement response, etc. Memory can hold up to two
gigabytes of data.
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Chapter 19

Program & OS Menus

AcqKnowledge menu
Mac OS only—System generated menu. Use for Quit and Preferences. (Quit
can also be found in the File menu.)

Window menu
The Window menu is a standard OS
function. See Windows or Macintosh OS
Guide for details.
Bring All to Front
If other programs are running, this
command will bring all AcqKnowledge
windows to the front (on top of all other
application windows); this command does
not change the windows size or position.
Additional options become available
when the Tabbed graph display preference
is selected. (Right figure)
Help menu
Use the User Support System pdf files for online help with the software.
Selecting “About AcqKnowledge” from the Help menu generates a dialog
that providing information about the AcqKnowledge software being used
and system parameters, which can be useful when contacting Technical
Support.
Note: For information about the MP160/150 data acquisition unit and
firmware, click MP160/150 menu >MP160/150 Info.

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Click the System Info button for more detailed information.

The Copy to clipboard button makes it easy to paste system info into an
email for Technical Support.

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Chapter 20

Media Menu

Also applicable to multi-camera systems and CAM-HFR-A high-speed camera. For Media Menu setup for CAMHFR-A, see page 482.
Media functionality allows users to capture and playback video and/or audio with a USB web cam or firewire DV
device and synchronize it with physiological information from an hardware device. The key functionality is a strong
link between the video and data cursor when graphs are being used in post-acquisition mode; changing the selection in
the graph window will automatically jump the video to the time corresponding to the cursor position. The reverse tie
is also in place where scrolling the video will move the data cursor to the corresponding data point in the graph.
For synchronized playback of media player with AcqKnowledge cursor in data view, BIOPAC recommends that the
users sample the hardware unit at least as fast as the video frame rate 30Hz. In this case, any measurement errors are
limited to the basic frame rate error window (1/30 sec). For exact match of Video and Data samples, BIOPAC
recommends frame rate 25 fps and acquisition rate 25 samples/second (or its derivatives).
Set Up

Establish Sources, Output and Media parameters. Set device type for audio and or/video.
Use refresh after connecting a new device to make it a selectable option. Browse using
standard file open/save functionality to specify media files. If desired, set a Delay between
file segments.

Show Capture Viewer

Use for video signal directly from a video camera; this option is disabled (grayed) in the
record mode when both the Capture video and Capture audio options in the Media Setup
dialog are off.

Show Playback Viewer Use to play back media from the disk (stored media files); this option is disabled (grayed) if
there is no media assigned to the file.
Sync SMI Video

This feature is used specifically for synchronizing video exported from SMI BeGaze eye
tracking software. The SMI video is synced by using timestamp information extracted from
the exported BeGaze data file. For more information about SMI Begaze Import/Export, see
page 272.
Video Playback and Capture preview include a right-mouse contextual menu item “Grab bitmap” which, when
selected, generates a Save As dialog to save the current displayed frame as a *.bmp image.
Media Notes
:: Media capture performance is improved under Windows 8 and 7 OS. If the selected webcam drops frames
because of poor performance/low quality, the degree of synchronization will be compromised. Testing
indicated the Microsoft Lifecam NX-3000 gave reliable performance with no dropped frames.
::

Several AcqKnowledge files can point (link) to the one media file.

:: AcqKnowledge files can link to media files created by other programs. If the media file is shorter or longer
than the AcqKnowledge files, just align the two files at the start.
:: AcqKnowledge files alignment precision with the media file is user-controlled through the use of a delay
function that allows a forward or backward time shift.
:: AcqKnowledge files store the location (path) of the media file. This path is editable, so the AcqKnowledge
file can link to other media files too.
::

Media functionality does not support the Autosave file acquisition mode.

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:: Using the “Reset” function on appended acquisitions does not delete any previously recorded Media
segments.

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Synchronization Tip
To optimize synchronized playback of the media and the physiological record, use the OUT103 LED to determine the
delay between the media and the data. The LED must be in view of the video camera and the LED channel must be
recorded.
MP160 Media synchronization - Windows only
Option 1: MP160 and UIM100C setup using an Analog Output
a. Connect the OUT103's 3.5 mm phone plug from the LED to one of the arms of the included Y-cable.
b. Connect the included CBL100 to the other arm of the Y-cable.
c. Connect the stem of the Y-cable to a CBL122 connected to one of the two Analog Output connections on the
front face of the HLT100C.
d. Connect the other end of the CBL100 to a CBL122 connected to an otherwise unused Analog Channel also on
the front face of the HLT100C.
e. Use "MP160 > Set Up Channels..." (in AcqKnowledge, choose "Channels" in the left pane after choosing
"MP160 > Set Up Data Acquisition...") and acquire and plot the analog channel to which the CBL100 is
connected.
f. Use "MP160 > Set Up Stimulator..." (in AcqKnowledge, choose "Stimulator" in the left pane after choosing
"MP160 > Set Up Data Acquisition...") to send 5 volt pulses through the Analog Output.
MP150 Media synchronization - Windows only
Option 1: MP150 and UIM100C setup using an Analog Output
g. Connect the OUT103's 3.5 mm phone plug from the LED to one of the arms of the included Y-cable.
h. Connect the included CBL100 to the other arm of the Y-cable.
i. Connect the stem of the Y-cable to one of the two Analog Output connections near the bottom of the front
face of the UIM100C.
j. Connect the other end of the CBL100 to an otherwise unused Analog Channel also on the front face of the
UIM100C.
k. Use "MP160/150 > Set Up Channels..." (in AcqKnowledge, choose "Channels" in the left pane after choosing
"MP160/150 > Set Up Data Acquisition...") and acquire and plot the analog channel to which the CBL100 is
connected.
l. Use "MP160/150 > Set Up Stimulator..." (in AcqKnowledge, choose "Stimulator" in the left pane after
choosing "MP160/150 > Set Up Data Acquisition...") to send 5 volt pulses through the Analog Output.
MP36R setup - additional items required
a. Connect an OUT3 (BNC adapter) to the 'Analog Out' port on the rear of the MP36R.
b. Connect a BSLCBL6 (interface cable: BNC to 3.5 mm) to the OUT3.
c. Connect the OUT103 3.5 mm plug to the BSLCBL6 3.5 mm socket.
d. Set MP36 > Output Control 'Low Voltage Stim' option
- set Pulse width to 100 msec
- set Pulse level to 5 Volts
- set Reference Channel to any digital channel
- click the 'ON' button to output a digital pulse
·

Once the LED has illuminated and the square wave in the file is visible, the channel can be hidden.

·

After the recording is complete, use the I-beam selection tool to measure the offset between the LED
illumination and the leading edge of the digital impulse. Use a Delta T measurement to determine the
delay information; Delay may be positive or negative based on camera performance. Delay should be
entered in the Linked Media row for each segment—see page 480.

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Media > Set Up
Source
Use this dialog to select media source and select audio and video to record. Click Refresh to update the list if a
video or audio device is connected after the dialog was opened. When video/audio for capture is selected, an
output file must also be selected. Input file name and click OK; this will close the Media Setup dialog and
automatically open the media window if the Capture option is ON.
All video camera, audio (microphone) input parameters can be setup by user with the UI provided by camera
manufacturer, or use the “Configure” button for direct access to camera properties, such as exposure, saturation,
contrast, white balance, etc.

Output
Video/audio capture requires a media file specified with full name with disk location. *.avi or *.wmv file formats
are supported. Users can save AcqKnowledge data and media streams onto separate hard drives.

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Linked Media
IMPORTANT

An AcqKnowledge data file must be opened before linking to a media clip.

If media was captured with the data file, the Linked Media dialog will display a row for each appended
segment in the AcqKnowledge data file and will list the file location of the corresponding media for each segment.
The samples above show four AcqKnowledge data segments and four linked media Files.
Click anywhere in the row (or choose the Edit button) to set a delay to synchronize the media file with the
physiological data. Delay range: Min= 1 millisecond, Max = segment duration.
§ See Synchronization Tip on page 478.
If media was not captured with the data file, click the appropriate row and click “Link” to browse to the
desired media file from that segment.
Delay—Each segment can have a distinct delay. Click in the Delay
cell or click Edit to generate the dialog for Delay entry.
“+” Delay places start of video file after graph start
“-” Delay places start of video file before graph start
The best possible synchronization can’t be better than the video frame rate (usually 1/30 of a second).
Media > Capture
Use Set Up to assign a Source and Output to enable the Capture menu option. There are no Preview window
controls and the size reflects default video camera resolution.
Playback Preview
As the media file is manually scrolled or automatically played, the AcqKnowledge cursor keeps moving to reflect
the corresponding location in the AcqKnowledge graph. If the AcqKnowledge cursor is moved, the media file is
automatically scrolled to keep time sync with the data file.
Media files linked to appended data segments are loaded in sequential order. After playback of the first media
segment, the cursor will automatically advance to a still-frame view marking the beginning of the next segment.
The Play button must be pressed in order to play back subsequent segments.
Audio Mute button and level slider
Video Digital indicator (time in milliseconds or frame number for the segment clip) and Horizontal slider
(progress bar) to navigate the media file. The start point can be set from either the media clip or the data
file. For precise selection, hold the shift key and use the forward or backward arrow keys on the media
player or the keyboard to move single video frame (mostly 1/30 seconds) or data point.
Use the scroll bar to navigate to different frames. Synchronization should be maintained with data in the graph
window. This should result in a single sample selection cursor shown at the time closest to the displayed video
frame.
The media window displays the text “No media assigned” in Playback Preview when the media window is visible
but there is no video/audio file assignment for given data segment.
During the capture or playback of audio only, the media window will be displayed with a static
musical note image as shown at right.

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The Playback viewer uses standard media player controls.
Go to previous segment / go to beginning of
segment
Step backward a frame/sample
Fast backward / reverse rewind
Play/ pause
Fast forward
Step forward a frame/sample
Go to following segment
Mute sound
Media Playback Example
1. Launch AcqKnowledge.
2. Open a saved acquisition file.

3. Select Media > Show Playback Viewer.
4. Experiment with the following options:
§ Select I-beam cursor on graph and push
“Play” button on the player.
§ Change selection with I-beam on graph
and see the video.

IF media is not assigned, locate the video clip
for the appropriate segment:
a.) Select Media > Set Up
b.) Select the “Linked Media” tab
c.) Select Segment 1 and click “Edit.
d.) Click “Link” and select a saved media
file.

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Media Capture Setup with CAM-HFR-A High Speed Camera
The CAM-HFR-A is a high speed camera capable of capturing more precise video at rates up to 100 frames-persecond. AcqKnowledge versions 4.3.1 and higher support use of this camera. The Media setup procedure differs from
that of a standard USB camera, with the AcqKnowledge Stimulator providing a “sync pulse” between the MP160/150
and the camera. Therefore, no manual synchronization procedure is required. The following pages describe hardware
and software setup for the CAM-HFR-A.

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A. Connect Camera Hardware:
Before beginning:
Make sure the camera drivers and the provided ETHCARD3 Network Interface Card are installed on computer.
1. Connect the CBLHFR 6-pin-connector to the camera input.
2. Connect the female end of the CBLHFR connector to the AC300A power supply adapter cable.
3. MP160: Connect the CBLHFR Trigger Cable to a CBL122 RJ11 adapter and plug into an HLT100C Analog
Output. For MP150, connect the CBLHFR Trigger Cable to the UIM100C Analog Output.
4. Plug the AC300A power supply cord into wall socket.
5. Connect the Ethernet cable between the camera’s Ethernet port and the ETHCARD3 network interface card
supplied with the system. Attach the 6 mm lens to camera (included as LENS-CAM-A).
6. Launch the pylon IP Configuration Tool from the Desktop shortcut to verify camera/network connection. If
successful, the camera’s network settings will appear in the IP configuration window as shown below. (Make
sure the IP configuration is set to DHCP.)

NOTE: If the camera’s network settings don’t appear in the pylon IP Tool Configuration window, click the
“Refresh” button and highlight the camera device from the list at the top of the Configuration Tool.
If the camera’s network settings still don’t appear, or appear in the pylon IP Configuration Tool window
as “unreachable,” reset the IP configuration to Static IP.

B. Set Up Camera Configuration in AcqKnowledge Software:
1. Launch AcqKnowledge and select Media >
Set Up. The Basler camera should appear as
selected in the “Video” list.
2. Check the “Video” option (and “Audio” if
sound is to be recorded).

3. Click the “Output” tab and type in a media file
name.
4. Click “Browse” and choose a format** (*.wmv
or *.avi) and directory for the new media file.
5. Click “Save.”

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6. Click “OK” to bring up the Video Capture
Viewer. This is useful for determining proper
camera positioning, lighting, etc.
7. To access the “Video” properties (Exposure
or Gain controls), go to Media > Set Up and
click the “Configure” button.
NOTE: The “Configure” button is not active
until the Media > Set Up dialog is
dismissed with “OK” and reopened.

8. Click the “HW Trigger” tab to:
·

Use the MP160/150 Stimulator to
trigger and synchronize the camera
recording with AcqKnowledge data
collection.

·

Set the camera frame rate (25, 50, or
100 fps).

**Dropped frames while recording in *.avi format are an indication that the computer may lack sufficient
resources to support this larger-scale format. If this occurs, it’s advisable to use *.wmv format instead.
NOTE: The CAM-HFR-A can link with only one graph at a time. A previous graph must be closed prior to connecting to a
second graph, or a conflict error message will result.
For camera specifications, see the CAM-HFR-A Product Sheet or the BIOPAC Hardware Guide.
Watch the AcqKnowledge CAM-HFR-A video tutorial for a detailed demonstration of this feature.

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Part D — Licensed Functionalities
AcqKnowledge Licensed Functionalities consist of powerful optional features not included in the standard
AcqKnowledge installation. These features become available with the purchase of an enhanced licensing level, and
can be purchased individually or in a bundle at any time and added to an existing installation.
Access to the licensed features is enabled by a USB License Key provided by BIOPAC, and the USB key must be
connected in order for the licenses to be active. With the license key connected, information about the available
licenses can be found by going to Help > About and clicking the “Licensed Features” button.

The following chapters offer an overview of the various licensed features available from BIOPAC.

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Chapter 21

Licensed Functionality: Network Data Transfer

Network Data Transfer (NDT) functionality is available through an optional license available with
AcqKnowledge 5. The license must be authorized to access NDT functionality. To add an NDT license to an
existing MP System, please contact BIOPAC.
Network Data Transfer (NDT) is a real-time data transfer system that allows access to the data being acquired into a
graph by AcqKnowledge for use in an external application; the AcqKnowledge process and the custom application
may run on the same computer.
Make TCP or UDP connections to external applications and stream binary data during acquisitions. Network Data
Transfer is supported in MP160 or MP150 hardware only.
The NDT license
§

allows Network Data Transfer functionality

§

links the Network Data Transfer Reference under Help

§

includes network data transfer Preferences

Most of the settings for the network data transfer functionality are set by clients through control connections. Several
settings for the AcqKnowledge server may be set directly in the AcqKnowledge preferences. Versions of
AcqKnowledge that include network data transfer functionality have an additional "Network" group of settings
underneath their Preferences. These Preferences are accessed from the Display menu ( Windows 8, 7/Vista) or from
the AcqKnowledge menu (Mac OS):

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NDT is a basic method for allowing third party applications to tap into the data stream being generated by both the
MP unit and AcqKnowledge during data acquisitions. NDT provides
§

networking facilities that allow for integration into a distributed application environment

§

basic control facilities to allow external applications to query and control the AcqKnowledge application state.

The NDT system is split into two separate types of connections: data connections and the control connection.
A. Data connections deliver data from AcqKnowledge to external applications during acquisitions.
B. Control connections are made from external applications to AcqKnowledge to query application state and

adjust data connections.
The server refers to the AcqKnowledge process and the computer on which it is running. The client refers to the
custom application that is to receive data from AcqKnowledge and the computer on which it is running.
All connections should be made using standard network protocols, either TCP or UDP. Single system image
architectures should make connections using the loopback interface. It is assumed that network implementations have
appropriate IP networks in place with routing between machines that can be identified either by IP address or by
hostname. Firewalls must be properly configured to allow network communications between the client and server.
Appropriate network configuration is the user’s responsibility.
Data Connections
Data connections are used to deliver data from the AcqKnowledge server to the client application. Data connections
stream both data acquired from an MP unit and computed data from AcqKnowledge calculation channels. Data
connections are available in a variety of formats and can be configured to meet the needs of the client application and
bandwidth requirements.
Data connections are created only at the start of acquisitions. It is not possible to “attach” to data acquisitions that are
already in progress.
XML-RPC calls for retrieving data are also described in this section. These connections are not persistent and not
established from server to client, but rather a request made from client to server. The recommended mode of operation
is regular TCP or UDP operation.
Variable Sampling Rates
AcqKnowledge uses variable sampling rates that allow different channels of data to be acquired at different sample
rates. This allows fast moving signals (such as EMG) to be acquired at high sampling rates while simultaneously
recording slow moving signals (such as respiration) at lower sampling rates. The primary use of variable sampling
rate is to optimize storage requirements by minimizing space spent retaining slow moving data.
In addition to the storage optimizations, variable sampling rates are also used to optimize data connections. Channels
that are sampled at lower rates require less network bandwidth to transfer from client to server. If channels of data
cannot be disabled and overall bandwidth is limited, variable sampling rate can be used to lower the bandwidth
required to move data between the server and the client.
The use of variable sampling rates requires the client to be aware of downsampled channels and handle data
accordingly. Variable sampling rate may also affect the interpretation of the incoming data connection stream, as
indicated below.
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Transfer Types
Clients may choose between two different transfer types:
§

single connection uses one data connection between the server and the client to deliver all data

§

multiple connection uses multiple data connections delivering data simultaneously

Single Connection
The single connection transfer type uses a solitary connection between the server and the client to deliver data. When
multiple channels of data are being delivered, all data is sent over the single connection in an interleaved format.
The interleaved format mingles the data of all channels in order. For example, an interleaved representation of two
samples from three channels of data would be: C1 C2 C3 C1 C2 C3. This is equivalent to two sample frames where a
frame contains the data at a particular sample location for all of the channels, in this case “C1 C2 C3.” Frames are
delivered sequentially over the data connection.
The single connection transfer type allows for all data to be processed from a single location and uses only one
network connection resource. Single connection transfer has drawbacks including the need for the client to demux the
data stream as well as account for variable sampling rates.
Variable Sample Rate Considerations
When variable sampling rate is being used, the single connection transfer type has the characteristic where not
all frames have the same size. If a frame occurs at a sample position where a channel is not being sampled,
that channel will not be included in the frame.
All downsampling within the AcqKnowledge variable sampling rate environment occurs at integer divisions
of the base sampling rate. Only frames with indexes (zero-based) that are evenly divisible by the
downsampling divider will contain data for that channel.
It is the responsibility of the client to compute and retain the frame index and to properly check
channel dividers against the frame index to determine which channels are represented in that
frame.
Frame 0 always contains a data point from every channel.
For example, consider a three channel acquisition. Channels 1 and 3 have a downsampling divider of 1, that
is, they are being acquired at full speed. Channel 2 has a downsampling divider of 2, that is, channel 2 is
being acquired at half speed. The first five frames of data in the single connection transfer type will appear as
follows:
C1 C2 C3 | C1 C3 | C1 C2 C3 | C1 C3 | C1 C2 C3
Note how frames 1 and 3 are shorter as they occur at positions where channel two is not defined.
If variable sampling rate is being used, clients are required to perform proper frame indexing in order to
demux the interleaved data stream. If clients cannot handle variable sampling rate correctly and are using the
single stream transfer type, clients should check all of the downsampling dividers using the control
connection to AcqKnowledge and warn the user if the configuration cannot be supported with that client.
Multiple Connection
The multiple connection transfer type uses a single connection from server to client for each channel of data that is
being delivered. Using multiple connections offers the benefit of avoiding the client having the need to demux all of
the data from each sample. If the client is operating in a high-load environment, the elimination of the demuxing may
be useful in reducing processor overhead. It also allows client code to be simpler if variable sampling rate is being
used.
The primary disadvantages of using the multiple connection transfer type are the usage of more network ports and the
client assuming responsibility for synchronization of data across multiple channels. The data immediately available on
one network connection may not be guaranteed to be the identical sample index of data being received for another

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channel. The client must keep track of sample index on an individual channel basis to properly synchronize data
across multiple channels.
Variable Sampling Rate Considerations
Using variable sampling rate in a multiple connection transfer type is significantly easier. Each individual
channel's connection delivers data at that channel's sampling rate. On a given connection, all samples have an
identical length.
Clients still must be aware of variable sampling rates. The sampling rate of information on a downsampled
channel connection is different than the sampling rate of information on an upsampled channel connection. If
the client is performing any time domain measurements or other computations involving the sample interval,
the difference in inter-sample-interval must still be taken into account.
XML-RPC
The XML-RPC transfer type allows clients to explicitly request data from the server. Instead of data being
automatically pushed to clients, the client must post an XML-RPC function call to the server. This allows the
client to query the server for the most recently acquired data sample value for a particular channel. Clients
that do not require continual data streams or interact with only slow moving data may wish to use this method
communication method. This method returns values only; no information about sample indexes or lengths is
returned.
XML-RPC has significant overhead for both client and server, so this transport method cannot handle more
than a few requests per second. If faster response time is required, the client should implement either the
single connection or multiple connection streaming methods.
XML-RPC is not a true data connection as it does not involve the server constructing a streaming connection
to the client.
Transport Protocol
Data connections offer a choice of using either TCP or UDP as the transport protocol for delivering data to the client.
Choice of protocol depends on application requirements. When a client is receiving data, it is assumed that all data
connections are using the same transport protocol.
TCP/IP
TCP is the preferred transport protocol. As TCP guarantees reliable, ordered delivery, all data is simply transferred
from the server to the client without any additional information. Data is streamed continuously as it becomes
available. TCP is recommended for all clients that require a guarantee of receiving all information. It is also
recommended for any configuration using up to two computers. The port number used for data connections is
specified by the client using the control connection prior to the start of acquisition. Once a client passes along port
information, the client should begin listening for connections on that port.
When using TCP data connections, the start of acquisition is signaled to clients by the establishment of a connection
on an appropriate port to the client. The end of an acquisition is signaled by the termination of the connection.
UDP
UDP is a connectionless protocol that does not guarantee either delivery or properly ordered reception of packets by
clients. Data connection is allowed to be switched to UDP delivery mode. The primary benefit of using UDP
datagrams is that a single data stream can be multicast to a number of computers. Multicasting is not offered
implicitly by the AcqKnowledge data connection protocol but can be achieved implicitly by requesting a data
connection be bound to a broadcast address.
UDP delivery used fixed size datagrams. The default size is 512 bytes. Clients can modify this size to any fixed
number of bytes prior to the start of acquisitions. The UDP packet size is stored in the template and is different for
each graph. UDP clients that require a specific packet size should set that packet size prior to the start of
each acquisition.

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Each datagram will contain the following:
Field
Starting sample
index

Data Type
unsigned long
(four bytes,
network order)

Offset

Description

0 byte

This indicates the starting sample position of the first sample of data
contained in the packet. This number is always monotonically
increasing and can be used to reassemble datagrams that are received
out of order.
This field is always stored in network order. Usage of htonl()/ntohl()
should convert from network order into host endian.

Length of data
section in bytes

unsigned long

4 bytes

(four bytes,
network order)

Total number of bytes in the data section. Data is sent by
AcqKnowledge as it is available, so not all data packets will contain
the same amount of data.
This field is always stored in network order. Usage of htonl()/ntohl()
should convert from network order into host endian.

Data section

(type and
8 bytes
endian specified
by client)

Data section containing the binary data that was acquired. The data is
converted into the appropriate data as configured by the client.

All of the data delivery is performed as data is available from the MP unit. The actual size of the data section in
packets that get delivered to the client is dependent on the speed of data acquisition and other activity on the host
computer. If variable sampling rates are being used, frames will not be split up. All of the data for the final frame is
contained in the UDP packet. If a frame will not fit in the amount of space in a packet, it is sent in the next packet.
There are no provisions for clients to request retransmissions of packets from the server. Clients should be aware that
data may not be delivered when using UDP and should be prepared to examine sample indexes at the beginning of
each packet and handle missing data accordingly (padding, warning user, etc.).
The port on which datagrams is delivered is specified by the client prior to the beginning of acquisition on the control
connection. Once the client specifies its port, it should begin listening for datagrams delivered to that port. The start of
acquisition is signaled by the first datagram that is sent to that port. The sample index of the first datagram
corresponds to the first hardware sample of data acquired by AcqKnowledge. If the graph is initially empty, the index
is zero.
Unlike TCP connections which get explicitly disconnected at the end of acquisitions, there is no direct messaging for
UDP delivery indicating the end of acquisitions. Datagrams will not be sent to the client after the end of acquisition.
Clients requiring explicit termination notification should either use TCP or implement a timeout mechanism combined
with an XML-RPC getAcquisitionInProgress call on the control connection to locate the end of acquisitions.
XML-RPC
The XML-RPC “get most recent data sample” call will use standard XML-RPC connection semantics involving the
client making an HTTP POST request to the server and interpreting the response as appropriate. Handling of XMLRPC can be performed by a library in the client's appropriate implementation language.
Real-time Delivery Guarantees
No delivery time guarantees exist for any data connection. Data is delivered to the client as it becomes available. The
overall latency of the system from physical sample time to data delivery is dependent on a number of factors
including network load, AcqKnowledge overhead (which is variable due to calculation channel processing time, user
interface activity, thread scheduling, and other operations), system load, and other factors. The actual sampled data
itself is guaranteed to be accurate; the sample time of a signal acquired into the hardware unit is always accurate.

