ThinkGear Development Guide For Android Think Gear

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ThinkGear Development Guide for Android

December 14, 2012

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Contents

Introduction 4

inkGear SDK for Android Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Supported inkGear Hardware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Your First Project: HelloEEG 6

Developing Your Own inkGear-enabled Apps for Android 7

Preparing Your Android Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Creating the TGDevice Object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Receiving and Handling Data Messages . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

TGDevice Message Types (msg.what) . . . . . . . . . . . . . . . . . . . . . . . . . . 9

TGDevice States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Using the TGDevice Object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

inkGear Data Types 14

General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

POOR_SIGNAL/SENSOR_STATUS . . . . . . . . . . . . . . . . . . . . . . . . . 14

RAW_DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

RAW_MULTI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

EEG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

ATTENTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

MEDITATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

BLINK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

EEG_POWER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

THINKCAP_RAW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

POSITIVITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

FAMILIARITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

DIFFICULTY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

ECG/EKG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

HEART_RATE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Smoothed Heart Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Heart Rate Acceleration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Target Heart Rate for Physical Training . . . . . . . . . . . . . . . . . . . . . . . . . 18

Heart Fitness Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

RELAXATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

RESPIRATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Heart Risk Awareness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

HEART_AGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Personalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

EKG_RRINT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Proper App Design 26

Troubleshooting 27

Important Notices 28

Chapter 0 –

APPENDIX A: Additional References 29

APPENDIX B: UART (Non-Bluetooth) Connections 30

Chapter 1

Introduction

is guide will teach you how to use NeuroSky's inkGear SDK for Android to write Android apps

that can utilize bio-signal data from NeuroSky's inkGear family of bio-sensors (which includes the

CardioChip family of products). is will enable your Android apps to receive and use bio-signal data

such as EEG and ECG/EKG acquired from NeuroSky's sensor hardware.

is guide (and the entire inkGear SDK for Android for that matter) is intended for programmers

who are already familiar with standard Android development using Eclipse and Google's AndroidSDK.

If you are not already familiar with developing for Android, please rst visit http://developer.android.com

to learn how to set up your Eclipse+AndroidSDK development environment and create typical An-

droid apps.

If you are already familiar with creating typical Android apps, then the next step is to make sure

you have downloaded NeuroSky's inkGear SDK for Android. Chances are, if you're reading this

document, then you already have it. If not, the SDK can be downloaded from

http://store.neurosky.com/products/developer-tools-3-android.

ThinkGear SDK for Android Contents

• inkGear SDK for Android: Development Guide (this document)

• inkGear SDK for Android: API Reference

• inkGearBase.jar library

• inkGearPackX.jar library

• HelloEEG example inkGear project for Android

• HelloEKG example inkGear project for Android

You'll nd the "API Reference" in the reference/ folder of the TG-SDK, the "inkGearBase.jar"

and "inkGearPackX.jar" in the lib/ folder, and the "HelloEEG and HelloEKG example projects"

in the Sample Projects/ folder.

Supported ThinkGear Hardware

e inkGear SDK for Android must be used with a inkGear-compatible hardware sensor device.

e following inkGear-compatible hardware devices are currently supported:

• MindWave Mobile

• MindBand

• MindTune

Chapter 1 – Introduction

• MindSet

• inkCap 1.0

• BrainAthlete

• CardioChip Starter Kit Unit

Important: Before using any Android app that uses the TG-SDK for Android, make sure you have

paired the inkGear sensor hardware to your Android device by carefully following the instructions

in the User Manual that came with each inkGear hardware device!

Supported ThinkGear Hardware

Chapter 2

Your First Project: HelloEEG

HelloEEG is a sample project we've included in the inkGear SDK for Android that demonstrates

how to setup, connect, and handle data to a inkGear device. Add the project to your Eclipse IDE

by following these steps. (Tested with Eclipse IDE for Java Developers Version: Juno Service Release

1 on Mac OS 10.8.2)

1. In Eclipse, select File >New >Project…

2. In the New Project wizard, expand the Android section and select Android Project from Ex-

isting Code and click Next

3. Click on Browse… and locate the HelloEEG project folder in the Sample Projects folder and

click Open

4. Click the checkbox for Copy projects to workspace and click Finish

5. Click Finish to exit the wizard.

6. Have your Android device connected to your computer.

7. At this point, you should be able to browse the code, make modications, compile, and deploy

the app to your device or emulator just like any typical Android app.

Note: If there are problems, try the following:

• Right-click on the project and select Properties. Click on the Android section and make sure

a build target of at least Android 2.3.3 is selected.

• Before trying to connect, make sure you have paired your inkGear hardware device to your

Android device via your Android device's Bluetooth settings!