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It is only the time between the physical time corresponding to a sample and its delivery to the client application that is
variable.
Clients that require strict real time guarantees or more predictable latencies should investigate using the hardware API
on their local machine.
Data Formats
It is assumed that the data transfer feature is used in a mixed host environment, potentially with clients running in
environments that have restricted data types. The sampled information delivered by a data connection is allowed to be
controlled to appear in a variety of different formats for the client:
l

64 bit floating point – This format will always be available for all channels and may be delivered in either big
endian byte order or little endian byte order. This is equivalent to a C style double data type.

l

32 bit floating point – This format will always be available for all channels and may be delivered in either big
endian byte order or little endian byte order. This data type is not native to AcqKnowledge, so the precision of
received data may differ from data as recorded by AcqKnowledge. This is equivalent to a C style float data
type.

l

Signed 16 bit integer – This format is available only for analog data channels. It may be delivered in either big
endian byte order or little endian byte order. This is equivalent to a C style short data type. Clients receiving
data in 16 bit integer format should use the control connection to determine appropriate floating point scaling
factors that need to be applied to the data to convert into actual units.

Data formats should be specified by the client prior to the start of acquisition. If left unspecified, the default data
format depends on channel type:
Channel Type

Default Data Type

Analog

16 bit signed integer, little endian

Digital

16 bit signed integer, little endian

Calculation

64 bit floating point, little endian

XML-RPC get most recent sample requests will always return the double type of XML-RPC (in ASCII notation).
Default Data Connection Settings
If the client does not modify any data connection settings, the following is used:
l

Single connection transfer type

l

TCP/IP transport protocol

l

Port 15020 for single connection

l

For multiple connections, each channel type (16 channels per type) is set as follows: analog channels [1502015035], digital channels [15040-15055], calculation channels [15060-15075].

l

Default data formats for each channel type as indicated in the “Data Formats” section

Note that no channels are enabled for delivery by default. Both data connection delivery and get most recent sample
tracking are disabled. Clients will still need to enable channels in order to receive data.

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Locating AcqKnowledge Servers
It is possible that clients and servers may be located on networks with dynamic IP addresses or other features that
make establishing the connection between machines difficult. In this case, a simple UDP broadcast mechanism can be
used to locate known servers.
AcqKnowledge will listen for incoming UDP packets on port 15012. If the UDP packet contains the sequence of
ASCII characters “AcqP Client” and only that sequence, it will send a broadcast packet containing “AcqP Server
Port:” followed by the port number on which the server is listening for control connections. The port number is
expressed in base 10 ASCII notation.
It is possible to configure AcqKnowledge to not acknowledge discovery requests for security purposes.
Control Connections
Clients connect to an AcqKnowledge server using control connections. A control connection allows the client process
to control how data is going to be delivered to it, query settings, modify settings, and perform other basic operations
without requiring graphical interaction with the AcqKnowledge environment.
On the start of an acquisition, all data connections are established to the client that most recently established a control
connection unless the client has modified the destination by using the changeDataConnectionHostname command.
It is possible to configure AcqKnowledge to not respond to any control connections for security purposes.
The majority of all control connections use XML-RPC. The XML-RPC specification can be located at
http://www.xmlrpc.com/spec. XML-RPC consists of an HTTP POST request being assembled by the client along
with data content expressed in the XML-RPC notation. The remote procedure call will then return with an appropriate
response to the caller. By design, XML-RPC is client and platform agnostic.
XML-RPC implementations exist for a number of languages. If there is no implementation in the client's language,
hardcoded requests can be embedded or a small helper application or shared library can assist in providing the control
connection interface.
The URI that should be used when connecting to the server is the recommended “/RPC2” for XML-RPC. For
example, a URL for localhost control connections would be “http://localhost/RPC2.”
TCP Port
Only one control connection may be opened by a client to a server at a time. The server will listen on port 15010 by
default. As this port may conflict with other network services or may need to be modified for firewall accessibility,
AcqKnowledge will allow the server port to be modified by the user in the Display > Preferences panel. Clients should
be aware that control connection port numbers are not fixed and should either allow users to change the port number
from the client or use the dynamic discovery mechanism for locating AcqKnowledge servers.
Control Procedure Calls
Control procedure calls are remote procedure calls with a set method name and response. All method names and
strings are case sensitive. The available control calls are roughly split up into querying acquisition parameters,
configuring data delivery, and limited calls for modifying acquisition parameters and affecting application state.
Channel Index Parameter Structures
Some procedure calls take a channel index structure as a parameter. This is an XML-RPC structure that consists of
the channel type and index. The channel type is a string member named “type” that is one of the following strings:
analog, digital, calc. The channel index is an integer member named “index” and contains a zero-based index
indicating the channel. For example, the following channel index parameter structure can be used to refer to calc
channel 2 (recall, in AcqKnowledge calc channels are indexed from zero):


type
calc

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index
2


Querying Acquisition Parameters
The calls for querying acquisition parameters are intended to allow clients to request information required for them to
fill out appropriate parameters and to verify that previous control requests have been properly applied. The following
control calls are recognized:
getMPUnitType
Method name: acq.getMPUnitType
Parameters: None
Return value: int
Retrieves the type of MP unit to which the server is connected. This may be zero (indicating no unit is
connected, e.g. “No Hardware” mode), 160/150 (for MP160/150), or 36 (for MP36R).
The client can use this value to decide between appropriate templates to download or other channel settings.
getEnabledChannels
Method name: acq.getEnabledChannels
Parameters: string
Return value: array populated with int
Retrieves the channels that are available for acquisition and data delivery over a data connection to the client.
The type of channels that are to be returned are specified in the string parameter. The string parameter may be one of
the following: analog, digital, calc. The type must be lowercase. “analog” returns information about analog channels,
“digital” digital channels, “calc” calculation channels.
The enabled channels are returned as an array of channel indexes, zero-based. These are the indexes that can
be validly used in calls for configuring data connection parameters.
getChannelScaling
Method name: acq.getChannelScaling
Parameters: channel index parameter structure
Return value: struct containing scaling
For channels that can be delivered in short integer format, the channel scaling provides the scale factor and
offset used to convert the short into physical units using the formula: sample*scale+offset. The scaling is returned as a
structure containing two double-valued members: “scale” contains the multiplication factor, “offset” contains the
offset factor.
Channels that cannot be delivered as short integers cannot be scaled. If this method is called with an invalid
type of channel, a fault response is returned.
getSamplingRate
Method name: acq.getSamplingRate
Parameters: None
Return value: double
Returns the current sampling rate expressed in Hz. This is the rate at which data is sampled for a channel
whose downsampling divider is 1.
getDownsamplingDivider
Method name: acq.getDownsamplingDivider
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Parameters: channel index parameter structure
Return value: int
Retrieves the downsampling divider for a particular channel. A channel is sampled at the base sampling rate
divided by this factor. This factor is also used to determine which frames contain samples for this channel.
Data Connection Configuration Commands
While it is possible to configure data connection parameters using AcqKnowledge, frequently clients may need to
alter data connection configurations based upon dynamic information regarding the machine on which they are
running (e.g. port collisions with other services, unexpected endian changes, etc.). The following commands may be
used to configure how data is delivered to the application.
getDataConnectionMethod
Method name: acq.getDataConnectionMethod
Parameters: none
Return value: string
Returns the method currently being used for data connections between the server and client. The string value
is either: single, multiple. “single” corresponds to a single data connection being made between the server and the
client with all data interleaved over that connection. “multiple” corresponds to opening an individual connection to
the client for each channel.
changeDataConnectionMethod
Method name: acq.changeDataConnectionMethod
Parameters: string
Return value: 0 on success, or fault code
Changes the method used to deliver data to the client. The parameter is a string that is one of the following:
single, multiple. “single” opens up a single data connection and sends data in an interleaved fashion. “multiple” opens
up an individual data connection for each channel.
getDataConnectionHostname
Method name: acq.getDataConnectionHostname
Parameters: none
Return value: string
Returns the currently set hostname for data connections. When data connections are established on the start of
acquisition, the IP address associated with this hostname is sent the data. Hostnames must properly resolve in order
for data connections to be made; DNS configuration is outside of the scope of the network data transfer feature.
If this hostname is empty, data connections is made to the most recently connected client application. This is
the default setting.
Hostnames are unique on a graph by graph basis and are saved in templates and graph files. Clients
redirecting data to another machine should check and set the data connection hostname as appropriate prior to the start
of acquisition.
changeDataConnectionHostname
Method name: acq.changeDataConnectionHostname
Parameters: string
Return value: 0 on success, fault on error
Changes the destination machine for data connections, the recipient of the network delivered data. If the
parameter is an empty string, data connections will automatically be made to the most recently connected client. The
empty setting is the default.

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If non-numeric hostnames are specified as parameters, they must be resolvable. If a hostname cannot be
resolved, a fault is returned. Proper DNS configuration of the server is beyond the scope of the network data transfer
feature.
getTransportType
Method name: acq.getTransportType
Parameters: None
Return value: string
Retrieves the transport type that is being used to deliver data from the server to the client. The transport type
is a string that is one of the following: tcp, udp. Note that the XML-RPC data delivery method may be used in
addition to this transport type if channels are enabled.
changeTransportType
Method name: acq.changeTransportType
Parameters: string
Return value: 0 if successful, else fault code
Change the transport type that is used to deliver data from the server to the client. The transport type is a
string that has one of the following values: tcp, udp. XML-RPC last value data delivery may be used in addition to
this type provided channels are enabled properly.
getUDPPacketSize
Method name: acq.getUDPPacketSize
Parameters: None
Return value: int
Returns the current size in bytes of UDP packets that is delivered to clients. Datagrams are always this fixed
byte length although each individual datagram may contain varying amounts of data.
setUDPPacketSize
Method name: acq.setUDPPacketSize
Parameters: int
Return value: 0 on success, fault on error
Changes the size in bytes of UDP packets that are delivered to clients. Each individual datagram will always
be this fixed length although the amount of data sent in specific packets may vary.
getUDPBroadcastEnabled
Method name: acq.getUDPBroadcastEnabled
Parameters: None
Return value: boolean
Determine if UDP packets are sent only to the client or are broadcast to the broadcast IP of the network.
Broadcasting is supported only when the transport type is UDP.
changeUDPBroadcastEnabled
Method name: acq.changeUDPBroadcastEnabled
Parameters: Boolean
Return value: 0 if successful, fault code on error
Modify whether UDP packets are sent only to the client or are broadcast to the broadcast IP of the network.
Broadcasting is supported only when the transport type is UDP.
getSingleConnectionModePort
Method name: acq.getSingleConnectionModePort
Parameters: None
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Return value: integer
Returns the port number on which the server will connect to the client to deliver data. This port is used only
when the connection mode is set to “single” which interleaves all data over a single connection.
changeSingleConnectionModePort
Method name: acq.changeSingleConnectionModePort
Parameters: integer
Return value: 0 on success, else fault code
Modifies the port on which the server connects to the client to deliver data. This port is used only when the
connection mode is set to “single” which interleaves all data over a single connection.
getDataDeliveryEnabled
Method name: acq.getDataDeliveryEnabled
Parameters: channel index parameter structure
Return value: boolean
Query whether a channel is enabled for data delivery. Channels must be enabled for data delivery in order for
their data to be delivered to the client. Not all channels that are being acquired are required to be delivered to data
delivery.
changeDataDeliveryEnabled
Method name: acq.changeDataDeliveryEnabled
Parameters: channel index parameter structure, Boolean
Return value: 0 for success, else fault code
Change whether or not data delivery is enabled for a particular channel. Data delivery can only be changed
prior to the start of an acquisition. Changes to data delivery enabling are only applied on the next start of acquisition.
getMostRecentSampleValueDeliveryEnabled
Method name: acq.getMostRecentSampleDeliveryValueEnabled
Parameters: channel index parameter structure
Return value: Boolean
Query whether a channel is enabled for most recent data sample requests. If a client wishes to use the XMLRPC calls to fetch the most recent value of data acquired of a channel, the channel must be enabled for this
functionality prior to the start of acquisition.
changeMostRecentSampleValueDeliveryEnabled
Method name: acq.changeMostRecentSampleDeliveryValueEnabled
Parameters: channel index parameter structure, Boolean
Return value: 0 for success, else fault code
Change whether or not a channel is enabled for most recent data sample requests. When a channel is enabled,
XML-RPC calls can be used during an acquisition to return the most recent sample of data acquired (or computed) for
the channel. Any changes to the enabled state of a channel is applied on the start of the next acquisition. If a client
wishes to use XML-RPC calls to read the value of a channel, that channel must be enabled prior to the start of the
acquisition.
getDataConnectionPort
Method name: acq.getDataConnectionPort
Parameters: channel index parameter structure
Return value: int
Retrieves the port on which the server will deliver the data for the channel specified in the parameters to the
client. Per-channel data connections are only used if the data connection method is set to “Multiple.”

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changeDataConnectionPort
Method name: acq.changeDataConnectionPort
Parameters: channel index parameter structure, integer
Return value: 0 for success, else fault code
Changes the port on which the individual connection is made by the server to the client to deliver the data for
the channel specified in the parameters. This style of connection is used only if the data connection method is set to
“Multiple.”
getDataType
Method name: acq.getDataType
Parameters: channel index parameter structure
Return value: structure
Returns the data type that is being used in the binary data streams for the channel's data. The return value is a
structure with a type and endian member. The type member, named “type”, is a string and contains one of the
following values: short, double, float. These strings correspond to their matching C-style data types. The endian
member, named “endian”, is a string and contains one of the following values: little, big. “little” corresponds to little
endian byte order, big endian bit order. “big” corresponds to big endian byte order, big endian bit order.
changeDataType
Method name: acq.changeDataType
Parameters: channel index parameter structure, type structure
Return value: 0 on success, or fault code
Changes the data type that is used for binary data streams of the channel's data. The type structure is a struct
containing two members. The “type” member is one of the following strings: double, float, short. Each string
corresponds to the matching C-style data type. The “endian” member is one of the following strings: little, big. Each
corresponds to the matching byte endian. Bit order within a byte will always be big-endian.
Not all channels may be able to support all data types. If the channel cannot be transmitted in the requested
data type, a fault code is returned.
setDataConnectionTimeoutSec
Method Name: acq.setDataConnectionTimeoutSec
Parameters: integer of new timeout in seconds
Return value: 0 on success, or fault code
Changes the timeout in seconds after which the data connections is closed when acquisitions complete.
Clients may need to set this keep-alive timeout in order to receive the trailing data at the end of acquisitions. The
default value is “0” seconds which terminates all data delivery connections immediately when the final sample of data
is acquired.
Reading Data During Acquisition
Normally data is delivered to clients during acquisitions using data connections. Data connections are either TCP or
UDP connections established from the server to the client over which the server streams the incoming data. In some
languages and environments however, it may not be possible to handle continuous data streams. The following XMLRPC commands are offered to assist these types of clients. Due to the large overhead of processing connections and
XML-RPC requests, this data transfer type is not recommended and TCP/UDP should be used wherever possible.
getMostRecentSampleValue
Method name: acq.getMostRecentSampleValue
Parameters: channel index structure
Return value: double, or fault code
This procedure allows clients to read the most recent data value of a specific channel during acquisitions. In order for
this call to be successful, a data acquisition must be in progress and the channel must be enabled for most recent
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sample value data delivery. Issue a changeMostRecentSampleValueDeliveryEnabled call prior to acquisition to allow
this procedure to be used.
getMostRecentSampleValueArray
Method name: acq.getMostRecentSampleValueArray
Parameters: none
Return value: array of structures with channel info and values, or fault code
This procedure allows clients to retrieve the most recent data values of all channels during acquisitions in a
single call. If clients are interested in the values of multiple channels, using this method is more efficient than
performing consecutive getMostRecentSampleValue calls (which require an individual POST request per call).
Only channels that are enabled for most recent sample value data delivery is returned. Issue a
changeMostRecentSampleValueDeliveryEnabled call for each desired channel prior to acquisition in order for this to
return the value for a channel.
The return value is an array of structures, one per channel. Each structure contains two members. The
“channel” member will contain a channel index structure with members set to appropriate type and index information
for the channel. The “value” member is a double that contains the most recent sample value of the channel specified in
the “channel” member.
This procedure cannot be called unless there is an acquisition in progress and there is at least one channel
enabled for most recent sample value delivery.
Other Control Connection Commands
Control connections will also allow for the following additional commands to be used by clients:
loadTemplate
Method name: acq.loadTemplate
Parameters: base64 encoded binary AcqKnowledge graph template
Return value: 0 on success, or fault code
Attempts to open the passed template within the AcqKnowledge environment. The parameter is a base 64
encoded AcqKnowledge “gtl” graph template file. Only templates in PC AcqKnowledge 3.7.1 or Mac AcqKnowledge
graph templates are allowed to be used with this command. The parameter must include the entire contents of the
template file.
The parameter in the XML-RPC call should be a base64 parameter with the raw binary contents of a graph
template file. When this parameter is decoded, it should correctly provide the contents of a template file on disk.
This function will return 0 on success, otherwise a fault code if the template could not be loaded. Once a
template is loaded, the hardware settings contained within that template is used for subsequent data acquisitions.
Templates for ACQ 3.9.2 and higher will retain any data connection settings that have been specified by clients. After
loading a template, clients should re-send any configuration information for ports and data connection methods if they
do not match the new settings from the template.
If the template data is corrupted or is incompatible with AcqKnowledge, user interaction may be required on
the server computer to dismiss any error messages when attempting to load the template. If user interaction is required
on errors, this call may not return until the user interaction has completed. Clients who are using XML-RPC bindings
that offer timeout services may wish to use them with this function.
getAcquisitionInProgress
Method name: acq.getAcquisitionInProgress
Parameters: none
Return value: Boolean

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Query whether data acquisition is currently in progress or not. A value of true is returned if data acquisition is
occurring in any open AcqKnowledge graph window.
toggleAcquisition
Method name: acq.toggleAcquisition
Parameters: none
Return value: 0 on success, else fault code
Toggles data acquisition in the frontmost graph. If data acquisition is in progress, it is halted. If none is in
progress, data acquisition is started in the graph.
Note that this function invocation may block if physical user interaction is required to start the acquisition in
the graph, such as dismissing an overwrite warning, warnings on incompatibilities between different MP unit types,
specifying a save location for acquisition to disk, etc. If the implementation of the XML-RPC binding used by the
client supports timeout capabilities, it is highly recommended to enable timeouts for this function.
setOutputChannel
Method name: acq.setOutputChannel
Parameters: channel index structure, float output value
Return value: 0 on success, else fault code
Changes the voltage on the specified output channel of the MP device. For analog outputs, the value should
be in the range (-10, 10) for the voltage level. For digital outputs, a value of 0 will turn the specified line off, a nonzero value will turn it on. The latency of when the output line is changed is variable and non-guaranteed. Additionally,
the output channel may be modified by other areas of the software including control channels, manual user
intervention, configured stimulators, etc.
The valid output channels are dependent on the type of MP device that is connected.
§

MP160/150 units allow analog 0, 1 and all digital output channels

§

MP36R units allow no analogs and digital 0-8.

Unity Interface for AcqKnowledge (requires Network Data Transfer License)

Unity® Interface for AcqKnowledge® allows for easy connection of Unity3D projects with AcqKnowledge software.
· Create a virtual environment using industry-standard Unity
· Connect and configure projects with AcqKnowledge in real time
· Control Acquisition from Unity to Custom Markers, Digital, and Analog I/O
· Deploy to your devices. Immerse your users and capture biofeedback for analysis
This Unity3D package allows Unity developers to access the AcqKnowledge network API (Network Data Transfer)
v5.0 from Unity scripts without having to deal with the details of network communication, threading, and data access.
The Unity Interface for AcqKnowledge is compatible with recent versions of Windows and macOS.
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Chapter 22

Licensed Functionality: Vibromyography

VMG functionality is available through an optional license available with AcqKnowledge 5. The
VMG license must be authorized to access VMG functionality. To add a VMG license to an
existing MP System, please contact BIOPAC.
The vibromyography transducer (TSD250) uses an accelerometer to measure surface vibration during activity which
is directly correlated to muscle activity; this allows for muscle force and balance to be assessed without using surface
electrodes or needle probes. The VMG license allows access to software processing algorithms that are incorporated
into AcqKnowledge to perform data reduction for analysis of data collected from a VMG system.
The VMG license:
§

adds “Vibromyography” Calculation channel Preset with required scaling and calibration

§

adds “Vibromyography Filter” option under the Analysis menu

§

includes QuickStart Q45 Vibromyography (.gtl format)—the journal of the file introduces VMG and the
hardware settings use Module Setup to add a “VMG Transducer” to analog channel 1 and analog channel 2 of
an HLT100C module. Two calculation channels are set to the “Vibromyography” preset using analog channel
1 and analog channel 2 as the respective source channels.

The VMG analysis reduces the channel sampling rate by a factor of 32. In the AcqKnowledge software, all data in an
individual waveform share the same acquisition sample rate and each channel may have a lower sample within certain
parameters, see (link for variable rate sampling ). It is not possible to mix sampling rates within a channel. This
analysis is preformed for the entire channel or appended segment (see VMG and append on page 46x). Traditionally,
if there is only a single point selected, then the entire data channel is transformed. If only a portion of the wave is
selected, then the following warning will be displayed:

When OK is clicked, analysis will be performed on the entire waveform. The selected area will be maintained but the
waveform regions outside the selected area will still be transformed. This matches the “Transform entire wave”
checkbox operation of other transformations. Cancel exits without modifying the data.
Sampling Rate Restrictions
The Vibromyography Filter is designed to process data acquired at 2 kHz sampling rate only. If the correct
sampling rate is not used (via Hardware menu > Set Up Data Acquisition > Length/Rate), results may be
unpredictable.
Transducer Setup
The TSD250 VMG transducer is a MEMS accelerometer transducer used for recording vibromyography signals
from major muscle groups.
§

MP160/150: Activating the VMG license adds the “VMG Transducer” option to the MP160/150 module
setup; it is an HLT100C high level transducer.

§

MP36R Support—the MP36R system may be useful for VMG analysis as four channels allows for
comparison of muscle balance between two muscle groups. No analog channel preset exists for the VMG
transducers, but a Vibromyography preset exists for the calculation channel. See page 501.

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Post-Analysis Selection Adjustment
After the analysis completes, the waveform sampling rate of the selected waveform will be reduced by a factor of
32. As this reduction occurs, the selected area or cursor will adjust to the nearest sample point in the processed
VMG channel.
Data Modification History Name
This operation will be displayed in data modification logs (Display > Channel Info) as “VMG Analysis.”
It will not have any parameters.
VMG Calculation Channel Preset
The Vibromyography calculation channel preset uses the VMG channel as its source channel. The calculation
channel preset automatically applies a downsampling divider of 32 based on the acquisition sampling rate.
§ The Vibromyography preset automatically adjusts the channel sampling rate by a factor of 32. After
setting up the Vibromyography calculation channel, adjusting the channel sampling rate for the VMG
source channel will not change the sampling rate of the Vibromyography calculation channel. The
channel sampling rate can be manually adjusted.
At the end of an acquisition, the Vibromyography preset automatically performs the following steps:
1. Checks for the Vibromyography license. If the license is not found, then the appropriate prompt is
displayed.
2. Checks if acquisition is running in append mode. If this is the case then additional parameters are checked
and the user will be prompted as needed.
3. Perform Vibromyography Analysis filtering.
4. Adjust selection to highlight only the most recently acquired data segment. If not in append mode, all data
will be selected.
5. Copy the processed data to the clipboard.
6. Select the destination calculation channel.
7. Paste processed data from clipboard over the zero valued data for the appended segment (or entire
channel if not in append mode).
8. Remove the duplicated channel created earlier.

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VMG Sample Data Files
Two sample data files illustrating basic VMG data and analysis results are included:
§ VMG right leg VL dynamic isometric.acq

§

VMG Squat Data.acq

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Watch the AcqKnowledge Vibromyography video tutorial for a detailed demonstration of this feature.