• In Eclipse's Package Explorer, expand the libs/ folder of your project, right-click (or Ctrl-click

for Mac users) on inkGearBase.jar, and select Build Path >Add to Build Path ALSO add

the inkGearPackX.jar that is in the folder.

• Check the Eclipse!Run!Run Congurations.. to make sure the application is running on the

correct device. On the Target tab you can pick "Always prompt to pick device".

• Take a look in the Eclipse Console, sometimes it indicates that it needs to be restarted, so exit

Eclipse and restart it.

• If you see the message e selection cannot be launched, and there are no recent launches." en

right click on the project in the Package or Project Explorer, choose "Run As"and pick "Android

Application". en try to Run again.

You may use this same process to build the HelloEKG sample project.

Chapter 3

Developing Your Own

ThinkGear-enabled Apps for

Android

Preparing Your Android Project

• First, make sure the "Android build target" for your project is at least Android 2.3.3.

1. Right-click on your project and select Properties.

2. Click on the Android section and make sure a build target of at least Android 2.3.3 is

selected.

• en, you must add the ThinkGearBase.jar and ThinkGearPackX.jarlibrary les to your

project:

1. With your Android project open in Eclipse, use the Package Explorer in Eclipse to create

alib folder at the root folder of your project

2. Use Windows Explorer (or Finder on Mac) to copy the ThinkGear jar les from the lib

folder of your TG-SDK for Android to your Eclipse project's lib folder.

3. In the Eclipse Package Explorer, right-click (Ctrl-click for Mac users) on ThinkGear-

Base.jar select Build Path »Add to build path. ALSO add the ThinkGearPackX.jar

• Assuming your app will be connecting to the inkGear hardware device via bluetooth, you will

need to enable the BLUETOOTH permission in your app's manifest le:

<uses-permission android:name="android.permission.BLUETOOTH" />

...

</manifest>

Creating the TGDevice Object

ATGDevice object is used to manage a single connection to a single inkGear hardware device.

is guide will only cover the most common connecting case, which is where your Android app

will be connecting to the inkGear hardware device via standard Android Bluetooth using the

TGDevice(BluetoothAdapter, Handler) constructor. (e alternate TGDevice(InputStream,

OutputStream, Handler) constructor should only be used for special, uncommon use cases).

• Import the following packages into your Activity:

import com.neurosky.thinkgear.*;

import com.android.bluetooth.*;

import com.android.util.Log;

Chapter 3 – Developing Your Own ThinkGear-enabled Apps for Android

• Declare a TGDevice object and a BluetoothAdapter object in your Activity:

public class HelloEEGActivity extends Activity {

//...

TGDevice tgDevice = null;

BluetoothAdapter btAdapter = null;

//...

• Initialize the btAdapter and tgDevice in the onCreate() method:

public void onCreate(Bundle savedInstanceState) {

//...

btAdapter = BluetoothAdapter.getDefaultAdapter();

if( btAdapter != null ) {

tgDevice = new TGDevice( btAdapter, handler );

}

//...

}

Note: We'll discuss the handler object in the next section.

Receiving and Handling Data Messages

e TGDevice will communicate to your app via messages sent to a Handler object. To create a

Handler object in your app to process incoming data:

private final Handler handler = new Handler() {

@Override

public void handleMessage( Message msg ) {

switch( msg.what ) {

case TGDevice.MSG_STATE_CHANGE:

switch( msg.arg1 ) {

case TGDevice.STATE_IDLE:

break;

case TGDevice.STATE_ERR_BT_OFF:

break;

case TGDevice.STATE_CONNECTING:

break;

case TGDevice.STATE_ERR_NO_DEVICE:

break;

case TGDevice.STATE_NOT_FOUND:

break;

case TGDevice.STATE_CONNECTED:

device.start();

break;

case TGDevice.STATE_DISCONNECTED:

break;

default:

break;

} /* end switch on state change type */

break;

Receiving and Handling Data Messages

Chapter 3 – Developing Your Own ThinkGear-enabled Apps for Android

case TGDevice.POOR_SIGNAL:

Log.v( "HelloEEG", "PoorSignal: " + msg.arg1 );

break;

case TGDevice.MSG_ATTENTION:

Log.v( "HelloEEG", "Attention: " + msg.arg1 );

break;

case TGDevice.MSG_RAW_DATA:

int rawValue = msg.arg1;

break;

case TGDevice.MSG_EEG_POWER:

TGEegPower ep = (TGEegPower)msg.obj;

Log.v( "HelloEEG", "Delta: " + ep.delta );

break;

default:

break;

} /* end switch on message type */

} /* end handleMessage() */

}; /* end Handler */

e type of each Message is determined by examining the value of msg.what, while the actual data

value for the Message is available from either msg.arg1 (for simple values) or msg.obj (for more

complex values).