Chapter 23

Licensed Functionality: Scripting

Scripting functionality is available through an optional license available with AcqKnowledge 5. The Scripting
license must be authorized to access Script functionality for executing, authoring, and debugging BIOPAC
Basic scripts. To add a Scripting license to an existing MP System, please contact BIOPAC.

BIOPAC Basic Scripting is a scripting language development option for AcqKnowledge that allows for viewing
of runtime variables, creating new script files and editing existing script files, triggering of individual script functions
for testing and single step functionalities. Only users that have licensed the BIOPAC Basic feature may run usergenerated scripts; if the feature is not available only digitally signed BIOPAC scripts may be executed. Scripting is
available in any hardware supported in AcqKnowledge but configuration commands may not be available for non-MP
hardware.

The Scripting license
§ enables the Script menu
§ adds the Calculation channel Preset “Run Macro”

§
§

links the BIOPAC Basic Reference under Help
adds Preferences for Scripting

Script Editor Controls

Functionality

Save As

Saves changes applied to a script

Check Syntax

Click to check the current macro for errors.

Find/Replace

Opens a find and replace dialog for quickly editing text within the current macro.

Revert

Click to discard any changes to the current macro.

Delete

Click to remove currently displayed macro function from the script. This operation cannot be
undone.

Run

Click to run the currently displayed macro. If single step mode is active, only the first line will
be executed.

Script File:

Use to open an existing script or create a new one.

Macro:

Use to create or select the macro or callback to be applied. For more information, se the
Biopac Basic Reference under the Script Editor or AcqKnowledge Help menu.
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Scripting Menu

Script Editor
The Script Editor is the window used for creating and editing scripts. The window appears blank by default
unless an existing script file (*.bbs) is selected or a new script is created.
To create a new script in the Editor, select New Script File from the “Script file:” menu.
To open any of the existing AcqKnowledge Specialized Analysis scripts, choose Open Analysis Script from
the “Script file:” menu and select the desired script file.
Script Editor formatting is controlled in the Script Editor Preferences (Display > Preferences > Script Editor).

The size of the Script Editor window can be customized by using the “Set Default Window Size” preference
option. (AcqKnowledge 5.0.1 and higher). To resize to a new default setting:
1. Open the Script Editor window (Script > Script Editor)
2. Resize the window to the desired size by clicking and dragging the corner.
3. in Display > Preferences > Script Editor, click “Set Default Window Size” and click OK.
Default settings can be restored with the “Use Default Settings” button.

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Variables Explorer

Variables Explorer Window
The Variables Explorer window (Script > Variables Explorer) shows the contents of the scripting language
variables.
Single Step Execution mode (Script > Single Step execution) halts execution after each individual line of a
macro, which allows for stepping through macros line by line for debugging and development purposes.
Example Scripts
Several BIOPAC example scripts and macros are available in this menu. When a script file is selected, the
scripting language for the selected script is displayed in the Script Editor.
Run Macro Calculation Channel

Run Macro Calculation Channel Setup Dialog
The “Run Macro” Calculation Channel Preset enables automatic post-processing at the end of acquisition.
Note
§ Inserting an extra End in the middle of the macro creates a second macro upon saving. The second
macro starts immediately after the inserted End.
§ Run Macro calculation channels created with a licensed version will run if opened in a copy of
AcqKnowledge without a Scripting license, but the macro cannot be edited.

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To view the full online BIOPAC Basic Reference Scripting Manual, see the AcqKnowledge Help menu.

More Scripting References
For more information about creating user-defined scripts for automated analysis routines, see the
Tutorial Video.
Preconfigured scripts for automated routines may also be downloaded from BIOPAC here.

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Licensed Functionality: Remote Monitoring

Remote Monitoring functionality is available through an optional license available with
AcqKnowledge 5. The license must be authorized to access Remote Monitoring functionality. To add
a license to an existing MP System, please contact BIOPAC.
New! Remote Monitor
Track the welfare of the subject with alarms to
warn when signals fall out of range. The system
will work on any device that has access to the
same IP based network as the MP150.
Simplified user interface to view subject data on
another computer or mobile device – ‘bedside
monitor’ display.

AcqKnowledge MP devices are generally tethered to specific computers where data acquisition is performed.
In some laboratories, this computer may not be in the same location as the researcher performing the
experiment. In MRI situations, for example, the data acquisition computer may be in the MRI control room
but the researcher may be in a separate area. AcqKnowledge Remote Monitoring offers researchers the
capability of checking on critical parameters from an alternate location.
Remote Monitoring is a client/server application capable of locating and connecting to computers running
AcqKnowledge on the same network. It consists of a simple browser interface, from which acquisitions can be
started, stopped and remote data viewed during and post-acquisition. Remote Monitoring is supported in
MP160/150 hardware only.
About Remote Monitoring
§

Remote Monitoring is licensed functionality and must be activated by BIOPAC.

§

Remote Monitoring is for viewing of data only. Transformation and specialized analysis of graph data
is not supported within the Remote Monitoring interface.

The Remote Monitoring web interface consists of three primary pages:
§ A list of open graph windows
§ Configuration settings for an individual graph
§ The data monitoring page.
Remote Monitoring in AcqKnowledge Networking Preferences
Remote Monitoring is enabled by default in
AcqKnowledge Networking Preferences (Display >
Preferences > Networking > Remote Monitoring). The
Enable remote monitoring checkbox option activates
the local machine on the network, making it visible to
other local network machines also running
AcqKnowledge Remote Monitoring.
The Webserver TCP port is the numerical port on which AcqKnowledge listens for remote requests. (This
port is set to 8080 by default.) The Remote monitor URL is a clickable link that opens Remote Monitoring
in the local machine’s default web browser. This view will display acquisitions running on the local
machine only. (This is actually an easy way to become familiar with Remote Monitoring). To view
acquisitions running on machines in other network locations, the stand-alone Remote Monitoring Client
application must be used. For further details, see the Remote Monitoring Client section on the following page.
NOTE If a Remote Monitoring preference or port setting is changed, the new preference will not be applied
until the subsequent AcqKnowledge application launch.
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Remote Monitoring Client
The Remote Monitoring Client is a stand-alone application residing in the AcqKnowledge program folder.
This application facilitates the remote connection to other computers running AcqKnowledge acquisitions on
the local network. AcqKnowledge does not need to be running on the local machine in order to use the
Remote Monitoring Client to observe remote acquisitions in progress. To launch the Client, browse to the
following directory:
Main Drive:\Program Files\BIOPAC Systems, Inc\AcqKnowledge 5\RemoteMonitorClient.exe

Double-click on the RemoteMonitorClient.exe to launch the application. After launching, the first presented
item is the Remote Monitoring Server list. This is a list of other AcqKnowledge computers on the network
that have Remote Monitoring enabled.

Quit
Refresh List
Connect

Exits Remote Monitoring Client
Updates list of available AcqKnowledge Remote Monitor computers on network
Connects to the computer selected in list

The above-right figure shows a right-click contextual menu available within the Remote Monitoring Server
List, which allows an alternate means of connecting to a selected computer. The Properties option displays the
AcqKnowledge application status, along with network and hardware information about the selected computer.
Remote Monitoring Client Browser
Selecting a computer from the list launches the Remote Monitor Client browser interface. The navigation
buttons operate in the same manner as most Internet browser controls. See the following page for details on
the Remote Client browser buttons.

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Button Function
Back

Explanation
Moves browser back one page

Forward

Advances browser ahead one page

Refresh

Reloads the current page

Stop

Stops loading of current page

Address bar

Displays I.P. address of currently-connected computer

Zoom in

Master control for enlarging size of browser content

Zoom out

Master control for decreasing size of browser content

File, Edit, Help
menus

File contains Page Setup and Print controls for
Remote Monitoring chart displays. Quit exits the
Remote Monitor.
Edit contains a Copy option. (Copy function not
supported in Windows version)
Help displays “About” information for the current
version of Remote Monitoring Client*

NOTE for Windows only:
In order for the Remote Monitor Client to properly display the server list of additional AcqKnowledge
computers on the network, Bonjour Service for AcqKnowledge must be installed. (The option of
installing Bonjour Service is presented during the licensed AcqKnowledge application installation). If
Bonjour is not installed, the following dialog will be presented upon launch of the Remote
Monitoring Client:

The I.P. address of the desired computer can be entered into the http-address field. If the address is
valid, clicking OK will connect the Remote Monitoring Client to this computer. An acceptable entry
should include the server IP address and UDP port number. (Example; http://192.168.1.76:8080)
Open Graphs Page
When the Remote Monitoring Client browser is launched, a scrollable list of all graph windows currently
open on the selected remote machine is presented. Only one graph may be selected at a time.

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Refresh this page

Reloads the page and refreshes the list of available graphs.

Show Monitor

Advances the browser view to the selected file’s setup page.

Configuration Settings Page
After selecting a graph and clicking Show Monitor, the following Monitor Setup page is displayed. This page
contains configurable options for data display and other viewable parameters in the Remote Monitor graph.
Note that all available options are set individually per channel.

Control
Return to Graph List
Show Monitor
Auto-refresh interval
Use audible alarms

Label
Show Trend
Show Most Recent Value
Show Min/Max
Alarm Enabled
Precision

Description
Returns browser to list of currently-open graphs. Serves the same function as the
browser’s ‘back’ button.
Saves the selected setup and advances the view to the data monitoring page.
(‘Show Monitor’ button at bottom of screen duplicates this link’s function)
Chooses the interval at which the monitored data is being refreshed over the
network. The increments range from 1-sec. to 5 minutes.
When enabled, an alarm will sound if the Remote Monitoring graph data display
exceeds its maximum or minimum visible ranges. The audio sound is a onesecond beep followed by one second of silence. This audio playback is supported
only on HTML5 compliant browsers.
Displays assigned label of the AcqKnowledge data channel
Displays a graphical plot of the currently monitored data.
If checked, the most recent value of the channel data is displayed in a large font.
If unchecked, textual display of this value is omitted.
Displays minimum and maximum value of currently monitored data.
If the channel value exceeds the current trend display range, the alarm changes
the color of the textual display to red and optionally plays audio.
Sets number of decimal places following channel display values.

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Data Monitoring Page
After the desired channel setup parameters are selected, choosing ‘Show Monitor’ will advance the view to
the data monitoring page.

If an AcqKnowledge acquisition is already in progress and data being plotted, the screen will appear similarly
to above, with the graph plot tracing at intervals determined by the Monitor setup auto-refresh rate. If the
acquisition has not been started prior to launching Remote Monitoring; the Start button will be displayed in
this screen. (Remote acquisitions can be easily started or stopped from within this data monitoring page).
Control
Return to Graph List
“-“ and “+”
Reset
Show Monitor Settings
Start/Stop
Refresh Now
Stop Alarms
Plot
Change Range

Description
Displays scrollable list of all currently-open graphs.
Controls for decreasing and increasing size of the input values display font.
Resets size of input values font display to default setting.
Returns to the “Monitor Setup” page for adjusting refresh rate, display options, and
other monitoring parameters.
Toggles between starting/stopping acquisition in Remote Monitoring graph.
Updates data and controls on Monitoring page.
Halts any audio alarms that may be playing. Active only if Audio Alarm option is
enabled.
Controls visual display of Min, Max and Mean values display of current graph
Allows adjustment of visible ranges of the chart, similar to the vertical and
horizontal scale dialogs found in the AcqKnowledge application. This is useful for
viewing data that may otherwise appear out of range of the default scaling. Change
Range only affects the data display in the Remote Monitoring window, not in the
actual AcqKnowledge graph data. (See below for Change Range example and further
details).

Default Visible range. (Note BPM data from this graph is ‘out of range’ in the above chart)
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Visible range is modified via ‘Change Range’ to include entire data set. Horizontal time scale and vertical divisions were
also modified.

Controls in Visible Range (Change Range) dialog
Control
Return to Monitor page
Show seconds of data
Number of horizontal divisions
Horizontal axis precision
Vertical lower endpoint
Vertical upper endpoint
Number of divisions

Description
Clickable link for paging back to the Monitoring screen.
Determines visible horizontal time scale in chart display.
Sets the number of horizontal divisions in chart.
Sets number of decimal places following horizontal time values.
Determines low end of vertical graph scale.
Determines high end of vertical graph scale.
Sets the number of vertical divisions in chart.

NOTE: Remote Monitoring plots are only updated in the data monitoring window while an acquisition is
in progress. Once a Remote Monitoring acquisition is stopped, the graph will remain visible only as
long as the browser page is displayed. After navigating away from the page, the plot will not be
retained or reconstructed. To save a Remote Monitoring plot for future reference, printing a hard
copy or printing to a PDF file is recommended.
*For Remote Monitoring technical support, contact BIOPAC Systems, Inc at (805) 685-0066 or
support@biopac.com

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Licensed Functionality: B-Alert

B-Alert functionality is available through optional licenses* available with AcqKnowledge 4.4.x.
(B-Alert wireless headset hardware is also necessary).
* B-Alert Headset integration: must be authorized to access basic B-Alert functionality.
* Cognitive States Analysis: must be authorized to access this enhanced functionality.
To add licenses please contact BIOPAC.
The B-Alert Hardware Data Acquisition license adds:
§

Basic wireless recording of up to nine channels of raw or decontaminated EEG data

The Cognitive States Analysis Software license adds:
§

Functionality described above, plus the ability to create individual baseline recordings for each
subject

§

Additional analysis software and specialized calculation channels

Data Acquisition and Analysis with B-Alert™

B-Alert™ X10 is a Bluetooth wireless system and sensor headset integrated with AcqKnowledge software to
record up to 9 channels of monopolar EEG, plus one optional channel of ECG data. B-Alert data can be
acquired simultaneously with BIOPAC MP160/150 Hardware, if additional graphs are used.
IMPORTANT NOTE: In AcqKnowledge for B-Alert:
§ B-Alert is licensed functionality and must be activated by BIOPAC
§ Analog channels can be toggled on/off but not modified
§ Digital channels are not supported
§ B-Alert-specific calculation channels are available when the optional Cognitive
States Analysis software license is applied (AcqKnowledge calculation channels C8
and higher can be used if configured manually)
§ Data acquired with B-Alert is outputted in standard BIOPAC *.acq format
B-Alert™ users should refer to the B-Alert X10 User Manual for complete hardware setup instructions. This
guide, and other B-Alert material can be found on the BIOPAC Manuals Support page.

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AcqKnowledge software is used to view, record and analyze data acquired with the B-Alert unit.
To launch software with B-Alert hardware:
1. Connect the B-Alert dongle to a USB port and turn the X10 headset unit’s power switch ON.
2. Choose B-Alert device from the AcqKnowledge Startup Wizard Hardware menu or from the
‘Connect to > Add New Device’ menu in the application window. (See figures below.)
3. Use the B-Alert menu options for acquisition and channel settings.

With B-Alert installed, an additional
“B-Alert Live” shortcut icon will
appear on the Desktop. To use BAlert with AcqKnowledge, initiate all
B-Alert actions from within the
AcqKnowledge software interface as
shown in this chapter. For further
information about B-Alert, see the BAlert Software Manual.

OR:

When AcqKnowledge launches in B-Alert mode, the MP menu will be replaced by the B-Alert menu and the
B-Alert device ID will appear in the AcqKnowledge graph “Connect to” menu.

If the B-Alert device cannot be located or is disconnected, the following dialog will appear:

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Click ‘Retry’ in the B-Alert Headset Warning dialog to initiate a refresh of the hardware connection.
Click ‘Cancel’ in the B-Alert Headset Warning dialog to launch the AcqKnowledge software in analysis
mode. This operates similarly to MP “no hardware” mode, for which data can be analyzed and transformed
but not recorded.
Acquisition Setup
Standard recording modes found in MP hardware (with the exception of Averaging) are supported in B-Alert
but the acquisition sample rate is limited to a maximum of 256 samples per second. Dependent upon licensing
level, there are two additional checkbox options in the B-Alert Set Up Data Acquisition > Length Rate dialog:
·

Record EEG artifacts as events: When checked, recorded EEG artifacts are translated into
visible events (eye blinks, EMG interference, etc.). When unchecked, artifacts are discarded and
only data is acquired.

·

Use B-Alert Definition File: When checked, enables use of a subject’s baseline Definition File.
This option is only available if the Cognitive States Analysis license is applied. See page 519 for
a detailed explanation of Definition File setup in AcqKnowledge.

Channel Setup
Nine analog input channels of monopolar EEG data are enabled by default in B-Alert, along with one optional
ECG (EKG) channel. Channels are configurable as desired. In the standard B-Alert setup, calculation
channels C8 – C15 remain available for additional online transformation/filtering of data (for C0-C7, see page
522). (Digital channels, stimulation or triggering are not supported in B-Alert hardware.)

Under the standard B-Alert license, the Input channel setup contains options for recording raw or
decontaminated EEG data. These parameters are set individually per channel. It is possible to record raw data
on one channel and decontaminated data on another.
·

Record raw data: records unfiltered data. Any further filtering must be applied through
calculation channels or transformations. (Default setting)

·

Record decontaminated data: filtered data will be recorded for the channel. This setting applies
algorithms to minimize artifact resulting from eye blinking or other small involuntary
movements.

The optional B-Alert Cognitive States Analysis license offers additional functionality, such as creation of a
baseline “Definition” file (based upon a subject’s responses to some simple cognitive tests), and access to preconfigured calculation channel setups.

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B-Alert-specific Hardware Menu Options

B-Alert Headset Check Impedance
This item is found in the B-Alert menu, (which
replaces the MP menu in B-Alert hardware
configuration) and is used to initiate an
impedance check to verify the headset’s
electrode contact quality. Results and
resistance values are displayed in the dialog
when the check is complete. If any of the
channels show red or fail the impedance check
(as shown on Channel Fz on the right), verify
that electrodes are firmly attached and making
good contact, and then rerun the check.

B-Alert Headset Benchmark Session
Requires Cognitive States Analysis license
Use to set up an “Alertness Memory Profile”
(AMP) Baseline recording of a subject’s EEG
definition file. The baseline (Benchmark)
recording consists of a three-choice
psychomotor vigilance task (3CVT) and eyes
open/eyes closed.
Subject: Field for 4-digit identifier unique to
subject being recorded.
Group: Field for single-digit identifier used to
distinguish the subject’s group number.
Iteration: Field for single digit identifier
identifying the session, if additional Baseline
sessions are recorded for a subject.
ABM Benchmark scenario: Choose the type
and length of the baseline recording. The
following recording lengths are supported:
·

Short Benchmark – 3CVT (three-choice
Psychomotor Vigilance Task, 3 minutes
per task)

·

Medium Benchmark – VPVT (Visual
Psychomotor Visual Task, 5 minutes per
task)

·

Long Benchmark – APVT (Auditory
Psychomotor Vigilance Task, 20 minutes
per task)

After setting up the required fields, click OK to
launch the baseline recording user interface,
which will resemble the example to the right. A
series of onscreen step-by-step instructions will
follow.

For more details about the Benchmark recording user
interface and additional software controls, refer to the
Benchmark section of the B-Alert Software Manual.

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B-Alert Generate Definition File
Requires Cognitive States Analysis license
Use this option to generate or recreate a
definition file from a previous Headset
Benchmark session.
After completing a Benchmark session (see
previous page), a definition (.def) file is
automatically generated and saved to the
subject folder. This *.def file is used to generate
the Benchmark Report file. If the *.def file needs
to be recreated, the "B-Alert Generate
Definition File" option can be used. Note: The
previous Benchmark Signal *.edf and all
baseline Events *.edf files must be located
within the same folder, and have the same 9digit number for a definition file to generate
properly. Follow the steps below to create a
definition file:
1. Choose “B-Alert > B-Alert Generate
Definition File.”
2. Click “Select Source Files…”.
3. Navigate to the desired folder
containing the Benchmark session
*.ebs “Signal” file.
4. Select the *.ebs “Signal” file and click
“Open.”
5. Select the “Event” (*.edf) files (a
minimum of three must be selected)
and click “Open.”
6. Click “Generate” to create the new
definition file and report and save them
to the Benchmark destination folder.
Once created, the individualized .def
file can be reused across sessions (for
Cognitive State and/or Workload Metric
classifications) for a given individual.
7. See page 519 for further details about
using and assigning a definition file.

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B-Alert ESU Configuration
The B-Alert ESU unit is a multi-channel external
synchronization unit that serves as a
communication interface between the B-Alert
unit and the computer. It allows for
synchronization of data between the B-Alert
hardware and other third-party data acquisition
devices.
For more information about the B-Alert ESU
unit, see the B-Alert with AcqKnowledge Quick
Guide or the B-Alert Software Manual.

NOTE: Before configuring the ESU settings, the ESU
must be paired with the B-Alert unit via a Bluetooth
connection.
·

B-Alert headsets are shipped paired to either a
B-Alert Dongle or an ESU. If the pairing is lost,
the devices must be re-synced using the “Sync”
option in the B-Alert Live software’s “Operations”
menu. For more information, see the “Sync
Device” troubleshooting section in the B-Alert
with AcqKnowledge Quick Guide or the B-Alert
Live Software Manual.

To Configure the ESU in AcqKnowledge:
1. Plug the ESU unit into a computer USB port.
2. In AcqKnowledge: choose B-Alert > B-Alert ESU
Configuration.
3. In the ESU Control Panel, use the pop-up menus
to configure ESU third-party data (three serial
COM ports and one parallel port) as desired (see
below).

4. Click “Save config to ESU unit” to save the
settings.
5. Wait until the “saved configuration” confirmation
dialog appears. Restart the ESU by unplugging it
and then re-plugging into the computer’s USB port.

B-Alert Show Brain State Gauges
Requires Cognitive States Analysis license
activation
Displays real-time views of B-Alert headset data
as it is being acquired. Information includes
Meter Gauges (Top Left) with Engagement,
Workload and Drowsiness (along with Heart
Rate) Time Series (Bottom) Movement Meter
Gauge (Bottom right) Heat maps (Top Right)
display EEG power spectral densities (PSD) in
both spatial and temporal maps for the
traditional Hz bands (Beta, Alpha, Theta,
Sigma).

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Assign Definition File
Requires Cognitive States Analysis license activation

The Definition File is created when the subject undergoes an initial baseline EEG recording while responding
to some simple onscreen tests, or can be recreated from an existing Benchmark session via the “B-Alert
Generate Definition File” menu item. (The Definition File setup is configured in the B-Alert Headset Amp
Baseline dialog, referred to on the previous pages). The file is saved to the directory containing the subject’s
B-Alert profile folder. Once created, a subject’s Definition File will always be referenced for subsequent
recordings and analysis.

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Output to ABM File Format
Acquisition setup options are available for controlling data output to a separate B-Alert ABM file format,
which contains an “*.ebs” extension. Outputting to *.ebs format can be useful for preventing raw EEG data
from being overwritten while recording in decontamination mode. (AcqKnowledge does not save the original
raw EEG data within the default *.acq file format if the decontamination option is applied.) To set the
filepath for saving ABM files, open B-Alert > Set Up Data Acquisition > Length Rate, and click “Choose
ABM data file location.” A file chooser dialog will appear for setting the desired path.

If no user-defined ABM data file location is selected, the ABM files will be saved by default to
C:\Users\username\AcqKnowledge\ABM.
Other B-Alert Setup Options are:
· Record B-Alert EEG artifacts as events:
When this option is selected, artifacts appearing in the B-Alert data (i.e., eye blinks) will be assigned
event markers as these artifacts are detected during the recording. B-Alert events can also be
manually assigned to recorded data while in progress or in post-acquisition analysis by using the
Event tool

. For more details on the AcqKnowledge event marking system, see page 224.

Event types supported for B-Alert recordings

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·

Use B-Alert Definition File:
When this option is selected, the Benchmark definition file will be used for the recording (requires
Cognitive States licensing level).

·

Assign Definition File:
Use this option to navigate to and select a different definition file for the recording.

Opening the ABM Data File
The outputted ABM *.ebs format data file can be opened in AcqKnowledge by choosing File > Open,
browsing to the file location and selecting “EDF” format from the file type list. For a complete list of
outputted ABM data see the Data Output table on page 523.
NOTE: Even though the file extension in the output dialog appears as “*.ebs”, the file will open in
AcqKnowledge by choosing “EDF” format.

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Linked Acquisitions in B-Alert
Linked acquisitions are supported in B-Alert. In a Linked Acquisition session, different hardware device types
can acquire data simultaneously into individual graphs. B-Alert acquisitions can be synchronized with and
triggered by an MP160/150 unit and the multiple data recordings merged into one graph at the end of the
session.
NOTE: In order to use “master synch device” mode to link signals between B-Alert and MP160/150
hardware, a CBLX10 cable is necessary. See the MP Hardware Guide for more CBLX10 details.
To connect the CBLX10 for an MP160/150/B-Alert linked acquisition:
1. Plug the black connector into an Analog Output on the UIM100C* module connected to the MP unit.
*If using the HLT100C module with the MP160 hardware, connect the black connector to a CBL122
adapter cable (3.5 mm jack to RJ11 connector).
2. Plug the blue connector into the 2-pin (ECG) input on the top of the B-Alert unit.
3. In AcqKnowledge, choose “MP160/150 > Set Up Data Acquisition > Set Up Linked Acquisitions”
and select “Use the master synchronization” as the synchronization method to pair and synchronize
data obtained during linked MP160/150 and B-Alert X10 acquisitions. This is the only configuration
where the “Master Sync Device” radio button is active.
IMPORTANT: About 10-12 seconds after starting a linked MP160/150/B-Alert X10 acquisition, and
verifying that both independent signals are being plotted correctly in AcqKnowledge, disconnect the CBLX10
from the B-Alert headset to avoid introducing extraneous noise into the B-Alert signal.
For further details on setting up Linked Acquisitions, see page 244 or watch the Tutorial video.
Cognitive Analysis Calculation Channels
Pre-configured calculation channels C0 – C11 become available when a subject’s B-Alert Definition File is
active. These signals are mapped from the Definition File and extract cognitive workload, high/low
engagement, distraction, drowsiness, movement and tilt angle data. The channel setups and presets are not
editable but can be enabled or disabled as desired.

For specific information on additional B-Alert GUI software controls, see the B-Alert Software Manual.

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Data Output
The following data is collected during a B-Alert experiment and merged into a standard AcqKnowledge *.acq
file:
Real-Time Output file name

Description

Data file
.edf

_Impedance.csv

European data format containing nine raw and nine decontaminated
EEG channels, raw ECG channel, plus derived heart rate, head
movement value and head movement level
Lists the values obtained for each channel each time impedance was
measured

Automatically Generated during Acquisition – for all EEG Channels
_Ref_Raw.csv
_Ref_Class.csv

Absolute PSD from 1 to 40 Hz, relative PSD from 1 to 40 Hz, and EEG
bands labeled by channel (no edge-effect window)
Absolute PSD from 1 to 40 Hz, relative PSD from 1 to 40 Hz, and EEG
bands labeled by channel (with Kaiser window)

Automatically Generated during Acquisition – Derived Signals
_HR_beat.csv
_HR_epoch.csv

Presentation of heart rate based on beat-to-beat interval
Beat-to-beat heart rate interpolated to sec-by sec value

Optionally Generated with B-alert Cognitive State Classifications
_Classification.csv

_Diff_Raw.csv

_Diff_Class.csv

_Zscore_class.csv

_Zscore_psd.csv

Probabilities for sleep, distraction, low and high engagement, cognitive
state from DFA with greatest probability, probability of high workload
based on forward and backward digit span (FBDS), backward digit span
(BDS), and average of FBDS and BDS
Absolute PSD from 1 to 40 Hz, relative PSD from 1 to 40 Hz, and EEG
bands for differential channels: FzPO,CzPO,FzC3,C3C4, and F3Cz (no
edge-effect window)
Absolute PSD from 1 to 40 Hz, relative PSD from 1 to 40 Hz, and EEG
bands for 5 differential channels FzPOz, CzPO, FzC3, C3C4, F3Cz (with
Kaiser window)
Updates and applies mean and standard deviation with each new
second to provide z-scores for B-Alert cognitive states (sleep onset,
distraction, low and high engagement, three workload measures)
Updates and applies mean and standard deviation with each new
second to provide z-scores for PSD for all channels requested in
initialization process

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Chapter 26

Licensed Functionality: PV Loop Analysis

PV (Pressure-Volume) Loop Analysis is available through an optional license available with
AcqKnowledge 5. The license must be authorized to access this Analysis tool. To add a license to an
existing MP System, please contact BIOPAC.
Pressure-volume loops (a.k.a. PV Loops) measure blood pressure and flow from a catheterized system. This
analysis tool extracts various measures of heart function, including contractility, elasticity and ventricular
characteristics. Sophisticated algorithms in this advanced analysis feature help circumvent the laborious visual
process of identifying loop ranges while allowing the inclusion or exclusion of individual loops in the analysis
output. Extracted measurements can be saved to an Excel spreadsheet, and selectable XY data views clearly
show a wide range of outputted data. A pressure-volume loop graph template containing the necessary
analog/calculation channels, data views and custom toolbars is included with the feature. (Q46-Pressure
Volume Loop.gtl) PV Loop Analysis is supported in MP160/150 hardware only.
Loop Location
The two primary time locations for an individual PV loop range from the end systole (ES) point where the
aortic valve closes, and the end diastole (ED) point where the mitral valve closes. On a PV loop XY plot, the
end systole point is located at the top left corner of the loop and the end diastole is at the bottom right corner
of the loop. An individual loop is defined as the extent from one end diastole to next end diastole, the
equivalent of one heart beat.
PV Loop Analysis Preferences
PV Loop Analysis Preferences are accessed via the Analysis > PV Loop menu and offer two methods for
locating cardiac cycles.

PV Loop Analysis Preferences dialog
PV Loop Analysis Preference Controls
P/V ratio
ED relaxation percentage
% threshold of dP/dt max and min
% of max
% of min
Customize Baseline Results

Description
When selected, ES and ED are located by analyzing
the ratio of pressure over volume.
Percentage that P/V ratio must fall from ES in order
to locate ED.
When selected, ES and ED are located using the
pressure signal derivative only.
Defines percentage of the positive pressure
derivative local maximum for ED.
Defines percentage of the negative pressure
derivative local minimum for ES.
Displays a checkbox dialog for selecting measures to
be included or excluded from baseline analysis. (See
next page for complete list of available measures)

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Baseline Analysis
Baseline analysis extracts basic single-loop measures over selected data ranges. These measures are used to
assess proper positioning of the catheter for calibration and for assessing various changes during the
experiment. Baseline analysis is accessed via Analysis > Pressure-Volume Loop > Baseline Analysis, or via
the “Analyze Baseline” button on the PV Loop graph template. Measures to be extracted or excluded are
accessed in the Preferences > Customize Baseline Results menu.

Available Baseline Analysis measures
The figure below shows a partial view of single-loop Baseline Analysis measures. The Save icon on the top
left is used to save the measures to an external Excel file.

Locate ES and ED Boundaries
This option is accessed via “Analysis > Pressure-Volume Loop > Locate ES and ED Boundaries.” It locates
the ending systole and ending diastole boundaries in a selected area and inserts events into the graph marking
their location.
Realtime Display
Realtime display during PV Loop acquisitions involves setting up multiple views, toolbars and calculation
channels specifically tailored for PV Loop analysis. For convenience, a Pressure Volume Loop Quickstart
graph template is included with AcqKnowledge software. This template is configured for MP160/150
hardware and contains all above-mentioned setups, as well as two additional toolbars for realtime and postprocessing data display.
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PV Loop Quickstart showing graph data and Pressure vs. Magnitude XY data view

The above figure shows the additional toolbars present in the PV Loop Quickstart template, with toolbar
functions explained below.
·

Recent Values toolbar (outlined in blue)

The Recent values toolbar extracts the following measurements in real time from the cardiac calculation
channels 42-46. (Values are displayed during acquisition.)
Heart Rate (BPM)
Maximum Pressure (mmHg)
Minimum Pressure (mmHg)
Maximum Volume (mL)
Minimum Volume (mL)
·

Custom Button toolbar (outlined in red)

This toolbar provides quick access to the following functions during recording and in post-processing
Show PV Loop

Analyze Baseline

Displays the Pressure Volume Loop in XY view. Plot
shows most recent 6 seconds of pressure (X) vs.
volume (Y). Useful for viewing experimental effects or
determining catheter positioning.
Performs baseline analysis on selected graph data.
(A shortcut to choosing Analysis > Pressure Volume
Loop > Baseline Analysis.)

Show P vs. Magnitude

Displays the Pressure vs. Magnitude data in XY view.
Plot shows most recent 6 seconds of pressure (X) vs.
Magnitude (Y). Useful when positioning the catheter.

Show V vs. Phase

Displays the Volume vs. Phase data in XY view. Plot
shows most recent 6 seconds of pressure (X) vs.
phase (Y). Useful for viewing oscillating muscle
contributions in the signal.

Reset Display

Sets the display back to the default view.

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Full PV Loop Analysis
After all pressure volume data has been acquired, it may be analyzed in detail using the full static analysis
tool. This is accessed via Analysis > Pressure-Volume Loop > PV Loop Analysis. This tool enables the
examination of all loops within the selected area of the graph. PV Loop Analysis is a manual process where
outliers are defined both visually and through determining how different sets of loops affect defined
parameters. When activated, if End Diastolic and End Systolic events are already present in the selected data,
they will be used to define the loop boundaries. If none are present, new events will be defined using the
desired location method and preferences.
The full PV Loop dialog appears as follows:

The PV Loop Analysis dialog is divided into three basic panes.
·

Loop display (right pane)

·

Multiple loop measures (left pane)

·

Per loop measures (bottom pane)

The loop display shows an XY plot of volume vs. pressure. Individual loops are drawn using the waveform
plot color of the pressure channel. Overlaid in black on top of the loops are two best fit curves for end systolic
pressure volume relationship (ESDVR) and end diastolic pressure volume relationship (ESPVR). Use the
checkboxes under ‘Cycle’ to include or exclude individual loops in the plot analysis. Excluded loops will
appear as dotted lines and the actively selected loop will be outlined in blue. Excluded loops will also be
grayed out in the per loop measure display (bottom pane).
The loop display can be rescaled by clicking on the XY graph’s vertical and horizontal axis in the same
manner as in any graph, and then modifying the scaling parameters.
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Use the controls
horizontally, and zoom data.

in the upper left of the loop display region to autoscale vertically,

Multiple loop measures
Once a set of loops has been identified, various models are constructed showing ideal boundaries of pressure
and volume extents for varying cardiac cycles. Additional relationships between per-loop measures are also
extracted to help assess overall cardiac condition. Multiple loop measures include the following relationships
and controls:
ESPVR (End Systolic Pressure Volume
Relationship)

Theoretical maximum pressure for any given volume.

Type

Use to select the equation upon which to base the PV
loop curve fit: Linear or quadratic.

Ees

Index of overall myocardial contractility.

V0

Theoretical volume of loop at zero pressure.

EDPVR (End Diastolic Pressure Volume
Relationship)

Passive filling properties of ventricle, reciprocal of
ventricular stiffness.

PRSW (Preloadable recruitable stroke work)
Pressing
displays a plot showing linear
regression between stroke work and diastolic volume
between loops.
dpMax vs. EDV
Pressing
displays a plot showing maximum
change in pressure vs. end diastolic volume.
PVA vs. EDV
Pressing
displays a plot showing pressure
volume area vs. end diastolic volume.
PVA vs. ESP
Pressing
displays a plot showing pressure
volume area vs. end systolic pressure.
Other controls
Pressing
copies the loop-specific measures to
the clipboard.
Pressing
Excel file.

saves the loop-specific measures to an

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Per loop measures

The bottom pane of the analysis window contains a table display of individual loop analysis results. Each loop
occupies one row. Comparative measures are automatically updated upon any changes to included loops.
Each per loop measure is recorded in its own table column. The following hemodynamic measures are
reported:
Measure

Abbrev.

Formula

Units

Description

Heart rate

HR

BPM

Provides the heart
rate.

End systolic
pressure

ESP

mmHg

Blood pressure at
end of systole.

End diastolic EDP
pressure

mmHg

Blood pressure at
end of diastole.

Maximum
pressure

Pmax

mmHg

Maximum pressure
within the loop, left
endpoint exclusive
right endpoint
inclusive.

Minimum
pressure

Pmin

mmHg

Minimum pressure
within the loop, left
endpoint exclusive
right endpoint
inclusive.

Maximum
dP/dt

dPmax

mmHg / sec

Maximum change in
pressure within the
loop, left endpoint
exclusive right
endpoint inclusive.

Minimum
dP/dt

dPmin

mmHg/sec

Minimum change in
pressure within the
loop, left endpoint
exclusive right
endpoint inclusive.

Maximum
volume

Vmax

ml

Maximum volume
within the loop, left
endpoint exclusive
right endpoint
inclusive.

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Measure

Abbrev.

Formula

Units

Description

Minimum
volume

Vmin

ml

Minimum volume
within the loop, left
endpoint exclusive
right endpoint
inclusive.

End systolic
volume

ESV

ml

Volume at ES.

End diastolic EDV
volume

ml

Volume at ED.

Stroke
volume

SV

ml

Volume of blood
ejected.

Cardiac
output

CO

ml / minute

Amount of blood
pumped per unit time.

Ejection
fraction

EF

(none)

Percent of the end
diastolic volume
ejected during each
contraction.

Maximum
power

MaxPwr

Parallel
power

PlPwr

Stroke work

SW

Maximum cardiac
power within the loop,
left endpoint
exclusive right
endpoint inclusive.
With appropriate
factors may be
converted into Watts.

mmHg * ml

Work performed by
the ventricle to eject
the stroke volume.
Equivalent to the
area of the PV loop.

mmHg / ml

Measure of arterial
load for measuring
coupling between
heart and arterial
system.

where
Arterial
elastance

Ea

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Relaxation Constant
The relaxation constant, or tau, is a measure of the shape of pressure decay during ventricular relaxation. The
relaxation period is defined as the time of minimum change in pressure until the time when the pressure signal
has dropped under the EDP of the previous loop (or to ED if no previous loop is located). Multiple methods
are used to extract tau:
Method
Tau Weiss

Description

Units

Tau parameter in best fit of pressure data to:

(unitless)

where is the value of the LVP signal at the time of dP/dt
minimum and t is the time coordinate shifted such that t is 0 at the
time of dP/dt minimum.
Tau Logistic

Tau parameter in best fit of pressure data to the zero asymtote
logistic:

(unitless)

where t is the time coordinate shifted such that t is 0 at the time of
dP/dt minimum. Let us fix the initial endpoint such that
.
The logistic fit is computed by the best linear fit to the equation
where
Tau Glanz

and

, such that

.

The Raff-Glanz relaxation constant method is described in
(unitless)
http://circres.ahajournals.org/content/48/6/813.full.pdf. This
extends the Weiss method by allowing a non-zero asymptote to be
incorporated into the relaxation model such that the formula is:

To solve for the constant, the slope a of the best fit linear
regression of the series of points
resulting in
.
Tau Mirsky

Time interval between dP/dt minimum and when P drops below a
threshold of

.

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Comparative Measures
After multiple loop measures are extracted, the following additional measures may be extracted for each loop
to examine its relationship to the volume-relationship analyses of a set of loops and expected theoretical
baselines. These measures are based upon various multiple loop measures and should be recomputed any time
they are changed due to modifications to the set of loops included in the analysis: (See following page.)
Measure

Abbrev.

Pressure volume PVA
area

Description
Provides a measure of the total mechanical energy
produced by a ventricular contraction. From the set of
loops the ESPVR model provides the theoretical baseline
volume at zero pressure
. The PVA for a loop is then
determined from the following formula:

Units
mmHg * ml

where SW is the stroke work for the loop.
Potential energy

PE

Provides a measure of the elastic potential energy built
during the systole and stored in the ventricular wall at the
onset of relaxation. From the set of loops the ESPVR
model provides the theoretical baseline volume at zero
pressure V0. The PE for a loop is then determined from
the following formula:

mmHg * ml

That is the total mechanical energy minus the actual work
used to eject the stroke volume.
Efficiency

Eff

Maximum time
Emax
varying elastance

Provides the fraction of the total mechanical energy used to (unitless)
eject the stroke volume:

The normalized time varying elastance for an individual
loop is adjusted from the theoretical baseline volume at
zero pressure V0 and is given by the Suga and Sagawa
formula:

mmHg / ml

For a given loop, the maximum value of E(t) will occur
when pressure is highest and volume is lowest, or at the
time of ES:

This is also the slope of the line connecting V0 with ESP
within the XY loop plot1.

See the AcqKnowledge PV Loop Analysis video tutorial for a detailed demonstration of this feature.

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533

Licensed Functionality: Baroreflex Analysis

Baroreflex Sensitivity Analysis (BRS) functionality is available through an optional license available
with AcqKnowledge 5. The license must be authorized to access BRS functionality. To add a BRS
license to an existing MP System, please contact BIOPAC.
Baroreflex analysis measures the relationship between blood pressure and heart rate and is derived from
measures of blood pressure and ECG. The body regulates blood pressure to ensure proper blood flow to
organs underneath different conditions, e.g. supine to standing. Baroreflex sensitivity is a measure of how
quickly the blood pressure system compensates for changes in conditions, such as would be observed in
increasing or decreasing exercise. Variations in baroreflex sensitivity are useful as a comparative measure
between subjects and for assessing various external impacts.
The Baroreflex licensed functionality adds two additional measures to the Specialized Analysis >
Hemodynamics menu.

Baroreflex Sequence Analysis
Baroreflex Sequence analysis method produces measures of Baroreflex sensitivity (BRS) by automatically
locating time periods to analyze. Analysis results can be outputted to a graph channel and/or spreadsheet. The
output format is selected in the Hemodynamics global preferences.
The Graph channel output consists of two channels:
· “Local BRS – Ascending” with values set to the BRS estimate slope during the time periods of all
ascending Heart Rate and Systolic Blood Pressure sequences.
· “Local BRS – Descending” will have its values set to the BRS estimate slope during all time periods
of descending Heart Rate and Systolic Blood Pressure sequences.
Sequence Analysis Setup Dialog
Choosing the Baroreflex Sequence Analysis option produces
a dialog with the following controls:
Source channels:
·

ECG Lead II – Selects the ECG channel for detecting heart
rate

·

Blood Pressure – Selects pressure channel for extracting
systolic pressure
Sequential method parameters:
·

Min required cardiac cycles – Minimum number of
increasing or decreasing cardiac cycles required to initiate
a sequence analysis operation

·

Heart rate threshold – Minimum heart rate change
required to initiate a cardiac analysis operation

·

Systolic BP threshold – Minimum systolic blood pressure
change required to initiate a BP analysis operation
Analyze:
·

entire graph – The entire graph is analyzed for Baroreflex
measures

·

focus areas only – Only defined focus areas are analyzed
for Baroreflex measures

·

Show RR data in the graph – Outputs the RR interval as a graph channel

·

Show SBP data in the graph – Outputs the systolic blood pressure data as a graph channel

·
Note

Define events at sequence boundaries – Outputs events at the beginning and end of sequence
When “focus areas only” is selected, the entire graph is still scored for QRS events and systolic BP events, but
only defined focus area data is included in the analysis output.

Baroreflex Sequence Analysis description references can be found on page 536.
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Baroreflex Slope Analysis
The Baroreflex Slope analysis method uses linear regression to determine a measure of Baroreflex sensitivity
(BRS). The analysis output area displays the current BRS estimate and the slope of the best linear regression
fit to all of the cardiac cycles included in the analysis.
First, a source time interval is defined in the cardiac recording, generally located around regions of induced
change in blood pressure. The pairs of heart rate and systolic pressure within this time interval are extracted.
A linear regression of these coordinates is computed, with pressure as the x coordinate and heart rate interval
as the y interval. BRS is defined as the slope of the best fit linear regression, in units of ms/mmHg.
The slope method is useful when correlating with studies using this method, performing validations, or when
areas to be measured are very well known. This method can only be used on an area of selected data. If
attempted on unselected data, a dialog will appear prompting for data selection with the I-beam tool or a
defined focus area.
Baroreflex Slope Analysis description references can be found on page 536.
Slope Analysis Setup Dialog
Choosing the Baroreflex Slope Analysis option produces the following dialogs:

In the initial dialog, the ECG and blood pressure channels are selected (above).

The subsequent dialogs prompt for the highlighting and selection of a systole in the BP data (above).

Following systole selection, the arterial blood pressure events are scored. This can take some time, depending
on the width of the selected area (above).
An interactive plot (see next page) will appear, and displays the best present linear curve fit and the cardiac
cycles as points on an XY plot of systolic blood pressure versus heart rate.
Include or exclude points from analysis by checking or unchecking the numbered cardiac cycle boxes, or by
clicking on individual points while holding down the ALT key. When individual points are excluded or
included, the best linear fit will be automatically recalculated. The cardiac cycle table at the bottom of the
analysis window provides a tabular spreadsheet view, and includes:

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·
·

Active (checked) or hidden (unchecked)
Time on horizontal scale that cardiac cycle occurred

·
·

Heart Rate (HR) in milliseconds
Systolic Blood Pressure (SBP) in mmHg

Control

Description
The analysis output area in the upper left corner displays the current BRS estimate,
the slope of the best linear regression fit to all cardiac cycles included in the analysis.
Underneath it the present r value, goodness of fit, is displayed. These values are
updated dynamically if plot data is modified. The “Copy” button in this area copies the
text to the clipboard.
Copies the plot to a *.jpeg file.
Copies the plot data to the clipboard.
Autoscales the plot vertically.
Autoscales the plot horizontally.
Toggles between selection and zoom mode in the plot.
The “Pair” checkboxes allow for dynamic interaction with the individual heart rate
(HR) and systolic blood pressure (SBP) points (also referred to as pairs). This is
useful for visual identification and the exclusion of outliers.
·

Check/uncheck a box to show or hide a point, or click a point while holding
down the ALT key. Active points appear like this:

·
·

Hidden points appear like this:
Click on a point to highlight it. The highlighted point will also be selected in
the cardiac cycle table in the lower part of the screen. Highlighted points
appear like this:

Click the left icon above the cardiac cycle table data to save table data to an Excel
spreadsheet; click the right icon to save it to the clipboard.
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Baroreflex Sequence Method Description
The Baroreflex Sequence method is described in the following papers:
Kuusela, Tom; “On the Analysis of Baroreflex Sensitivity,” 2010.
Reyes del Paso, Gustavo A; “A program to assess baroreceptor cardiac reflex function,” “Behaviour Research
Methods, Instruments & Computers,” 1994, 26 (1), 62-64.
The sequence method first applies criteria to the heart rate and systolic pressure signals to locate time ranges
for analysis. Given a minimum number of samples n, a minimum rate of change in heart rate
, and a
minimum rate of change in systolic blood pressure
, the sequence of RR and pressure intervals is
examined for time ranges of rising and falling signals.
As indicated in section 2.5 of the Reyes del Paso paper, the pressure value at index u will actually be paired
with the heart rate value at index u+1. This one index delay is estimated to provide a better estimation of
BRS.
A rising time interval is defined as a time range where at least n consecutive data points
exhibit
and
, that is the heart rate and pressure
signals are increasing by at least their thresholds in between consecutive data points. These intervals must be
at least n samples but will be extended until the first sample where the signals either decrease or the increase
is underneath the appropriate thresholds.
A falling time interval is defined as a time range where at least n consecutive data points
exhibit
and
, that is the heart rate and
pressure signals are decreasing by at least their thresholds in between consecutive data points. These intervals
must be at least n samples but will be extended until the first sample where the signals either increase or the
decrease is less than the appropriate thresholds.
For each of these defined periods, the baroreflex sensitivity is computed using the slope method. That is, the
best linear fit for each individual sequence with pressure as the x coordinate and heart rate as the y coordinate
will be computed. As with the range identification, the source data used for this regression analysis will be
the pressure at index u paired with the heart rate at index u+1. The slope of this best fit line is the local BRS,
expressed in units of ms/mmHg.
The default values of the thresholds and count are defined in section 4 of the Kuusela paper as follows:
,
,
.
Because of the delay applied to the heart rate signal from the systolic pressure, the slope method may not be
directly used to validate local BRS measures from the sequential method.
Baroreflex Slope Method Description
The Baroreflex Slope method is described in the following papers:
Kuusela, Tom; “On the Analysis of Baroreflex Sensitivity”, 2010.
Patakas, D., Louridas, G. et. Al; “Reduced baroreceptor sensitivity in patients with chronic obstructive
pulmonary disease”, Thorax 1982; 37:292-295.

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Licensed Functionality: Actigraphy

Actigraphy Analysis functionality is available through an optional license available with
AcqKnowledge 5. The license must be authorized to access Actigraphy tools. To add an Actigraphy
license to an existing MP System, please contact BIOPAC.
Actigraphy is the long term study of accelerometer data correlated to subject activity. One of the primary uses
of actigraphy is to conduct sleep studies in which subjects are relatively motionless for extended periods. With
this AcqKnowledge licensed feature, long term data recordings acquired with accelerometers and BIOPAC’s
wireless BioNomadix, Mobita or BioHarness systems can be employed to empirically detect periods of
waking and sleep. Using Actigraphy, researchers have the ability to noninvasively measure a subject’s activity
level, and analyze the resulting data to assess sleep disorders and other sleep related criteria. These types of
studies usually span at least one day and often encompass several weeks of data.
The purpose of the AcqKnowledge Actigraphy analysis tool is to import and process accelerometer data from
graph data files and perform further data reduction into meaningful sleep metrics. A new file format
(actigraphy analysis file or *.act) allows multiple recordings to be stored and analyzed for individual subjects
across multiple time periods.
Actigraphy User Interface
A separate user interface and file format is employed for saved actigraphy analysis files within
AcqKnowledge. The actigraphy analysis (*.act) file retains the following information and settings:
· Subject name and description
· One or more activity records. Each activity record contains the calendar date starting time and activity
count data (1 minute epochs)
· Time used to separate days (default is 12:00 PM)
· Sleep onset interval detection setting
· Low activity level threshold
· High activity level threshold
· Previous analysis results for each day containing activity records (primary sleep onset, end, sleep
deprived measures, and activity level analysis)
· Number of visible activity level count plots
· Index of last visible tab of analysis results in the window (sleep vs. activity)
Creating Actigraphy Files
To create a new actigraphy analysis file, select “Create new actigraphy analysis” in the Startup Wizard, or
choose “File > New > Actigraphy analysis file.”

This creates a blank actigraphy analysis window similar to the example above.
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Importing Raw Accelerometer Data
AcqKnowledge records raw accelerometer data which must be imported and processed into activity counts for
use in actigraphy analysis.
To import data from an external accelerometer sleep study file, click the
toolbar button in the Actigraphy
Analysis window, navigate to the raw data file’s location and choose “Open.” Once the data is imported, it
(along with the extracted sleep and activity level measures) can be saved as an actigraphy analysis (*.act) file.
After accelerometer data is imported into the main Actigraphy window, (or after an existing actigraphy
analysis file opened) the raw data appears in graph format in the upper “activity count plot” area of the
window, with all data correlating to a navigable and scalable horizontal time scale. The default scaling is for a
24 hour period, but data can be zoomed by clicking and dragging over any portion of the activity plot data.
During zoom, the rescaled clock time is displayed in red at the right border of the
zoomed area. (Right)
The activity count plot area displays activity data for the subject. Its overall vertical
area is split up into a variable number of plots, controllable within the Analysis Settings (see page 540). Each
plot represents 24 hours of activity data. The leftmost plotted position is the starting time where time periods
are to be split. The vertical label for the plot is set to the calendar date at that starting time position and the
horizontal axis shows time of day in a 24 hour time format. Every time the window is first opened, data is
horizontally scaled to show all 24 hours. Data plotting is vertically autoscaled so the bottom of each
individual plot is zero and the top of each plot area is the maximum activity count within the entire data set.

Following data import, multiple measures are extracted and displayed in column format in the lower pane of
the Actigraphy window. This pane is divided into two tabbed categories, Sleep Analysis and Activity Levels,
with each category displaying its own set of measurements.

All extracted measures can be exported to a text (*.txt) or Excel spreadsheet format.
Opening an Existing Actigraphy File
To open an existing actigraphy analysis file, choose File > Open in the analysis window, navigate to the *.act
file location and click “Open.”
Below: Actigraphy Analysis window populated with accelerometer sleep data (Max OS version).

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The following table explains the various menus, options and controls in the Actigraphy Analysis window:
Item

Description
File > Open – displays File Open dialog for navigating to existing
*.act (actigraphy) files.
Open Recent – displays most recently opened *.act files.
Export Activity Count Data – saves all raw accelerometer data to a
text format.
Export Sleep Analysis Spreadsheet – saves all sleep derived
measures to a spreadsheet format.
Export Activity Level Analysis Spreadsheet – saves all Activity Level
Analysis measures to spreadsheet format.
Edit > Copy Sleep Analysis to Clipboard – Exports sleep derived
measures to clipboard.
Copy Activity Level Analysis Spreadsheet – Exports activity level
analysis information to clipboard.
Analysis settings – opens the Actigraphy Analysis Settings setup
dialog. See details on page 540.
Add/Import – use to navigate to and import external accelerometer
data file into the Actigraphy Analysis “activity plot” window.
Save – saves any changes to the imported data file and Actigraphy
window settings.
Reanalyze – manually reanalyzes data to locate primary sleep
periods and repopulates the derived measure table.
Settings – opens the Actigraphy Analysis Settings setup dialog. See
details on page 540.
Field for entering text identifying Subject.
Field for entering text describing pertinent study information.
Autoscale – horizontally autoscales the activity plot data back to the
original 24 hour period.
Scaling – time scaling button. Opens setup dialog for adjusting the
time range of the Actigraphy window’s plotting area.

Tab for displaying sleep derived measures extracted from the data
file under analysis. For a list of specific sleep derived measures, see
page 542.
Tab for displaying activity level measures extracted from data file
under analysis. For a list of specific activity level measures, see
page 542.
Copy text – copies sleep derived measures to clipboard. (Performs
same function as Edit > Copy Sleep Analysis to Clipboard).
Export spreadsheet – exports sleep derived measures to a
spreadsheet. (Performs same function as File > Export Sleep
Analysis Spreadsheet).
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Actigraphy Analysis Settings
As stated in the previous section, choosing “Edit > Analysis settings” (or clicking the
toolbar button)
generates the Analysis settings setup dialog. This is where important parameters are selected and applied to
the Actigraphy Analysis file.

The following table describes the various parameters available in this dialog.
Actigraphy Analysis Settings Controls
Item

Description

Time Zone
(current file only):

Indicates the time zone in which the time data is being analyzed. This varies on a file-byfile basis and is set to the computer's time zone when the file is first created.

Separate 24h
periods at:

Provides the cutoff where data is split into new 24 hour blocks for analysis. Only one
primary sleep period is allowed per block, so this should be set to a time when the
subject is expected to be awake. Default setting is 12:00 PM.

Sleep onset
interval:

Selects the time interval for detecting onset of sleep. 10, 15, or 20 minute intervals are
available. Default value is 20 minutes.

Sleep end
interval:

Selects the time interval for detecting end of sleep. 10, 15, or 20 minute intervals are
available. Default value is 20 minutes.

Visible activity
count plot:

Selects the number of 24 hour activity plots to display in the actigraphy analysis window.
Default value is 3.

Low/Med activity
threshold level:

Threshold level used for separating the low and medium activity bands. Default value is
50.

Med/High activity
threshold level:

Threshold level used for separating the medium and high activity bands. Default value is
300.

Sadeh scoring
algorithm:

See below for separate explanation of this algorithm and associated settings.

Plot colors:

Clicking either option generates a colorwell for modifying the background or sleep period
plot colors.

Save as defaults:

Saves any modified settings as a new default for subsequent Actigraphy analyses.

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Sadeh Scoring Algorithm for Wake/Sleep Classification
After the activity count has been extracted from the accelerometer data, each data epoch is classified as either
a sleep or a wake interval based upon a formula cited in a widely-acclaimed sleep study publication,
“Activity-Based Sleep-Wake Identification: An Empirical Test of Methodological Issues (1994)” by Avi
Sadeh, Katherine A. Sharkey and Mary A. Carskadon.
Sadeh (1994) proposed one of the classic formulas referenced in multiple papers. Given the activity count
sequence A, this heuristic defines the “probability of sleep”.
The following table contains derived measures with formulas as described in Table 1 of Sadeh (P. 202):
Measure Description

Abbreviation Formula(s)

MeanWindowed mean of overall activity count in
W-5-min the present interval and the 5 minutes prior
to and after the present interval.

M

SD-last
6 min

Standard deviation of a 6 minute activity
window including the present interval.

S

NAT

Number of intervals within an 11 minute
window centered on the current interval
having activity counts within this example
range [50, 100).

N

LOG-Act Natural logarithm of the current activity
count plus 1.

L

Given these source parameters, the probability of sleep PS is defined on page 202 of Sadeh (1994) as:
If PS is negative, the minute at interval i is classified as a waking interval. If PS is zero or positive the
interval is classified as a sleep interval.
The default scoring algorithm can be modified if desired in the Sadeh scoring algorithm portion of the
Actigraphy Analysis setup window. All fields for described measures are editable.

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Sleep Derived Measures (Sleep Analysis)
After the primary sleep period has been located, it will be further subdivided into “bouts.” A “bout” is a
contiguous section of data that has been classified as either wake or sleep.
Once the primary sleep period has been located in the data file, the following measures are extracted:
Measure

Description

Date

This is the calendar date for the start of the primary sleep period. For most normal
sleep periods the ending time will be assumed to be the next day; the date is for the
start of the sleep cycle.

Sleep Onset

Starting time of the primary sleep period.

Sleep End

Ending time of the primary sleep period.

Total Sleep

Total duration of primary sleep interval.

Sleep Time

Number of minutes in the primary sleep interval classified as sleep.

% Sleep

Total percentage of the sleep period that was spent in the sleeping state.

Wake Time

Number of minutes within the primary sleep interval classified as waking.

% Wake

Total percentage of the sleep period that was spent in the waking state.

WASO (Wake
After Sleep Onset)

Number of minutes after the initial sleep onset period to the first epoch classified as
waking.

Sleep Bouts

Total number of sleep bouts within the primary sleep period.

Mean Sleep Bout
Len

Average length of a sleep bout in minutes.

Wake Bouts

Total number of wake bouts within the primary sleep period.

Mean Wake Bout
Len

Average length of each wake bout within the primary sleep period.

Activity Level Measures
The following measures are extracted from Activity Level Analysis.
Measure

Description

Date

Calendar date and starting time of the period being analyzed.

Total Low

Total low activity time for the entire period in minutes.

% Total Low

Percentage of the entire period spent in the low activity state.

Total Med

Total medium activity time for the entire period in minutes.

% Total Med

Percentage of the entire period spent in the medium activity state.

Total High

Total high activity time for the entire period in minutes.

% Total High

Percentage of the entire period spent in the high activity state.

awakeLow

Time spent in a low activity state when subject was not sleeping.

awakeLowPercent

Percentage of time subject was in a low activity state when not sleeping.

awakeMedium

Minutes in the medium activity state while subject was not sleeping.

awakeMedPercent

Percentage of time subject was in a medium activity state when not sleeping.

awakeHigh

Minutes in the high activity state while subject was not sleeping.

awakeHighPercent

Percentage of time subject was in a high activity state when not sleeping.

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Actigraphy Specialized Analysis

The Specialized Analysis menu contains options for performing Actigraphy import and analysis on any
currently-open AcqKnowledge data files. These options are defined as follows:
· Add to Existing Analysis – allows a channel of data in the graph to be added to a pre-existing actigraphy
analysis. This operation may be used often after importing or recording the next set of data from a subject.
To add to an existing analysis:
1. Open the graph containing the accelerometer data to be added to the existing Actigraphy analysis file.
2. Choose Specialized Analysis > Add to Existing Analysis.
3. If the graph contains multiple channels, select the channel containing the accelerometer data to be
added and click OK.

4. Choose the existing Actigraphy (*.act) analysis file to add the new data to and click “Open.”

Note

.
If multiple Actigraphy analysis files are open, a prompt to select the desired file will appear:

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· Create New Analysis – Imports and performs Actigraphy analysis on the currently-open AcqKnowledge
graph.
To create a new Actigraphy analysis from the currently open file:
1. Choose Specialized Analysis > Create New Analysis.
2. If the graph contains multiple channels, a prompt will appear to select the desired channel for import.

3. In the Actigraphy analysis window, choose File > Save as to save the new Actigraphy (*.act)
analysis.
Watch Actigraphy Tutorial Screencast for a detailed demonstration of Actigraphy.

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Chapter 29

BioHarness Bluetooth

A specially licensed version of AcqKnowledge is included and required when used with BioHarness.
Data Acquisition and Analysis with BIOPAC BioHarness™

IMPORTANT NOTE: In AcqKnowledge for BioHarness
§ BioHarness menu replaces the MP menu
§ Analog channels can be turned on/off but not changed
§ Other functionality remains the same

BioHarness™ users should see the BioHarness User
Guide available under the Help menu and installed to the
User Support folder in the program folder.
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Chapter 30

Stellar Telemetry

Stellar Telemetry Control interface for existing Stellar Small Animal Telemetry System & Implants is
available through optional licensing available with AcqKnowledge 5. The license(s) must be
authorized to access functionality for the specified number of implants. Please contact BIOPAC to
discuss licensing options.

Stellar Telemetry System
The Stellar Telemetry System wirelessly acquires and logs physiological data from single or multiple animal
subjects. The system consists of a small implantable recording device with an antenna and USB base station
for communicating with the implanted units. AcqKnowledge software is used to configure Stellar experiments
and analyze blood pressure, ECG, temperature, and accelerometer data imported from the logging sessions.
Specific data recording parameters, such as the desired signal type, recording schedule, duration/repetition
interval, and selection of animal subjects are set up beforehand in AcqKnowledge, whereas the import, display
and analysis of resulting data are performed following the logging session. Stellar Telemetry is a licensed
feature of AcqKnowledge, and activated with a BIOPAC USB License Key. The number of animal units
(allowable animal subjects controlled per experiment) is determined by the specific quantity of animal units
purchased in the software license.
Stellar data can be recorded in Scheduled mode (experiments are set up in a “scheduler” window and the
logged data downloaded into an AcqKnowledge graph when the recording is complete), or Realtime mode,
where data is recorded in “real time” directly into AcqKnowledge.
This chapter describes how AcqKnowledge software is used with the Stellar Telemetry System. For
information on the Stellar System hardware (setup of implantable devices, antenna and base station), see the
Stellar Telemetry User Guide. For Access Point hardware driver installation and troubleshooting, see the
Access Point Configuration Guide.
Before beginning: It is important to note that the Stellar Telemetry System may lose communication with the
Access Point if the computer is allowed to go to sleep, resulting in a loss of data. To prevent this from
occurring, disable the computer’s sleep mode prior to conducting a Stellar experiment. To disable, go to
“Control Panel” > “Power Options” and set the “Change when the computer sleeps” option to “Never.”

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Stellar Preferences
The Stellar Preferences pane offers options for setting the record mode to Scheduled or Realtime. Upon first
launch of AcqKnowledge, a dialog for setting these preferences will appear.

Stellar preferences can always be changed or set up later in AcqKnowledge by accessing them in Display >
Preferences > Stellar Telemetry. If the Recording Mode is changed in Stellar Preferences, the modified setting
will be applied the next time AcqKnowledge is launched.

Stellar Realtime Mode
In AcqKnowledge 5.0.3 and higher, Stellar has been extended to include Realtime mode, which enables data
to be streamed directly to AcqKnowledge from the Stellar unit without having to schedule or download an
acquisition. Selecting Realtime mode after initial AcqKnowledge launch, brings up the following dialog:

The following controls are available in Realtime mode setup:
Access point:

Lists all recognized access points and COM ports..

Animal units:

Lists animal unit configuration files in the Stellar directory that are compatible with the
selected access points.

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Access points should be configured prior to using Stellar units. Please refer to the Stellar Access Point
Configuration document for this information.
· Animal units previously connected for Realtime data acquisition will not appear in the Animal unit
list.
· Only one animal unit may be selected from the list at a time.
After selecting an animal unit from the list, the following prompt will be displayed:

As many animal units can be connected as are allowed by the Stellar license. Animal units are provided along
with the Stellar license. (In most cases, 4.)
Configuration files for animal units must be stored within the Stellar configuration directory.
Data acquisitions for Realtime mode can be configured in AcqKnowledge by selecting Animal Unit > Set Up
Data Acquisition, similar to using AcqKnowledge with other supported hardware.
Note that Stellar Animal Unit data acquisition settings are limited to the following items:
· Channels
· Length/Rate
· Event Marking
The standard 16 analog and calculation channels are available for Stellar animal units. Digital channels are
not supported.
As previously stated, Realtime data acquisition enables recording of Stellar data directly into AcqKnowledge
using the standard controls found in AcqKnowledge graphs. (Start/Stop button, standard toolbars,
measurements, menus, etc.)
To set up and use Stellar in Scheduled mode, please proceed to the next section.

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Stellar Experiment Interface in AcqKnowledge
The following section refers to the Stellar “Scheduled” mode preference setting. In Scheduled mode,
experiments are set up in advance and the logged data downloaded into an AcqKnowledge graph when
recording is complete.
Stellar experiments are configured in AcqKnowledge in a dedicated experiment setup window. Launch the
experiment setup by selecting “New Stellar Experiment” or by choosing File > New > and selecting “Stellar
Experiment” in the “Choose type” option dialog.

Stellar Experiment Setup Window

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Description of the Stellar Experiment Window Controls
CONTROL

DESCRIPTION

Visual Calendar view

This is the calendar view in the left pane. Interactive
calendar indicating date/time of scheduled logging
sessions. Scheduled sessions are highlighted with
orange squares. Double-clicking a date defines a new
session. If a session has already occurred, doubleclicking the date launches and displays AcqKnowledge
graph files containing data acquired during that date’s
session. The month display can be advanced or
regressed by using the arrows to the right and left of the
current month display or by clicking on the month and
selecting from the list (right).

Graphical Day view

Scrollable 24 hour representation of the selected calendar day. Vertical bars
represent scheduled session intervals, with one “session bar” per scheduled
session. Double-clicking an empty time slot creates a new 60 minute session.
Single-click an existing session bar to select and highlight it. While a session is
running, the active session bar becomes shaded in black, indicating elapsed
time of the session in progress. The session start/end time can be adjusted to
the nearest 15-minute interval by dragging the edge of a selected bar upward or
downward. For more precise scheduling, adjust the start/end time using the
navigation arrows in the Start and Stop fields, to the right of the Day View.
Graphical Day View Buttons:
Use the “Add Session” button to quickly add a session to the schedule. (This
performs the same function as double clicking on a date in the Visual Calendar
as described above.)
Graphical Day View Contextual Menu:
Graphical Day View supports the following contextual menu items. To display
the contextual menu, right-click a session bar in the Day View.
· Delete: Removes the selected session
· Clone: Shortcut to the “Clone Session” setup dialog (see below)
· Delete cloned sessions: Removes cloned sessions.
Zoom Controls:
Use the “+” and “-“ buttons to zoom in or out on the graphical day view grid for
optimal viewing of scheduled sessions.

Start Acquisition
Abort Acquisition

Stellar data logging will begin with the next scheduled session. Scheduled
sessions do not start automatically. They must first be initiated using the “Start
Acquisition” button.
During an active logging session, an “Abort Acquisition” button becomes
available, which enables the session to be ended prematurely if necessary. The
session can then be aborted (cancelled) or the available data downloaded (see
below).

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Allows sessions to be downloaded manually at any time. This button is
only visible while a session is in progress.

The manual download window consists of the following elements and
controls:
Session List: This list displays all available sessions, status, scheduled
start and stop times and animal units. The “Download” checkbox selects
a session for manual download.
Refresh List: Updates status of listed sessions.
Get Data: Activates downloading process of selected sessions.
Session Details Controls

Sets specific scheduling parameters for the session.
Start: Displays and adjusts the start time of the scheduled session.
Stop: Displays and adjusts the stop time of the scheduled session.
Start time offset – Start in: Allows the session to be automatically
scheduled to start two minutes (or more) from the present time. Clicking
Apply schedules the selected time offset.
Time align all animal units: Sessions of all animal units will be started
at the same start time. The start time is calculated based on the “Start”
value plus 15 seconds for every animal unit in the session. Time aligned
recording is useful when external stimuli or dosing is occurring at a
known fixed clock time.
Record – of data: Sets the duration of the data recording.
every: Sets the repetition interval of scheduled recordings.
Sample rate: Sets the data acquisition rate in samples per second (Hz).
Available sample rates are 100, 200, 500 or 1000 Hz, the default being
200 Hz.
Signals: Selects the physiological signals to acquire during the session,
with option to show or hide the continuous battery voltage level.
Available signals are Blood Pressure (2), ECG (2), Temperature and
Accelerometer (X, Y, & Z axes).
Summary accelerometer axis data monitored: Checking this option
combines the three axes accelerometer data into a single integrated
accelerometer signal.
Set input signals for all checked units: Use this option to apply the
same input channels to all selected animal units. Signals not supported
by a particular animal unit will be ignored. Using this option will generate
a confirmation prompt similar to the following:

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Clone Session button

Configure multiple instances of a given session without manually
repeating the session setup. This is useful when an experiment
extends over many weeks or months and the sessions need to be
frequently repeated.
Selecting “Clone Session” launches the following setup dialog,
allowing selection of session repetition intervals and duration.

Animal Units

An “Animal Unit” refers to a specific Stellar transmitter implanted
in an animal subject. This option controls which available animal
units are to be included in the session. The displayed information
includes unit serial number, animal ID, and last known status.
Specific Access Point and Animal Unit signal strengths are also
indicated under the AP RSSI and AU RSSI columns (not
depicted). Ranges of 0-10 indicate poor signal strength, 10-15
fair, 15-20 good, and +20 excellent.
“Pings” the animal units and provides feedback on the
communication status. “OK” indicates a successful
communication. “Error” indicates a failed communication with an
animal unit. Specific Access Point and Animal Unit signal
strengths are also indicated under the AP RSSI and AU RSSI
columns (not depicted). Ranges of 0-10 indicate poor signal
strength, 10-15 fair, 15-20 good, and +20 excellent.
Possible causes of communication failure:

Test Communications button

·
·

Animal unit may be out of radio range of the access point.
Animal unit may be in use for a recording by another
access point.

·

Animal unit may be frozen and require a magnetic reset.

·

Animal Unit battery may be dead (in which case the unit
must be replaced).

Automatically download data at end of
- recording session (accurate timing)
- recording of x passes (flexible schedule)

If “recording session (accurate timing)” is selected: After the final
session is completed, all data is automatically downloaded from
active animal units into the output directory.
If “recording of x passes (flexible schedule)” is selected: The data
will automatically be downloaded into the *.acq graph following
completion of the number of recording passes entered into the
“passes (flexible schedule) field. The remaining passes will be
downloaded at the end of the full session.
NOTE: Using this option may break the scheduled timing.

If only one recording pass is entered in the flexible schedule field, the following dialog will be displayed once
following application launch:

During a flexible schedule download, a Flexible Data Downloading Control Panel window is displayed during
the recording and download process. See page 559 for an overview of this window.
Chooses directory where AcqKnowledge graphs containing
Set Output Directory button
downloaded data will be stored. If undefined, the default path is
the user's Documents directory.

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Further Information about Flexible Data Download
· The recording session may include multiple animal units and various input signals per unit.
· All signals from all animal units will be combined into a single graph file – one graph
channel per signal.
· Data from every recording pass will be added to the graph file as appended segments with
appropriate labels and timestamps.
Stellar-specific Setup Window Menus
File Menu
> New Experiment

Creates a new experiment window.

> Open Experiment...

Displays a “File > Open” dialog for opening a Stellar
experiment file from disk.

> Open Experiment for downloading

Opens a Stellar experiment file from disk (*.ase format)
and activates manual data downloading based on the
settings stored with experiment file.

> Save Experiment

Saves any changes to the current experiment.

> Save Experiment As

Displays a “Save As” dialog allowing the experiment to be
saved to a new file on disk.

> Close

Closes the current experiment window, prompting to save
any changes to the experiment.

> Quit

Exits AcqKnowledge.

Session Menu
> New Session

Adds a new session to an experiment on the date
selected in the Calendar view.

> Clone...

Displays dialog for cloning the selected session.
(Performs same function as “Clone Session” button.)

> Delete

Deletes a selected session after a confirmation prompt.
Disabled if no session is selected.

> Delete cloned sessions

Deletes a selected cloned session after a confirmation
prompt. Disabled if no cloned session is selected.

> Start Acquisition

Reschedules a selected session to start immediately.
Dimmed if an acquisition in progress or no session is
selected.

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Animal Units Menu
> Add New Animal Units...

The License CD contains the purchased animal unit
configuration files. To add an animal unit:
1. Choose “Add New Animal Units.”
2. Navigate to the License CD and select the file(s) with
a *.set extension.
3. Click “Open.”

> Test Communications...

Performs the same function as the “Test Communications”
button in the setup window.

> Manage Animal Units...

Use to select or modify the animal unit configuration.
Animal Units: Lists available animal units
Details > S/N: Displays serial number of currently selected
unit.
Animal ID: Editable field for displaying additional information
about animal unit, name, etc.
Calibration Barometric Pressure: Indicates barometric
pressure at the time the animal unit was calibrated.
Firmware: Displays animal unit firmware version.
Channels count: Displays unit’s available input channels.
Type: Displays animal unit information.
On-board memory: Displays installed memory of animal unit.
Cut-off voltage: Displays lowest battery voltage allowable to
run data acquisition.
Channels: Displays list of animal unit input channels.
Test…: Performs short (2-sec) test acquisition of the selected
unit
Status: Displays status information of the selected animal
unit. This option is only available between recordings. Status
results are not returned during an active recording.
HW config: Displays hardware configuration of selected unit.
This option is only available between recordings.
Remove: Removes selected animal unit from the list.
Add New Unit: Performs same function as “Add New Animal
Units” in the Animal Units menu.

Access Point Menu
> Get Info...

Displays current access point information, including serial
number, communication status, and current barometric
pressure.

> Change Access Point...

NOTE: This functionality is not currently supported. Only one
access point may be used with the software at a time.

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Tools Menu
> Stellar Preferences

Set the following important parameters in the Stellar
Preferences dialog:
Path to Stellar Setting Folder – Displays the path location of
Stellar access point and animal units setup files.
Browse – Selects the path to location of Stellar access point
and animal units setup files.
Path to Barometric Pressure Log file – Displays the path
location of the “Stellar_BaroPressure.log” file.
Browse – Selects the path to location of the
“Stellar_BaroPressure.log” file.
Clear BP file – Used to delete the Barometric pressure log
file.
Default path to save data files – Displays the default
location of Stellar data files.
Browse – Opens a browse window for setting an alternate
data file path.
Set default – Resets the filepath to the original default file
path. (User’s Documents folder)
Show Log View – Displays the Journal log view by default for
new experiments to show real-time experiment information.
(This may also be controlled via the Options menu in the
Scheduler window.)

> Show/Hide Log (Journal)

When “Show” is selected, real-time experiment status
information is displayed at the bottom of the Scheduler
window. This field resembles the AcqKnowledge Journal, but
is not user-editable. (See below example.)

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> Print Log

Opens a dialog for printing contents (or a selection) of the log
and for setting the desired print parameters.

> Copy Settings to Clipboard

Copies experiment settings to clipboard in text format.

> Import data from animal units

Downloads data from selected animal units into an
AcqKnowledge graph.
1. Select the animal units for data import via the
Animal Unit checkboxes.
2. Select the option to create separate AcqKnowledge
graphs for each selected animal unit or to merge all
animal units into the same graph.
3. Choose the sample rate at which the animal data
unit was acquired. This information is critical for
accurate display of the imported data.
4. Click “Download.”

> Import data from backup file

To protect the animal unit data, AcqKnowledge creates a raw
data backup file every time data is downloaded from the
selected animal unit(s). Backup files are located at predefined folder titled “%temp%.” Backup file names appear in
the following format:
STELLAR_YYYY_MM_DD_HH_mm_ss.txt.
Use this menu item to select backup file(s) and import the
data into AcqKnowledge.

> Real time data preview

This option allows for the previewing of plotted data prior to
initiating the actual experiment, and is helpful for configuring
the real time data recording and plotting. Parameters such as
Animal Unit, input signals, sample rate and duration can be
modified and the result plotted in real time after clicking the
“Start” button.
Data preview graphs can be autoscaled vertically while in
progress for enhanced data display. See the following page
for a full explanation of the Real time data preview options.

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Real time data preview setup options
Animal
Units

Displays the animal units available for preview. Only one animal unit at a time may be selected.

Channels

Displays the channels available for preview. Multiple channels may be selected.

Duration

Sets the length of preview in seconds.

Unlimited

Choosing this option allows the preview to run until manually stopped.

Rate

Use this option to select the sample rate for the data display. Sample rates of 100, 200, 500 and
1000 s/s are supported.

Save data

Use this option to choose a path to save the preview data to a *.txt file format. This option is
available when the duration is set to seconds. It is not supported for unlimited data previews.

Time
range

Use this option to set a horizontal scale range for the data preview display. (Horizontal
autoscaling is not supported in the preview graph.)

Start

Toggles between Start/Stop of data preview. When clicking Start/Stop it may take a few
seconds for the application to respond before starting or stopping the preview. When this
occurs, a “Please wait” dialog will appear. Avoid repeated mouse clicking within the application
window during this time or AcqKnowledge may become temporarily unresponsive.

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Real time data preview in progress after clicking “Start”
Animal units and Channels selected for Real time data preview are displayed as in a moving graphical format
while the preview is in progress. The preview signals can be autoscaled vertically but not horizontally, so it is
important to set the horizontal display in the “Time range” field prior to clicking “Start.” Enhance the preview
vertical display using the “Zoom In” or “Zoom Out” buttons. (2x zoom is supported.)
Real time data previews set to duration of seconds can be saved in *.txt file format to a user-defined location.
These saved files can be reopened in AcqKnowledge using the following steps:
1. File > Open and choose “*.txt, *.csv” as the files of type.
2. Navigate to the saved preview *.txt file and open using the following import settings:

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Flexible Data Download Control Panel

When the flexible schedule download option is selected, the above control panel is displayed while the
recordings and downloads are in progress. In addition to Access Point, Start/End Time, Graph Filepath and
clock time (upper right), the following parameters are displayed:
Animal Unit

Displays the number of animal unit(s) used in the
recording and downloading process.

Status

Displays whether animal unit is recording or in idle
status for downloading.

Recording

If animal unit is in Recording state, this shows
elapsed time of recording. If animal unit is in
Downloading state, this shows estimated time until
next recording pass.

Downloading

If animal unit is in Downloading state, this shows
elapsed time of download. If animal unit is in
Recording state, this shows estimated time to next
download.

Command Status

Shows status of last command sent to animal unit.
OK – command successfully executed.
Error – command failed.
Busy – command could not be sent because
communication channel is busy.

Memory in use (Kbytes)

Displays estimated memory usage of animal unit.

Counter

Displays number of completed and requested
recording passes for the current recording session.

Abort Experiment

Cancels all activity and ends experiment.

Close

Closes control panel window. Dimmed while
recording session is in progress.
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Running a Stellar Experiment
The example below is a guide to scheduling and conducting a Stellar experiment. These steps assume that the
Stellar hardware is set up correctly, and successful hardware connection between the Access Point and the
Animal Unit has been established. For hardware setup instructions, see the “Access Point Configuration and
Troubleshooting Guide.”
1. In AcqKnowledge, launch a new experiment.
(File > New > Stellar Experiment). This will
launch the Calendar window. A “Create new
stellar telemetry experiment” option is also
available in the AcqKnowledge Startup
window.

2. Prior to session setup, it is important to test
the Animal Unit communications status.
3. Click “Test Communications.”
4. Click “Yes” to the resulting dialog to continue.

5. Enable the check boxes corresponding to the
Animal Units to be used during the session and
click “Start Test.”
· A successful connection is confirmed by a
Test Status of “OK.”

6. The Calendar will default to the current date. If
the session is to be scheduled for a future date,
click on the desired date to highlight.
7. Choose a time for the experiment to start by
double-clicking in the Graphical Day
View region or by clicking the “Add Session”
button. This highlights a one-hour time period
with a series of squares called a “session bar.”
Each black and white square represents a 15minute time block.
· Hold left mouse button down to drag
the highlighted session bar to a
different location on the time scale.
The bar can be dragged up or down in

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15-minute increments or greater.
·

·

Position the left mouse button over the
session bar border and drag the arrow
cursor up or down to adjust the session
length. 15 minute increments or greater
are supported.
Conversely, the session length can be
more precisely modified by using the
spinners in the “Start/Stop” fields.

8. Select the recording length, repetition, sample
rate, and the signal types to be acquired.

9. Select Animal Units to be included in the
session by checking the corresponding boxes.

10. Once the recording parameters and Animal
Units are selected for the session, click “Start
Acquisition.”
11. Choose a file name for the experiment.
· The session will start at the scheduled
time and display the imported data in
an AcqKnowledge graph when
concluded.

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Import and Display of Stellar Data in AcqKnowledge
Following completion of a scheduled experiment, the logged Stellar data is downloaded to an AcqKnowledge
graph for review and analysis. Stellar-optimized analysis tools enable selective viewing and spreadsheet
output of recorded data for all selected animal units.
· Physiological signals extracted from the Stellar experiment are imported into an
AcqKnowledge graph and displayed as separate channels.
·

Repeated recordings (for example, 15 seconds every 15 minutes for the duration of the
session), are displayed as appended segments.

Saving Graphs and Settings from Stellar Experiments
It is important to note that Stellar experiment data files and Stellar experiment settings are stored separately.
Graphs containing data imported from Stellar experiments are in standard AcqKnowledge *.acq or *.gtl
format, and like all AcqKnowledge graphs, are opened and saved via the main application window “File”
menu.
Conversely, Stellar experiment settings and parameters are saved and opened via a separate File menu in the
Scheduler window. (See Stellar-specific Scheduler menus on pages 3-5.) Stellar experiments are saved in
*.ase (AcqKnowledge Stellar Experiment) format and contain the following settings:
· Access Point ID
· Output directory
· List of Animal Units with their last known status
· List of Animal Unit IDs included into the session
· Start Date/Time
· End Date/Time
· Single Record duration: value and time units
· Interval between recordings: value and time units
· Sample rate in Hz
· Input signals for the recording session: (Blood Pressure, ECG, Temperature, Accelerometer, Battery
voltage)

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Stellar Analysis in AcqKnowledge
After the logged Stellar session is downloaded into an AcqKnowledge graph, data can then be extracted and
examined using the Stellar specialized analysis tools. Access these tools by using the Analysis > Stellar menu
option in the main graph window.

Analyze Stellar Data

Creates a spreadsheet output of combined data from
selected animal units included in the session. All
measurements are selectable in the Stellar Analysis
preferences and include the following:
· Delta T (duration of each recording
interval)
·
·

Mean Systolic Pressure
Mean Diastolic Pressure

·
·
·

Mean Mean Pressure
Standard Deviation Systolic Pressure
Standard Deviation Diastolic Pressure

·
·

Mean Pulse Pressure (systolic pressure
minus diastolic pressure)
Standard Deviation Pulse Pressure

·
·

Mean Heart Rate from Pressure
Mean Heart Rate from ECG

·
·
·

Standard Deviation Heart Rate from ECG
Standard Deviation Heart Rate from BP
Mean P-P from ECG

·
·
·

Standard Deviation P-P from ECG
Mean Temperature
Battery

·

Barometric Pressure (mmHg)

·

Activity Sum (measures overall activity
during the entire recording segment by
summing all activity count data)
Note that outputted measurements are dependent
upon the signal types selected in the setup window.
If the session includes multiple animal units, the rows
extend outward to accommodate all subjects and
displays measurement data for each.
Show average ECG

This option averages the ECG signal and provides
the average ECG waveform for the entire acquisition
period. When selected. AcqKnowledge performs an
ensemble average ECG complex for each recording
session and then overlaps them to obtain the
average.

View Signals for Specific Animals

The following parameters can be adjusted using the
“View Signals” controls:
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The above option selects the animal units to be
included in the graph. Unchecking an animal unit
hides the graph channel containing the deselected
unit.

Show or hide the various signal type channels
acquired during the session for a better view of a
particular signal.
Preferences > Stellar Analysis: Select measurements to
extract

Use this option to select or deselect the
measurements to be included in the analysis.

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Use this preference to enhance the accuracy of heart
rate ranges extracted during analysis. This option
(based upon the AcqKnowledge Find Rate
windowing algorithm,) can help improve results by
reducing the standard deviation of BPM values falling
outside of the defined range. These results appear as
selected measurements in the “Analyze Stellar Data”
spreadsheet output.
In general, adjusting the maximum BPM to a lower
value helps prevent excessive motion artifact from
adversely affecting the heart rate results.
This preference is also useful for tuning the heart rate
“window” for a specific subject type and experimental
condition, or in cases where the 700 BPM default
maximum heart rate may not be applicable.

To set the Heart Rate Range preference for an
experiment:
1. Analysis > Stellar > Preferences
2. Dismiss the initial “Select
measurements” dialog.
3. Enter the desired minimum BPM
value into the top field.
4. Enter the desired maximum BPM
value into the bottom field.
5. Click OK to apply the settings.
The example below shows how mean heart rate and
standard deviation results can be enhanced by
lowering the maximum heart rate range from a
default value of 700 BPM (left) to 300 BPM (right).

For more information about the AcqKnowledge Find
Rate feature and windowing setup, see page 358.

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Chapter 31

Mobita

Mobita is a portable wireless system for acquiring ECG, EMG, EEG, EOG, EGG and accelerometer data via a
dedicated WiFi network. This hardware system is controlled by a specially-licensed version of
AcqKnowledge (versions 4.4 and greater only).
The Mobita package consists of:
· AcqKnowledge software
· Battery-powered data acquisition unit
· USB WiFi dongle
· Detachable docking station (for charging unit, and connecting to computer via USB interface to
download logged data and change the recording configuration)
· Detachable “confiCap” (for connecting various electrode leads, allowing wireless acquisition and
data logging of up to 32 analog data channels, and up to 64 calculation channels)
The Mobita unit also has a built-in tri-axial accelerometer function, with the “X,” “Y,” and “Z” accelerometer
channels appearing immediately below the available analog channels in the AcqKnowledge channel setup.
The purpose of this chapter is to provide an overview of the AcqKnowledge software interface as it relates to
connected Mobita hardware. For details on Mobita installation, network setup and hardware, see the Mobita
Installation and Mobita Hardware guides.
AcqKnowledge Interface in Mobita
AcqKnowledge with Mobita looks nearly identical to the user interface seen when using MP160/150 or other
supported data acquisition hardware types. Standard AcqKnowledge functionality is supported, with the
following limitations:
· Acquisition rate is limited to a maximum of 1000 samples per second. (Other available rates are
500, 200 s/s.)
· Recording length is dictated by the maximum amount of available card storage memory in the
Mobita unit. The default recording length is the standard 3600 seconds (60 minutes).
· Stimulator controls are not supported.
· One optional digital channel for use with a trigger signal is supported depending on the
connections available on the cable.
Upon launching AcqKnowledge with Mobita, the Set Up Data Acquisition window is presented with the
Analog Channels tab active. Set up the desired channels and acquisition parameters here before continuing.

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Selecting or Adding Mobita Hardware in AcqKnowledge
If additional hardware types were used prior to Mobita installation, the Mobita hardware can be enabled by
selecting it from the “Connect to” hardware list (below left), or be added as a recognized hardware type via
Hardware > “Manage Hardware Connections” and choosing “Connect New Hardware” (below right).

Mobita hardware can also be selected upon application launch in the Startup Wizard following Mobita
installation and network setup.

Mobita Menu
The Mobita hardware menu will look familiar to AcqKnowledge users. The “Set Up Data Acquisition”
window brings up standard AcqKnowledge options for channel and recording setup. (The “Set Up Data
Acquisition” window is presented by default upon application launch, with Analog Channels display
enabled.)

.

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Mobita Analog Channels Setup
Up to 32 analog channels are available, with the following available presets and default filtering:

In Mobita, (as in other AcqKnowledge hardware types) channel labels, sample rates and setups are
customizable, and user-defined channel presets can be created and saved.

Note

Mobita accelerometer channels are fixed at absolute levels and have no configurable preset options.

Analog Channel Digital Filters
The Analog tab’s “Setup” button displays options for setting IIR filters and modifying scaling parameters for
the selected channel. Up to four IIR filter types are supported per channel. The bundled presets shown above
have default filter settings, but these can be modified and saved as unique channel presets if desired. (See
following page.)
The below example shows default filters, scaling settings and units for the ECG (0.5 – 35 Hz) analog
channel preset:

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To set a filter manually, select a filter type from the pop-up menu (see below).

For details about AcqKnowledge IIR filters, see page 302. See also Appendix B – Filter Characteristics.
Mobita Calculation Channels

Mobita Calculation channels and associated presets operate in standard AcqKnowledge fashion. Choose the
Calculation tab, enable a channel and select the desired preset and analog source channel. The “Setup” button
opens a dialog for modifying default parameters of the selected online transformation.
Enable Common Average Value Removal
“Enable common average value removal” is a checkbox is found at the bottom of the acquisition setup
(Length/Rate) window. This option is helpful for removing common mode interference, noise, and motion
artifact.
If disabled, signal and noise artifact can be removed post-acquisition by using the “Remove Common
Reference Signal” Analysis menu option. BIOPAC recommends keeping this option enabled for optimal data
quality.

Remove Common Reference Signal
Mobita hardware uses a common reference amplifier
design with unipolar lead capture. With this type of
amplifier design, there are common signals
superimposed on all channels. When mixing unipolar
and differential signals, the average of all of the
unipolar signals must be subtracted from them in order
to extract the unipolar signals. As this is a common
operation for Mobita data processing a Specialized
Analysis option has been created to make this process
easier. (Note that this feature is only intended for use
with AcqKnowledge data acquired with Mobita
hardware.)
To remove the common reference signal following data acquisition, choose Analysis > Remove Common
Reference Signal. select the channels to be averaged and click OK. The signals with the subtracted averages
will be outputted to additional individual graph channels. (See Specialized Analysis chapter on page 365.)

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Mobita Acquisition (Length/Rate) Settings

The following acquisition modes are supported in Mobita hardware:
Append and Autosave
Append and Autosave modes are available for WiFi communication only, with no data stored to the Mobita
hardware. Memory or disk storage options are supported both acquisition modes.
Save once (WiFi + Logging)
“Save once”(memory or disk) mode supports both WiFi communication and data logging. During “Save
once” acquisition, data is logged on the Mobita hardware and streamed wirelessly into the AcqKnowledge
graph. When acquiring data in this mode, note the “Start/Stop” button status is replaced by “Log.”

Mobita will log data for the selected acquisition length, or until hardware memory is filled to capacity. When
the acquisition is complete, all logged data will be present in the AcqKnowledge graph. If the “Log” button is
clicked before the acquisition is complete, (or if the subject wanders out of wireless range), a logging status
dialog is presented:

During this state, data plotting in AcqKnowledge stops, but data continues to be logged into Mobita
hardware. The start/finish times are displayed, along with a countdown of remaining logging time.
“Abort” option: Data logging to Mobita is cancelled. The “Log” button in AcqKnowledge reverts to “Start.”
Before acquiring new data or changing the acquisition mode, the Mobita hardware must be reset via the USB
docking station. For information about resetting the hardware or changing acquisition modes, see page 571.
Note: All data logged prior to choosing “Abort” is retained in the graph.
“Download” option: User will be prompted to confirm the download and connect the Mobita hardware to a
USB port. (Download of logged data is not supported in WiFi mode.) Upon connection, the logged data is
downloaded and imported into the graph. During download, a screen similar to the one below will appear:

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After the download screen closes, the logged data is imported into the AcqKnowledge graph at an accelerated
rate. The import duration is dependent on the length of the logged acquisition.
Changing Acquisition Modes or Resetting Hardware
To change acquisition modes, or to reset the Mobita hardware after logging data, use the following steps.
1. Select the desired acquisition mode in Mobita > Set Up Data Acquisition.
2. Click “Start.”
3. Follow the onscreen communication prompts as they appear. (Shown below.)

Communication Prompt 1

Important: After connecting the docking station, wait for the blue light on the Mobita unit to
illuminate before clicking “Retry.”

Communication Prompt 2

4. After clicking “Retry” in the confiCap communication prompt, the following connection
dialog will appear.

5. When Mobita connection is established, this dialog will close automatically and the recording
will start in the selected acquisition mode.
Mobita Network Connection Utility
If it becomes necessary to restore the connection to
the Mobita hardware and/or ASUS USB network
adapter, this connection message may appear:
To re-establish the connection, use the Mobita Network Connection Utility as follows:
1. Mobita menu > Manage Network Configuration Utility.
2. Click “Validate and Adjust Network Configuration.”

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3. If the USB adapter connection needs to be re-established, the following
communication prompt may appear:

4. If this prompt appears, highlight the ASUS USB adapter in the “Adapters” list and click “Validate
and Adjust Network Configuration” again. (Make sure the adapter is connected or it will not
appear in the list.)
5. Click “Yes” and “Retry” to the following four prompts as presented.

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Important: After connecting the docking station, wait for the blue light on the Mobita unit to illuminate
before clicking “Retry.”

6. After connecting and clicking “Retry,” wait for the connection to be established (20-30 seconds).

7. After the connection dialog closes, the hardware connection is complete. Close the Mobita
Network Configuration Utility.

NOTES:
·
·
·

Mobita functionality is supported in Windows 10, 7 and 8.x only.
Mobita with AcqKnowledge requires an Administrator user account. It is not functional for
Limited accounts.
USB download of data from the Mobita unit may be less stable via USB 3.0 port or hub. If
download issues occur, try connecting to a USB 2.0 port of hub instead.
For a detailed look at Mobita configuration, watch the Tutorial video here.

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Chapter 32

FaceReader

FaceReaderTM with AcqKnowledge is available through optional licensing in AcqKnowledge 5.
FaceReader runs on Windows only and current release 7.1 is supported on Windows 7 64 bit (SP
1) or Windows 10 (64 bit). Contact BIOPAC for licensing details.
FaceReader™ is the premier professional software for automatic analysis of facial expressions. FaceReader
emotion reading software locks onto a subject’s face and analyzes facial movements to classify the subject’s
response. The software was “trained” with more than 10,000 manually annotated images. Easily integrate with
physiological parameters from an MP160 or MP150 Research System or eye tracking data. Start AcqKnowledge
to begin recording, and FaceReader data is automatically synchronized and recorded in the same graph file.
Monitor data in the FaceReader display for real-time feedback. Classifications include:
·

Happy

·

Sad

·

Scared

·

Disgusted

·

Surprised

·

Angry

·

Contempt

·

Neutral

Add Action Units to measure three common affective attitudes: boredom, interest, confusion. FaceReader also
provides gaze direction, head orientation, and person characteristics, such as gender and age.

Seamless Integration – easily integrate and synchronize physiological data or eye tracking through
AcqKnowledge.
Complete Facial Expression Analysis – accurate modeling of the face by describing over 500 key points
delivers objectivity in observations.
Useful for a Variety of Applications – psychology, educational research, consumer behavior research,
usability studies, and neuromarketing research.

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How Does FaceReader Work?
FaceReader software uses the computer’s (or external) camera, a still photo, or a video image to detect and
analyze a subject’s emotional state by utilizing the facial action coding system (FACS) first developed in the
1960s by Swedish anatomist Carl-Herman Hjortsjö and later expanded by Dr. Paul Ekman. The FACS
algorithm is capable of interpreting the tiniest of facial movements, rendering an accurate and nuanced
interpretation of a subject’s emotional responses. This automated state scoring has become popular in
advertising and neuromarketing for assessing subject feedback to videos and other stimuli, and is also often
used as another measure during self-assessment studies.
The FaceReader licensed feature allows response classifications to be selectively recorded as channels in an
AcqKnowledge graph, and includes the following functionalities:
· Receive emotional state data from FaceReader in real-time*
· Store emotional state data in AcqKnowledge graph files
· Incorporate emotional state data with other physiological signals and data analysis
*Due to initial latency, the first second of FaceReader classification data and video may not be fully
synchronized. To synchronize video recorded by FaceReader with data recorded in AcqKnowledge, an LED
connected to the MP should be used to visually mark the first video frame corresponding to the start of data
acquisition. For more information see the video synchronization section of the Media Chapter on page 478.

AcqKnowledge FaceReader options become visible when the optional FaceReader license has been activated.
Additionally, FaceReader software must be installed on the AcqKnowledge computer, or on a networked
computer or server. See the FaceReader Software Reference Manual for installation and configuration
instructions (i.e., FaceReader software and camera setup.)
Using FaceReader with AcqKnowledge
To configure FaceReader for use in AcqKnowledge:
1. Launch the FaceReader software and create a new project.
2. Choose “File >Settings.”
3. Select “Data Export” and check the “Enable External Control (API)” option.
4. Note the External Connection Port number. The default setting of 9090 shouldn't need to be
changed unless there is a conflict with another application:

Enabling data connection in the FaceReader software settings
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5. To record overall valence and activity signals, scroll to the bottom of the Application Settings
screen and check the “Valence and Arousal” option (see below figure). For more information
on valence and arousal signals, see page 578.

6. Click OK to exit the Application Settings screen.
Creating a FaceReader Project and Recording in AcqKnowledge
1. After performing the above configuration steps 1-5, launch the FaceReader software and
choose “Create New Project.”
2. Add a participant to the project.
3. Add a camera analysis (Camera toolbar icon in FaceReader
software UI) and note the camera preview for positioning
the subject.
4. Launch or return to AcqKnowledge. (If necessary, create a new graph.)
5. Choose MP160/150 > Set Up Data Acquisition > FaceReader. (This option is only visible if a
FaceReader license is present.)

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6. Check the “Enable FaceReader” checkbox.
NOTE: Appended acquisitions are not supported in FaceReader. If the “Length/Rate” record
mode is set to Append, the following prompt will appear:

·

If the FaceReader software is installed on the local AcqKnowledge computer, select
“Local Host” as the “IP” setting and use the default Port number of “9090.”

·

If the FaceReader software is installed on another networked computer, choose the
“Manual” option and enter the I.P. address of the FaceReader computer. (The I.P.
address can be found by choosing Start > Run “cmd” and using the “ipconfig”
command.)

7. Select the desired “Emotional States to Record” signals. NOTE: All emotional states can be
selected or deselected at once by pressing the Alt/Option key and clicking a selection.
8. Exit the Channels > FaceReader setup screen and click the AcqKnowledge “Start” button. (At
least one AcqKnowledge Analog channel must be enabled in order for the recording to start.)
9. The selected Emotional State data will be recorded into a new set of channels alongside other
AcqKnowledge data.
10. Click “Stop” to halt AcqKnowledge FaceReader recording.
TIP: In the AcqKnowledge FaceReader tab, click the “Save as Graph Template” button to permanently save
the Port setting and selected Emotional States for future sessions.
Creating AcqKnowledge Graphs from a Saved FaceReader Analysis
Existing saved FaceReader analyses can be extracted into an AcqKnowledge graph, even if the analysis was
not originally performed using AcqKnowledge. To do this:
1. In FaceReader, open an existing project.
2. Open the Analysis for the project (click the magnifying glass icon to display the saved
video.)

3. Launch AcqKnowledge and make sure FaceReader is enabled in the application (See Steps
5-6 above).
4. Click “Start” in AcqKnowledge. The recorded FaceReader analysis will be displayed in
AcqKnowledge graph channels.
FaceReader Signals
FaceReader records various emotional states and displays the analysis in real-time. As previously explained,
this analysis extracted as graph channels in AcqKnowledge software. FaceReader implements a neural
network trained on the following facial expressions:
· Neutral
· Sad
· Disgusted
· Angry
· Scared
· Happy
· Surprised
These recorded expressions are used to extract the subject’s dominant emotional state during the response
period, otherwise known as “valence.”
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Valence and Arousal
Valence and Arousal are two additional high level signals derived by FaceReader. Valence is used as an
indicator of a subject’s overall emotional state based on sum of positive emotions minus the sum of negative
emotions, and ranges in value from 1 to -1. (The most positive emotional state being 1, the most negative -1.)
Arousal is used as an indicator of whether a subject is active or inactive and is based on average activity of the
various facial action units within the last 60 seconds. A value of 0 corresponds with an inactive subject and a
value of 1 with an active subject.
The seven emotional states, plus the derived valence and arousal signals provide useful high-level information
about a subject. FaceReader also provides tools for extracting other lower level facial information, including
state of standard FACS action units, general gaze direction, head orientation, eyes open/closed indicators and
other parameters. These high-level signals are relevant for psychophysiology.
If “Valence” and “Arousal” Emotional States are selected in the AcqKnowledge FaceReader tab but have not
first been configured for output in the FaceReader software, the following dialog will appear.

If this occurs:
1. Return to the FaceReader software, choose “File >Settings.”
2. Scroll to the bottom of the Application Settings screen and check the “Valence and Arousal” box.
3. Click OK to exit the FaceReader Application Settings screen.
4. Return to AcqKnowledge and rerun the FaceReader recording to verify that valence and arousal data
are present.
Connection Issues
If, after clicking “Start” AcqKnowledge fails to establish a connection with FaceReader, the following dialog
will appear:

If FaceReader and AcqKnowledge are installed on the same computer:
Check the IP port setting for both applications as shown on pages 575 and 576. The port settings should
match. (The default is 9090.) This port number may need to be changed if there is a conflict with another
application.
If FaceReader is installed on a different computer on the network:
Make sure the I.P. address of the FaceReader computer is correctly entered in the AcqKnowledge FaceReader
tab’s Manual field. Auto-location of the I.P. address is not supported, so this value must be entered manually.
To determine the I.P. adress of the FaceReader computer:
1. On the FaceReader computer, choose Start > Run.
2. Type “cmd” to bring up a command window.
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3. Type “ipconfig” and press the Enter key.
4. Note the I.P. address.
5. Return to the AcqKnowledge computer.
6. Enter the I.P. address in the AcqKnowledge FaceReader tab’s Manual field and click OK.

Camera Connection Issues
For certain types of USB cameras, the camera connection may become lost following a FaceReader analysis
session. If this occurs, unplug and reconnect the camera before continuing with a subsequent analysis. It is
recommended that an integrated camera be used if possible and set as the default camera.
For further instruction and technical details about Noldus FaceReader software, see the FaceReader
Software Reference Manual.
For more information about the AcqKnowledge FaceReader Licensed Feature, visit www.biopac.com.

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Part E — Appendices
Appendix A - Frequently Asked Questions
Q: I have a large data file and it seems to take a long time to redraw the screen. Is there anything I can do to
speed it up?
A: Yes. There are several remedies for this.
(1) The simplest solution is to check the Draft mode for compressed waves and Use all available
memory boxes in the Preferences dialog (shown below). Checking these two boxes will cause
AcqKnowledge to plot data faster (at the expense of some precision) and use as much available
memory as possible.

(2) The time interval per division can be reduced, which causes less data to be displayed on the
screen at one time, and should reduce plot time.
(3) If a high-resolution video card is installed (one capable of displaying millions of colors), it may be
helpful to reduce the resolution to speed up plotting time.
(4) Load all data into memory; see page 473 for details.
Q: Can I use other software with the MP System (MP160, MP150 or MP36R)? Can I use AcqKnowledge to
control other data acquisition hardware?
A: No. The MP System was designed to work with the AcqKnowledge software. However, the software
can read in previously acquired text files generated by AcqKnowledge or any other software.
Q: I have a device that outputs an RS-232/RS-422 signal. Can I connect this to the digital I/O lines?
A: No. These types of digital output devices have their own communication protocols and are more
complex than the digital pulses that the MP System (MP160, MP150 or MP36R) can accept as inputs.
Q: I imported a text file and the time scale is wrong. What happened?
A: When a text file is imported, AcqKnowledge assumes (by default) that the data was sampled at 100
Hz or 100 samples per second. This is arbitrary, and there are two ways to adjust this. Both methods
involve Calculating the interval between sample points. To calculate the sampling interval, the rate at
which the data was originally sampled must be known. The sampling interval is calculated by
dividing one by the sampling rate. The sampling interval can be adjusted to the appropriate value via
the File > Open dialog before the data is read in, or if the data is already present, change the time
scale in the Display > Horizontal scale dialog.
For instance, if 20 minutes of data was originally collected at 2Hz and is read into AcqKnowledge as
a text file, the software will interpret this as data collected at 100 samples per second. To set the time
scale to accurately reflect the data, change the sampling interval from 0.01 to 0.5 seconds per sample.
X

X

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To change this setting before data is read in, click the Options button in the File > Open dialog and
change the value in the Sampling Interval dialog. To change the time scale after data has been read in,
adjust the units per division in the Display > Horizontal axis dialog. If the data are time-domain data,
the seconds/sample interval can be adjusted at the bottom of the dialog. This value defines the interval
between sample points, and can be changed to fit the rate at which the data was originally acquired.
Q: I just filtered a waveform and now my data file is huge. Why is that?
A: When AcqKnowledge performs any type of transformation on a waveform (e.g. digital filtering,
waveform math), it converts the entire waveform from integer format (two bytes per sample) to
floating-point format (eight bytes per sample). Since each sample point in the waveform now takes up
four times as much space, the file should be approximately four times as large. AcqKnowledge still
saves the file as compactly as possible, and since some of the information stored describes the time
base, the file size will not increase by exactly a factor of four.
Q: My MP data acquisition unit seems to be connected, but I can’t acquire data. What should I do?
A: This can be caused by one of several conditions:
(a) Check to make sure that the MP data acquisition unit is ON and, if so, that all the connections to
the MP data acquisition unit were made properly. When the MP data acquisition unit is powered
up, a light on the front panel of the MP data acquisition unit will illuminate. If the power light
will not illuminate, check to make sure the proper power supply is connected. The power supply
that comes with the MP data acquisition unit is rated at 12 VDC @ 1 Amp, and using other power
supplies may result in damage to the MP data acquisition unit.
(b) If the proper power supply is connected but the power light still does not illuminate, disconnect
the power supply and check the fuse in the back of the MP data acquisition unit. The fuse is a
standard 2.0 Amp fast blow fuse, and can be changed by unscrewing the fuse cap and replacing
the fuse.
(c) If the power light does illuminate, the next step is to see if the busy light (next to the power light
on the front panel of the MP data acquisition unit) illuminates when the MP data acquisition unit
is powered up. When the MP data acquisition unit is powered up, the busy light should illuminate
for three or four seconds and then extinguish.
NOTE: The busy light is normally off (except at startup), but it will remain on while
data is being acquired and will illuminate for the duration of each trial when data is
being acquired in averaging mode. If the busy light does not illuminate when the
system is powered up or does not turn off after a few seconds, contact BIOPAC at
one of the locations listed in Appendix A.
Q: I set up the channels but I only seem to be acquiring noise. What’s wrong?
A: A number of phenomena can cause this. Check to make sure that the settings in the Set Up Channels
dialog correspond to the channel switch settings on the amplifier modules and/or direct analog
connections to the HLT100C or UIM100C. When a direct analog input is set to the same channel as
an amplifier, the resulting data will appear quite noisy or erratic. Check to see that no two amplifiers
are set to the same channel.
Another possible cause is that the gain settings on the amplifiers are too low and should be increased.
It also may be helpful to select Autoscale waveforms from the Display menu. This will automatically
adjust the waveforms to provide the “best fit” in terms of scaling the data to fit in the available
window space.
It is also possible that the electrodes/transducers themselves are the source of the noise. Proper
electrode adhesion techniques involve abrading the skin and securing the electrode in place to reduce
movement artifact.

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Q: What is the storage and operation accuracy of AcqKnowledge?
AcqKnowledge performs all internal calculations to the accuracy defined by the IEEE format for
double precision floating point numbers and stores the results of those calculations in double
precision floating point format. This format assigns 8 bytes to all numbers involved in calculations or
resulting from calculations. The 8 bytes (64 bits) are assigned as 52 bits to mantissa, 1 bit to sign, and
11 bits to exponent. The effective decimal accuracy for calculation operation or storage will be
defined as [2 to the 52] power or approximately 4.5 E15. Accordingly, the effective decimal accuracy
will be between 15 and 16 digits.

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Appendix B - Filter characteristics
Filter types
AcqKnowledge employs two types of digital filters:
(a) Finite Impulse Response (FIR) perform filtering calculations online (during an acquisition) or postprocessing (after an acquisition).
(b) Infinite Impulse Response (IIR) perform filtering calculations online (during an acquisition) or postprocessing (after an acquisition).
Although the similarities between the two types of filters outweigh the differences, some important
distinctions remain.
1. IIR filters tend to be less accurate than FIR filters. Specifically, IIR filters tend to cause phase
distortion or “ringing.” When the phase of a waveform is distorted, some data points on a waveform
are shifted (either forward or backward in time) more than others. This can result in the intervals
between events (such as the Q-R interval or the inter-beat interval in an ECG waveform) being
slightly lengthened or shortened compared to the original signal. In practice, however, the effect of
this distortion is usually minimal since the frequencies which are most distorted are also attenuated
the most. By contrast, FIR filters are phase linear, which means that the interval between any two
sample points in the filtered waveform will be exactly equal to the distance between the
corresponding sample points in the original waveform.
2. IIR filters have a variable Q setting that defines the filter response pattern, but FIR filters do not have
a Q component. The optimal Q of an IIR filter is 0.707, with lower values resulting in a flatter
response and higher values resulting in a more peaked response. The default Q for all IIR filters is
0.707 (except for Band pass filters where Q defaults to 5), which is appropriate for nearly all filter
applications.
In the examples on the following page, the filter responses of several different types of filters are compared.
All of the filters are 50 HZ low pass filters operating on the same data.
The first graph shows how the number of filter coefficients in FIR filters (Q) affects the filter’s frequency
response. Note that as the number of coefficients (Q) increases, the filter becomes more accurate. A good rule
of thumb is to set Q ≥ 2(fs/ fc), where fs = sampling rate and fc = cutoff frequency.

FIR filter performance as a function of number of coefficients (Q)

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The next graph shows how the pole or zero locations of the filter, as related to filter “peaking” (specified by
Q), affect the frequency response of the filter. The “Q” in this case is not to be confused with the Q from the
FIR filter. Note how increasing “Q” in the IIR filter case affects filter “peaking.”

FIR filter performance as a function of changes in pole or zero locations
Coincidentally, the FIR (Q = 10) and IIR (Q = 0.707) filters have very similar responses in this case.
Technically, the coefficient setting for FIR filters determine the number of multiplies performed by the
filtering algorithm. In practical terms, it determines how “steep” the frequency response of the filter is. Filters
with a large number of coefficients have a steep roll-off, whereas the frequency response of filters with a
smaller number of coefficients is not as steep.
Window Functions
Window functions are used for two purposes in AcqKnowledge. Windows are applied to the impulse response
in the (FIR) digital filtering functions, and can optionally be applied as part of the FFT function. In either
case, a window refers to a computation that spans a fixed number of adjacent data points.
Typically, window functions are used to eliminate discontinuities that may result at the edges of the fixed
span of points of the digital filter function (FIR filters) or the data points of the FFT.
Digital filtering. When a window is used in digital filtering, the impulse response of the filter (rather than the
data itself) is modified. When the impulse response smoothly approaches zero at both the beginning and end
of the data, this works relatively well. When the impulse response is not so well behaved, edge effect occurs.
Edge effects can be minimized by windowing, or forcing the edges of the impulse response to smoothly
approach zero. The exact process depends on the window selected (see below).
Another way to minimize edge effect with an FIR filter is to increase the number of coefficients used to
transform the data.
FFT. The FFT function also windows data, although the nature of the windowing function is somewhat
different in the sense that the window operates on the data. One of the assumptions of the FFT is that the input
data is an infinitely repeating signal with the endpoint wrapping around. In practice, the endpoints are almost
never exactly equal. This can be checked by choosing the Delta measurement item from the measurement
popup menus, which returns the amplitude difference between the first selected point and the last. To the
extent that the endpoints differ, the FFT output will produce high frequency components as an artifact of the
transformation.
§ AcqKnowledge displays only the positive coefficients of an FFT. In this FFT presentation, there is an
implicit negative frequency component for each positive frequency component, so if looking at
amplitude levels in a linear FFT, it’s necessary to multiply by two (negative frequency can only be
created with positive frequencies in the real world).
By windowing the data, the effects of this phenomenon are greatly diminished. When data are windowed, a
window is moved across the data, much as the smoothing function moves across the data. Whereas the
smoothing function simply takes the average of a specified number of points, each type of window weights
the data somewhat differently.

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The Window pull down menu offers the following options:

Bartlett implements triangular windowing and Rectangle does not window the data. The “shape” of the other
N -1
windows is defined by the following formula, where n = n and A, B, C and D are constants:
0

2 pn
2p2n
2 p 3n
A - Bcos
+ Ccos
+ Dcos
N
N
N
The table below details the different parameter values for each type of window.
Parameter Values
Type of Window

A

B

C

D

n/a

n/a

n/a

n/a

Blackman

0.42000

0.50000

0.08000

0.00000

Blackman -61

0.44959

0.49364

0.05677

0.00000

Blackman -67

0.42323

0.49755

0.07922

0.00000

Blackman -74

0.40217

0.49703

0.09392

0.00183

Blackman -92

0.35875

0.48809

0.14128

0.01168

Hanning

0.50000

0.50000

0.00000

0.00000

Hamming

0.54000

0.46000

0.00000

0.00000

Kaiser-Bessel

0.40243

0.49804

0.09831

0.00183

n/a

n/a

n/a

n/a

Bartlett

Rectangle
Windows/PC only

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Appendix C - Hints for Working with Large Files
It is not uncommon for users to generate large data files (on the order of several gigabytes) through some
combination of (a) high-speed acquisitions, (b) long acquisitions, and (c) multi-channel acquisitions. Users
frequently encounter system limitations (such as storage space limitations) and find the files are difficult and
slow in loading to memory.
File size is limited by the restraints of the operating system and the available memory space on your hard
drive or disk (depending to which you save the file). Software for Windows and MacOS may have different
limitations due to system restrictions.
The software provided with the MP System (MP160, MP150 or MP36R) stores the data in as compact a
format as possible. Each sample takes up roughly two bytes of storage space. When a waveform (or a section
of a waveform) is transformed (i.e., filtered or integrated) each data point takes up roughly eight bytes of
storage space. As a result, file size can change drastically after transforming one or more waves.
WINDOWS OS
Current release: AcqKnowledge 5.0.3 – 64 bit - AcqKnowledge 5.0.2 and higher 64-bit offers major
improvements in terms of file size and memory limitation.
All released versions have the same single limit applied to channel(s) length in SAMPLES.
Channel length is limited by 2 GigaSamples = 2,147,483,648 samples
Any EDIT functions (copy/paste, resampling, merging, duplicate channel, remove waveform, cut selected
data area) cannot exceed this 2 GigaSamples limit
File functions
AcqKnowledge 5.0.2 and higher can read/save data files of virtually unlimited size in bytes. The only
limitation is free hard disk space.
AcqKnowledge 5.0.2 and higher cannot avoid 2 GigaSamples limit per channel, but can handle 100+
calculation/transformation channels (8 bytes per sample).
Example: AcqKnowledge 5.0.2 and higher was tested with data files as large as 45 Gbytes – 4 analog
channels + 4 calculation channels, length approximately 1.1 GigaSamples
Memory functions
AcqKnowledge 5.0.2 and higher utilizes two features – 64-bit addressing and Virtual memory supported by
Windows – and to allow handling of data files in instances when size is limited by Physical RAM and Virtual
Memory settings of Windows OS.
AcqKnowledge 5.0.2 and higher can allocate ALL physical RAM on the computer to load data into the
memory for transformations, and also can utilize virtual memory on the computer.
Use of virtual memory for transformations or “load all data into memory” is very helpful. However, the user
should expect transformation delays because using virtual memory means using the hard drive as a memory
substitute.
MS Windows settings that control the size of virtual memory are explained here:
https://www.geeksinphoenix.com/blog/post/2016/05/10/how-to-manage-windows-10-virtual-memory.aspx
Example: Computer has 16 GB of RAM and the virtual memory configuration for PAGE FILE is set to Initial
size:
= 24 GB and Max size = 48 GB. Under this setting, Acq 5.0.2 can load into the memory a data file of about
16 GB
+ 48 GB = 64 GB (minus memory allocated by OS Windows and other processes)
MAC OS
· AcqKnowledge 3.9.0 and above files (including merged files) are not limited
· AcqKnowledge 3.8.2 and below files (including merged files) cannot exceed 2 GB

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Use the following equation to calculate the memory required for your acquisition
Memory required (bytes) = [(8C + 2A) x S x T] + 1 MB*
C = Number of calculation channels
A = Number of analog channels
S = Sample rate (samples/second)
T = Recording time (acquisition length)
* 1 MB = memory required to store file information
Journals, events, and other information are variable and will also require more disk space. Once analog
channels are filtered or otherwise transformed, the required amount of storage will increase to 8 bytes per
sample, identical to calculation channels.
The following tips can be helpful in getting the most out of the MP System (MP160, MP150 or MP36R) when
working with large data files.
Ø
Remove waveforms
Since each waveform adds to the total size of the file, try removing (or copying to another file) some
of the waveforms from a multi-channel file. This is especially true when performing transformations.
Ø
Sample slowly
Theoretical and methodological concerns will, to a large extent, dictate sampling rate. However, if it’s
possible to reduce the sampling rate, choose to do so. Or, use Transform > Resample (page 322) to
resample data after collecting it.
Ø
Set preferences
Check the “Use all available memory” and the “Draft mode for compressed waves” options under the
Preferences menu item. This should decrease the time it takes to redraw waveforms and allow the
software to access all available memory for storage.
Ø
Store to disk
Although slightly slower than storing to memory, much larger data files can also be stored to disk.
Loss of power to either the computer or the MP unit can result in data loss. To avoid potential data
loss, connect both the computer and MP power supply to an uninterruptible power supply.
Ø
Use the Append mode
The Append mode allows the acquisition to be paused for arbitrary periods. This can be helpful when
recording only a few key events that will occur randomly over a long period of time, since it will
reduce unnecessary data.
Ø
Compress Files
Use the File > Save As > Compressed option to store or transfer data

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Appendix D - Customizing Menu Functionality
AcqKnowledge now includes a powerful customization feature that allows menu options to be displayed
selectively. For a specific procedure, it may be helpful to limit the menu options to list only the functions
necessary for the experiment, thereby reducing the chance for confusion or error. For example, it may be
helpful to remove the “Set Up Triggering” and “Set Up Stimulator” options from the MP160/150 menu, as
shown below:

Default MP menu
Customized MP menu
Follow the simple procedure below to customize the menu display.
1.
With the AcqKnowledge application closed, navigate to the menu.dsc file:
DRIVE:\ProgramData\BIOPAC Systems, Inc\AcqKnowledge 5\menu.dsc
2.
Open the menu.dsc file in Notepad.

3. Find the menu and item to be changed (scroll through list as necessary) and type “OFF” to disable the
menu display. In the example below, the IDM_STIMULATOR option has been changed to OFF.
Ø Note that ON/OFF is case-sensitive and must be typed in ALL CAPS.
Ø Deleting a file listing instead of typing OFF will not remove the feature; it will default to ON unless
OFF is entered.

4. Save the changes to the menu.dsc file and close it.
5. Restart AcqKnowledge.
6. Check the menu listing.
To reactivate a menu item set to OFF, just repeat the above procedure and type “ON” for
the desired menu item.
To revert a customized menu.dsc to the factory default, choose Display > Preferences >
Other and select “Create default menu configuration file.” After choosing “Yes’ in the
subsequent dialog, the application must be closed and relaunched in order for the change
to take effect.
Note:

Application menu customization has a corresponding effect on contextual menu display. If a
contextual menu item does not have a corresponding application menu item, the menu customization
file identifier will begin with “IDM_CM.”

Part E — Appendices

589

Appendix E—Locking/Unlocking the MP160/150
for Network Operations
The MP160/150 is primarily designed to work in Local Area Networks (LAN). In a LAN, each MP unit may
be accessed from any workstation (PC or Mac) running an Ethernet version of AcqKnowledge software.
Theoretically, two or more workstations (WS) could be connected to one MP160/150 at the same time, but
the MP160/150 cannot perform independent acquisitions simultaneously, so in such cases one or all
connected WS would receive corrupted/invalid data and/or crash.
To prevent this, AcqKnowledge uses new “lock/unlock” technology that establishes communication between
an MP160/150 and one —and only one— dedicated WS in the Network.
AcqKnowledge locks an MP160/150 as soon as it connects to it, which tells the MP160/150 to only respond
to commands from that particular computer and the communication method (serial or Ethernet). The lock has
a timeout which is reset every time the MP160/150 unit receives a command from the computer that locked it.
To locate MP160/150s in the local network, AcqKnowledge sends a broadcast packet to the local area
network that asks all the MP160/150s in the network to respond. All the MP160/150s—whether locked or
unlocked—will respond to this prompt. This means that the “Select MP160/150” menu may allow a user to
select an MP160/150 that is locked. In such cases, AcqKnowledge will fail to connect (to a locked
MP160/150 unit), as expected. To resolve this issue, unlock or power cycle the unit.
Locked

An MP160 or MP150 becomes “locked” in operation to a WS (and unusable to other users) if
a)An MP160/150 unit is selected from
“Choose MP160/150.” The dialog lists all
MP160/150 units that are powered ON
and sitting on the same local area
network. Unfortunately, this dialog cannot
provide the locked/unlocked status of
each MP160/150 in the LAN. Refer to the
BUSY and ACTIVITY lights on the
MP160/150 to determine the status—if
the MP160/150 shows no connection but
its lights indicate data traffic or
acquisition, the MP160/150 is probably
connected to another WS.
b) When AcqKnowledge is launched.
AcqKnowledge will “remember” and try to
connect the last MP160/150 used by a WS;
if the last used MP160/150 is not available,
the user must pick an available MP160/150
unit from the “Select MP160/150” dialog.
c) With the advent of any new
communications or the start of any type of
acquisition to the MP160/150 unit. When a
WS communicates with an “unlocked”
MP160/150 unit, AcqKnowledge sends a
“lock” command.
When an MP160 or MP150 is locked, its serial number is listed in the Select MP160/150 dialog but
any attempt to select a locked MP160150 will generate a Hardware Not Found prompt (shown
above).

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Unlocked

No
Hardware

An MP160/150 automatically “unlocks” and becomes available to other users
a) When the user exits AcqKnowledge.
b) The user selects another MP160/150 in the Select MP160/150 dialog.
c) The user selects the “No Hardware” option in the Select MP160/150 dialog.
Other, less common conditions that may unlock the MP160/150 include
d) The MP160/150 is powered OFF and then ON.
e) The MP160/150 does not receive commands/data from the WS or AcqKnowledge for about 5
minutes. This time-out can occur when
§ An AcqKnowledge dialog (About, Calculation setup, etc.) is open for a long time.
§ AcqKnowledge or the WS crashes for any reason.
§ The connected WS was turned off without exiting AcqKnowledge.
If the MP160/150 becomes unlocked due to a time-out, two scenarios are possible:
1) The MP160/150 is locked—If another user has locked the MP160/150, the No Hardware
Prompt will be displayed. Check the MP160/150 lights to determine its status.
2) The MP160/150 is unlocked—The WS will “lock” the MP160/150 as soon as communication
or acquisition is initiated. Until then, the MP160/150 remains unlocked and available to
others.
When a user selects the “No Hardware” option, the menu of available MP160/150 units is
grayed out and becomes unselectable. If a user attempts to connect to a locked MP160/150, an
error message will be generated to advise that the MP160/150 unit is locked to a different
computer.

Cannot
lock

If the “cannot lock” prompt appears, check that no other user on the network is using the
MP160/150, power-cycle the MP160/150, check the current firmware version (About
MP160/150), and, if necessary, update the firmware using MP160/150Tools (see next
Appendix).
MP160 or MP150 Firmware Upgrade
MP160/150 firmware is upgraded automatically. Unless a firmware warning is displayed at application
launch, the MP160/150 already has the latest firmware revision and no further action is necessary. If a
firmware warning is displayed, or if existing firmware needs to be rolled back to an earlier version, contact
BIOPAC technical support.
Check the firmware version via the MP160/150 > MP160/150 Info menu item in AcqKnowledge.

Visit the online support center at www.biopac.com

Part E — Appendices

591

INDEX
A
A/D boards (third party), 580
About
About AcqKnowledge, 474
About MP160/150 (menu option), 250
Absolute value, 153, 308
AcqKnowledge, 21, 27–52
Accuracy (storage and operation), 582
Acquire checkbox, 31, 114
Acquire, Setup Channels option, 174
Acquisition
Acquisition Length, 32, 168
High speed, 586
Long, 586
Overview, 109
Set Up, 32, 117
Start acquisition, 33
Troubleshooting, 581
Adaptive filtering
Calculation channel, 161
Transformation, 297, 303
Adaptive scaling, 78
Adjust grid spacing, 448
Alpha waves, 297, 337
Amplitude scale, 24, 76, 118
Analog channels, 31, 117–18
Gain setting, 119
Analog triggers, 181
Analysis functions, 73
Annotation, text, 60
Append mode, 165, 587
Application Notes, 25
Arbitrary curve fitting, 106, 329
Arbitrary sample rate, 322
Arbitrary scale (units), 450
Arbitrary stimuli, 191
Arc cosine, 153
Arc sine, 153
Arc tangent, 153, 308
Archive options, 51
Area (measurement), 98
Artifact rejection, 172
Atan. See arc tangent
Attenuation, Manual Control, 243
Auto threshold detect, 361
Autoplot, 256
Autoposition Hidden Annotations, 61
Autosave file, 165, 174
Autoscale after transformations, 467
Autoscale horizontal, 43
Autoscale Horizontal, 447
Autoscale waveform, 44
Autoscale Waveforms, 445
Averaging
Advanced Averaging setup, 172
Average (moving), 134

Average over samples, Integrate option, 137, 138
Averaging mode, 32
Averaging setup, 171
Off-line Cycle/Peak Detector (MAC), 347
Overview, 169
Axis adjustment. See horizontal scale, vertical scale

B
Band filter, 299
Base 10 logarithm, 154, 309
Blood pressure analysis. See rate calculations
BPM
BPM calculation, 363
BPM measurement, 99
BPM, Rate function, 141
BSL File Import, 265

C
Calculate (measurement), 99
Calculation channels, 31, 129–30
Calibration, 117–18
Capacity dimension measurement, 100
center horizontal, 36
center vertical, 36
CH# Output Control, 198
Channel
Channel boxes, 91, 452
Channel label, 91
channel sample rate, 116
Channel sample rate, 32
Channel setup, 117
Chaos Analysis
Detrended Fluctuation Analysis, 370
Optimal Embedding Dimension, 370
Optimal Time Delay, 370
Plot Attractor, 371
Chart mode, 452
chooser, 284
Clear, 288
Clear all, 288
Clip data, Calculation channel Function, 145
Clipboard, 98, 291–92
Close
File menu command, 274
Close prompts, 275
Coefficients (FIR filters), 300, 583
Color, 449
Comb Band Stop
Calculation channel, 147
Transformation, 303
Compare Waveforms, 447
Compression
down sampling, 322
Save As option, 281
Connect endpoints, 308
Constant (K), Calculate measurement option, 99
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Control channel
Calculation channel, 156
Integrate Calculation option, 135
Convolution, 312
Copy, 288
Acquisition Settings, 292
Graph, 292
Measurement, 291
Wave data, 292
Correlate (measurement), 100
Correlation, 310, 312
Correlation Coefficient
Specialized Analysis, 371
Correlation dimension measurement, 100
Cosine, 153
Count peaks, 363
Create Data Snapshot, 51
Cubic spline interpolation, 322
Customizing menu display, 470, 588
Cutoff frequency, 300
Cycles/Peaks detect, 3D Output, 348
Cycles/Peaks tab, Cycles/Peaks detect, 342

D
Data View, 41
Delay
Calculation channel option, 155
Trigger Set Up, 182
Delta measurements, 101
Derivative, 316
detrending, 332
Difference
online calculation, 140
transformation function, 321
Digital
Digital channels, 31, 118–29
Digital filters, 297–302, 584
Digital I/O channels, Manual Control, 242
Digital output, 156
Digital triggers, 180
Digital Outputs Control, 200
Disk
Space, sampling rate impact, 32
Space, storage mode impact, 262
Storage option, 167, 587
Display
Menu commands, 443
Preferences, 587
Draft mode, 466
Duplicate waveform, 289
dZ/dt Specialized Analysis
Classifier, 410
Derive from raw Z, 410
Remove motion artifacts, 417

E
ECG Analysis

Detect and Classify Heartbeats, 368
ECG Interval Extraction, 395
Heart Rate Variability, 405
Locate Animal ECG Complex Boundaries, 369
Locate Human ECG Complex Boundaries, 368
EDA analysis, 372
edge effects, 584
Editing
Cursor tool, 59
Edit menu, 286
Features, 73
EGrid cursor, 59
Eigenanalysis (PCA), 339
Electrode Checker, 179
Embedded archive, 51
Ensemble Average, 391
Epoch Analysis, 392
European Data Format (EDF)
Open, 270
Save, 280
Event (Marker)
Graph Selection, defining via, 240
Hotkey Setup, 227
Location, 230
Measurements, 236
Overview, 224
Palette, 229
Preferences, 225
Printing, 239
Toolbar, 225
Tooltips, 225
Variable Sampling Rate and, 240
Waveform editing, 239
Event amplitude measurement, 101
Event count measurement, 102
Event definition cursor, 59
Event location measurement, 102
Event marker, 25
Events, 48
Events, R wave location, 406
ex power of a data point, 153
Excel Spreadsheet Export, 281, 367
Exp Exponential, 308
Exporting data, 50, 266
Expression, 147–59, 323
Expression evaluator, 147–59
Expression measurement, 102

F
FAQ, 580
Fast Fourier transformations. See FFT
FFT, 333–37, 584
File Compatibility for Specialized Analysis, 366
File format prompts), 282
File menu commands, 262
File size, 581, 586
Filter
Calculation, 146

Visit the online support center at www.biopac.com

Index

593

characteristics, 583
response, 301
Find, 358
Find Cycle/Peak, Mac OS X, 341
Finite impulse response filters. See FIR filter
FIR filters, 297, 300, 583
Focus areas, 92
Font, journal, 468
Formula
Area, 98
BPM, 99
Correlation, 100
Delta, 101
Delta T/F/X, 101
Freq (Frequency), 102
Integral, 103
Lin_reg (Linear regression), 104
Mean, 105
Slope, 107
Stddev (Standard deviation), 107
Threshold, 145
Fourier
FFT Fast Fourier transformation, 333
Fourier Linear Combiners
Calculation Channels, 160
Transformations, 306
Frequency
frequency spectrum, 337
Horizontal scale, 450
measurement (Freq), 102
rate calculation (Hz), 363
Frequency Bands, HRV analysis, 407
Frequently asked questions, 580
Friendly Grid Scaling, 84
Function
Calculation, 148
Equation (Expression) commands, 153

G
Gain setting, 119
Gastric Wave Analysis, 369
Gastric Wave Coupling, 369
Gauge, 252
Getting Started, 21
GLP audit
include timestamp, 466, 467
mark selection with Events, 466, 467
GLP guidelines, customizing menus for, 24
Graph template files (gtl)
Open, 266
Quick Start Files, 132, 266
Save As, 276
Graph window, 30
Gray non-selected waves, 466
Grid
Adjust spacing, 448
GridReset, 448

H
Hardware. See note on page 10
Heart Rate Variability, 405
Help menu, 474
Hemodynamic Analysis, 393
ABP Classifier, 394
Arterial Blood Pressure, 394
ECG Interval Extraction, 395
LVP Classifier, 398
MAP Classifier, 400
Monophasic Action Potential, 399
High pass filter, 298
Histogram, 327
Hold button, SIV, 241
Hold relative position
Horizontal Scale, 74
Horizontal
Axis, 25
scale, 42
Scale, 42
Scroll bar, 74
Human Subjects, Safety, 222
Hyperbolic
Cosine, 153
Sine, 154
Tangent, 154

I
I/O channels, Manual Control, 242
I-beam tool
selection cursor, 59
IBI Inter-beat Interval, 141, 363
IFFT. See inverse FFT
Igor Pro Experiment
Open (import), 269
Save As (export), 279
IIR filters, 297, 302, 583
Impedance Cardiography Analysis, 410
Body Surface Area, 410
Derive dZ/dt from raw Z, 410
dZ/dt Classifier, 410
dZ/dt remove motion artifacts, 417
ICG Analysis, 413
Ideal Body Weight, 416
Pre-ejection Period, 416
Preferences, 418
VEPT, 417
Independent Component Analysis, 339
INF (measurement value), 94
Infinite impulse response filters. See IIR filters
Information Dimension measurement, 103
Initial offset, 74
Input Values Setup (SIV), 241
Insert
Events, 48
Waveform, 289
Installation. See note on page 10
Integral

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measurement, 103
Transformation function, 315
Integrate
formulas, 318
Integrate Calculation (online), 134
inter sample interval, 269, 278
Interpolate pastings, 467
Interpolation method, resampling, 322
Inverse mean square error, 312

J
Journal, 50
Copy Measurements, 98
Paste options, 293
Preferences, 468
Show Journal, Mac OS X, 295
Jump-to tool (correlates data views), 60

K
K (Constant), Calculate measurement option, 99
Kurtosis measurement, 104

L
Latency, 170
Left Ventricular Pressure
LVP Classifier, 398
Limit data, Calculation channel Function, 145
Limit math command, 309
Lin_reg (linear regression measurement), 104
line plot, 453
Linear (FFT option), 336
Linear interpolation, 322
Ln natural logarithm, 309
Locate SCRs, 378
Location Palette, 454
Locked MP160/150, 589
Log, 154, 309
Low pass filter, 298, 316
Lyapunov measurement, 105

M
Macintosh® system requirements, 22
Magnetic resonance imaging
Specialized Analysis, 419
Manual Control (digital I/O), 242
Manual stimulator controls, 186
Math
Calculation, 143–44
Functions (Transformation), 308
Waveform Math, 324
MATLAB
Open (import), 268
Save As (export), 278
Max measurements, 105
Max T measurement, 105

Mean
Mean square error, 312
Measurement, 105
Removal, 311, 335
Mean subtraction, Integrate option, 135
Measurement, 94
Cycles/Peaks Output, 346
Preferences, 466
Preferences for Journal, 468
Presets, 97
Table of Explanations, 98
Media menu (capture or playback), 476
Median measurements, 105
Median T measurement, 105
Memory
Load all data into, 473
Storage option, 167
Use all available memory, 469
Menu configuration file, 470
Menu display, customizing, 470, 588
Merge Graphs, 290
Min (minimum) measurement, 105
Min T measurement, 105
Modeling
Linear
Autoregressive transform, 328
Lin_reg measurement, 104

Nonlinear, 329
NLM measurement, 106

Modeling, Autoregressive, 328
Moment measurement, 106
Monophasic Action Potential, 399
MAP Classifier, 400
Moving average, 320
MP, data storage option, 167
MP160/150
Locked/Unlocked, 589
MP160/150 Serial Number, 249
MP160/150 Info (menu option), 250
MP160/150 System
Features, 24
MP160/150 System Requirements, 22
Mutual information measurement, 106

N
Natural logarithm, Ln, 309
Network Data Transfer (NDT), 486
Neurophysiology
Specialized Analysis, 423
New
Data View, 262
No hardware mode, 249
Noise, 581
Calculation channel Function, 145
Math command, 309
Rejection (auto threshold detect, 361
None (measurement option), 106
Nonlinear modeling, 329

Visit the online support center at www.biopac.com

Index

595

NLM measurement, 106
Normalized cross correlation, 313

O
Off-line Averaging, Cycle/Peak Detector (MAC),
347
Online filtering, 146
Open (file command), 265
Open for Playback, 271
Options button, Open Text file, 266
Options, Input Values, 241
Organize Channel Presets, 257
Organize List, Preferences, 214
Output continuously. Stim. Setup, 185, 210
Output Control, 196
CH# to Output, 198
Preferences, 197
Pulses, 201
Stimulator – OUT3 adapter, 201
Stimulator—BSLSTM, 201
Output tab, Cycles/Peaks detect, 346
Overlap
Overlap Waveforms, 446

P
P300 measurements, 172
Pad with…, 333
Padding (resampling interpolation), 322
Paste, 288
Acquisition settings, 294
Measurement, 293
Wave data, 294
Pause mode (Append to disk), 166
PC-compatible files, 276
Peak
Detect (Find Rate option), 361
Find Cycle (Peak Detector), Mac OS X, 341
Minimum, 363
Peak-to-Peak (P-P measurement), 106
PEP Pre-ejection Period, 416
Phase, 336
Distortion, 583
Phasic EDA options, 380
PhysioNet
Save As (export), 278
PICT files, 292
Playback mode, 39
Plot
Plot on Screen, Setup Channels option, 174
Plotting data, 31, 256
Poincare plots, 403
Power Spectral Density, 331
Power supply, 581
P-P (peak-to-peak measurement), 106
Preferences
Display Preferences, 462
Journal preferences, 468
Menu configuration file, 470

Output Control, 197
Undo max, 467
Presets, 115
Organize Channel Presets, 257
Pretrigger, 182
Principal Component Analysis, 339
Principal Component Denoising, 429
Print, 25, 52, 284–85
PSD Options, HRV analysis, 407
Pulse Sequence Output Control, 203
pulse stimuli, 189
Pulses Output Control, 201

Q
Q coefficient, filter setting, 146, 302, 583
QRS Detector, HRV analysis, 406
Questions, frequently asked, 580

R
Ramp waves, 190
Rate
calculation, 140–43, 325
Rate mean measurement, 106
Rate median measurement, 106
Rate standard deviation measurement, 106
Raw data
Open (import), 269
Save As (export), 278
Record
Start acquisition, 176
Record/Record last, 165
Recursive formulas, 150
Remove
last appended segment, 289
mean, 311, 335
trend, 335
waveform, 289, 587
Remove Projection, 312
Remove Projection Template, 312
Remove Trend, Specialized Analysis, 430
Repeat mode, 174, 257
Repositioning Events (Marker), 230
Resample, 322
Resampling Interpolation, 322
Reset
Append acquisition button, 166
reset chart boundaries, size window, 472
Reset Chart Display, 448
reset thresholds, Integrate setup, 135
reset trigger, Integrate setup, 135
Reset Grid, 448
Resource allocation, 469
Respiratory Sinus Arrhythmia, Specialized Analysis, 404
RS-232/RS-422 signal, 580

S
Safety Notice, 19

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Sample
measurement, 106
Rate, 167–68, 587
Rate, Acquisition rate, 32
Rate, Channel, 31, 32, 116
Rate, Stimulation signal output, 183
Save, 50
Save (File command), 275
Save as (File command), 275, 282
Save once (Acquisition setup), 165
Save Settings, Preferences, 202, 213
Scaling, 117–18
Scaling, Friendly Grid Scaling, 84
Scope mode, 34
Scroll, 42, 73
Menu option, 256
Segment Labels, 250
Select
All, 289
Area, 46, 286
Area for measurement, 95
Channel, 44, 91
Cursor tool, 59
Waveform, 44, 91
Selection Palette, 453
Selection tab, Cycles/Peaks detect, 345
Serial number,, 249
Set template, 310
Set Up
Acquisition, 32
Channels, 112, 117
Triggering, 180
Set wave positions, 448
Shortcuts
Keyboard, 65
Toolbars, 57
Show
All Data Snapshots, 51
Display menu options, 452
Input values, 115
Input Values, 241
Input Values Setup options, 241
Modified input, 334
Signal averaging. See Averaging mode
Sine, 154, 309
Size window, 472
Skew measurement, 106
Slope (measurement), 107
Smoothing
online calculation, 139
transformation function, 320
Smoothing Baseline Removal, 380
Snapshot data after acquisition, Preference, 51
Sound Sequence Output Control, 210
Specialized Analysis Package, 364, 365
File Compatibility, 366
Specifications. See MP Hardware Guide
Spectral analysis. See FFT
Spectral subtraction, 436

Spectrum Analyzer Palette, 458
Square
Square, 154
Square Root, 154, 309
Waves, 189
Standard deviation measurement, 107
Start acquisition, 33
Starting an acquisition, 176
Statistics (Waveform Statistics dialog), 461
Status indicator, 33
Stddev (standard deviation) measurement, 107
Step plot, 456
Stimulation. Dual, 188
Stimulator
Stimulator Reference Channel, 222
Stimulator - BSLSTM, 201
Stimulator Manual Control, 243
Stimulator setup, 183
Stimulator, manual controls, 186
Stimulus signal, 170, 172, 183, 208
STM100C Manual Control, 243
Stopping an acquisition, 176
Sum measurement, 107

T
Tab interval, Journal, 468
Tangent, 154
Tau (time constant), 329
Template functions, 310
Text Annotation, 60
Text files, 50, 268
Textual value display, 78
Threshold
Math command, 309
Tile waveforms
Tile after transformations, 467
Tile Waveforms, 444
Time
Expression source, 149
measurement, 108
Set Horizontal Time scale, 450
Time scale after importing, 580
Timestamp, journal preference, 466, 467
Tone stimuli, 189–90
Toolbars, 57
Transform, 47
Math commands, 308
Menu commands, 296
Remove Projection, 312
Specialized Analysis Package, 364, 365
transition latency, 438
Triggering, 180
Troubleshooting, 580

U
Undo, 287
User Support System, 17

Visit the online support center at www.biopac.com

Index

597

V
Value (measurement), 108
Values checkbox, 31, 115
Show input values, 241
Variable Sampling Rate, 32, 116, 183
data processing notes, 151
Event plotting and, 240
VEPT, 417
Vertical axis, 25, 118
Vertical scale, 44, 76
Viewing data, 42

W
Warning
Before overwrite data, 257
Hardware not found, 29
Waterfall Plot, 439
WAV files, 270
Waveform
Arithmetic dialog, 99
Color, 449
Math transformation, 324–25

Selection, 44, 91
Statistics dialog, 461
Wavelet Denoising, 440
Window
Find Rate option, 361
Functions (filter, FFT), 584
Menu, 474
Windows® system requirements, 22
Working in AcqKnowledge, 27

X
X/Y mode, 34, 35
X-axis T/F/X (measurement), 108

Z
Zap, event cursor, 60
Zoom
Cursor tool, 46, 59
Zoom previous, 447

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COPYRIGHT
Information in this document is subject to change without notice and does not represent a commitment on the part of
BIOPAC Systems, Inc. This manual and the software described in it are copyrighted with all rights reserved. Under
the copyright laws, this manual or the software may not be copied, in whole or part, without written consent of
BIOPAC Systems, Inc., except in the normal use of the software or to make a backup copy.
The same proprietary and copyright notices must be affixed to any permitted copies as were affixed to the original.
This exception does not allow copies to be made for others, whether or not sold, but all of the material purchased
(with all backup copies) may be sold, given, or loaned to another person. Under the law, copying includes translating
into another language or format. This software is intended for use on only one machine at a time.

Open source software for Specialized Analysis:
§ PCRE
Regular expression support is provided by the PCRE library package, which is open source software, written by
Philip Hazel, and copyright by the University of Cambridge, England.
ftp://ftp.csx.cam.ac.uk/pub/software/programming/pcre/
§ The Apache Software License, Version 1.1
Copyright (c) 1999-2001 The Apache Software Foundation. All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the
following conditions are met:
1.

Redistributions of source code must retain the above copyright notice, this list of conditions and the
following disclaimer.

2.

Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the
following disclaimer in the documentation and/or other materials provided with the distribution.

3.

The end-user documentation included with the redistribution, if any, must include the following
acknowledgment: "This product includes software developed by the Apache Software Foundation
(http://www.apache.org/)." Alternately, this acknowledgment may appear in the software itself, if and
wherever such third-party acknowledgments normally appear.

4.

The names "Xerces" and "Apache Software Foundation" must not be used to endorse or promote
products derived from this software without prior written permission. For written permission, please
contact apache@apache.org.

5.

Products derived from this software may not be called "Apache", nor may "Apache" appear in their
name, without prior written permission of the Apache Software Foundation.

THIS SOFTWARE IS PROVIDED ''AS IS'' AND ANY EXPRESSED OR IMPLIED WARRANTIES, INCLUDING,
BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE
FOUNDATION OR ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
===================================================
This software consists of voluntary contributions made by many individuals on behalf of the Apache Software
Foundation and was originally based on software copyright (c) 1999, International Business Machines, Inc.,
http://www.ibm.com. For more information on the Apache Software Foundation, please see
.

Visit the online support center at www.biopac.com

599

LIMITED WARRANTY
BIOPAC Systems, Inc. guarantees its equipment against all defects in materials and workmanship to the original
purchaser for a period of 12 months from the date of shipment unless otherwise stated below; effective 1-1-2015,
BIOPAC MP36 units are guaranteed against defects in materials and workmanship to the original purchaser for a
period of 60 months (5 years) from the date of shipment.
If BIOPAC Systems, Inc. receives notice of such defects during the warranty period, BIOPAC Systems, Inc. will at its
option, either repair or replace the hardware products that prove to be defective in materials or workmanship. This
warranty applies only if your BIOPAC Systems, Inc. product fails to function properly under normal use and within the
manufacturer’s specifications. This warranty does not apply if, in the sole opinion of BIOPAC Systems, Inc., your
BIOPAC Systems, Inc. product has been damaged by alteration, accident, abuse, misuse, neglect, improper packing,
shipping, modification or servicing, by any party other than BIOPAC Systems, Inc. If a problem arises, please contact
us for authorization before returning an item.
Any returns should be supported by a Return Mail Authorization (RMA) number issued by BIOPAC Systems, Inc.
BIOPAC Systems, Inc. reserves the right to refuse to accept delivery of any shipment containing any shipping carton
which does not have the RMA number(s) displayed on the outside. The Buyer will prepay transportation charges to
the BIOPAC Systems, Inc. designated site. The warranty period for repairs and for used equipment purchased from
BIOPAC is 90 days.
BIOPAC Systems, Inc. makes no other warranty or representation, either expressed or implied, with respect to any
hardware or software product, its quality, performance, merchantability, or fitness for a particular purpose.
BIOPAC Systems, Inc. will not be liable for direct, indirect, special, incidental, or consequential damages resulting
from any defect in a hardware or software product or its documentation, even if advised of the possibility of such
damages, or for damage of any equipment connected to a BIOPAC Systems, Inc. product.

TRADEMARKS
AcqKnowledge is a registered trademark of BIOPAC Systems, Inc.
Windows is a registered trademark of Microsoft Corporation in the United States and other countries.
Mac and MacBook are trademarks of Apple Computer, Inc., registered in the U.S. and other countries.

AC NOWLEDGEMNTS
K

E

Technical Writer: Jocelyn Mariah Kremer, Mike Mullins, with input from Alan Macy, Frazer Findlay, Edward Peterlin.
Created with Microsoft Word for Windows, JASC, Inc. JasCapture, FastStone Capture, Adobe Photoshop.
Manual Revision: AcqKnowledge 5.0.3 and licenses
PDF 8.14.2018

AcqKnowledge 5 Software Guide
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