TGDevice Message Types (msg.what)

msg.what Description Data

MSG_STATE_CHANGE e TGDevice has

changed state

e state change info is stored in

the arg1 eld of the Message (see

TGDevice States table below)

MSG_POOR_SIGNAL Bio-signal quality/status e status or quality of the bio-

signal is stored in the arg1 eld

of the Message

MSG_RAW_DATA Raw sample value e single-channel raw sample

value (most inkGear devices) is

stored as an int in the arg1 eld

of the Message

MSG_RAW_MULTI Multi-channel raw values e multi-channel raw sample

data (only available from certain

inkGear devices) are stored as

aTGRawMulti object in the obj

eld of the Message

Receiving and Handling Data Messages

Chapter 3 – Developing Your Own ThinkGear-enabled Apps for Android

msg.what Description Data

MSG_ATTENTION Attention level e attention level of the user is

stored in the arg1 eld of the

Message

MSG_MEDITATION Meditation level e meditation level of the user

is stored in the arg1 eld of the

Message

MSG_BLINK Strength of detected

blink

e blink strength of the user's

blink is stored in the arg1 eld of

the Message

MSG_EEG_POWER EEG powers e EEG powers of the user are

stored as a TGEegPower object in

the obj eld of the Message

MSG_THINKCAP_RAW Multi-channel raw values e multi-channel raw sam-

ple data (only available from

inkCap devices) are stored as a

TGRawMulti object in the obj

eld of the Message

MSG_POSITIVITY -100.0 to 100.0 Values indicate the subject's emo-

tion or mood. e more posi-

tive values mean the subject is in a

positive emotion or approach mo-

tivation, and the more negative

values mean more negative emo-

tion or withdrawal motivation.

MSG_FAMILIARITY Can be used to compare a test

subjects familiarity with a newly

learned motor skill. One minute

of collected data could constitute

a trial, and will produce a famil-

iarity index value. e familiarity

index of separate trials of the mo-

tor skill can be compared.

MSG_DIFFICULTY Can be used to compare the dif-

cult a test subjects nds a newly

learned motor skill. One minute

of collected data could constitute

a trial, and will produce a diﬃ-

culty index value. e diﬃculty

index of separate trials of the mo-

tor skill can be compared.

Receiving and Handling Data Messages

Chapter 3 – Developing Your Own ThinkGear-enabled Apps for Android

msg.what Description Data

MSG_HEART_RATE Heart rate e heart rate data is stored as

an int in the arg1 eld of the

Message

MSG_EKG_RRINT R-to-R interval e R-to-R interval in mil-

liseconds is stored as an int in

the arg1 eld of the Message

MSG_RELAXATION Relaxation level e relaxation level of the user

is stored as an int in the arg1

eld of the Message

MSG_RESPIRATION Respiration Rate e respiration rate of the user

is stored as a Float object in

the obj eld of the Message

MSG_HEART_AGE Heart Age e heart age of the user is

stored as an int in the arg1

eld of the Message

MSG_HEART_AGE_5MIN Heart Age e heart age of the user is

stored as an int in the arg1

eld of the Message

MSG_EKG_TRAIN_STEP Train Step e train step value is stored as

an int in the arg1 eld of the

Message

MSG_EKG_TRAINED Trained Does not return anything

MSG_EKG_IDENTIFIED Identied e identied result is stored

as a string in the arg1 eld of

the Message

Note: Depending on the type of inkGear hardware device that your TGDevice is connected to,

some of the data types listed above will never be sent to your app's Handler, since those data types

may not be applicable for that inkGear hardware device. See the developer specs for each inkGear

hardware device that your app may support for details.

Important: Pay particular attention to MSG_STATE_CHANGE messages (which indicate what the TGDe-

vice object is currently doing), and to MSG_POOR_SIGNAL messages (which indicates the current state

of the physical inkGear hardware device). For example, if the MSG_POOR_SIGNAL is indicating that

the physical inkGear hardware device isn't even being worn by a user at the moment (a value of

200 on inkGear EEG devices, or a value of 0 on ECG devices), then the app needs to treat any

incoming raw data values or EEG power values accordingly, possibly by ignoring them as appropriate

for the app.

For more detailed information about each data type such as Attention, Meditation, or Relaxation,

please use the inkGear Data Types section below as a reference guide.

For information that may be device-specic, additionally refer to the specs and development notes

that are available for each specic inkGear hardware device.

Receiving and Handling Data Messages

Chapter 3 – Developing Your Own ThinkGear-enabled Apps for Android

TGDevice States

State Description

STATE_IDLE Initial state of the TGDevice. Not connected to

any inkGear hardware device after stop()

STATE_ERR_BT_OFF e Android device's Bluetooth adapter is not

turned on or enabled during TGDevice() con-

structor or connect()

STATE_CONNECTING Attempting to connect to a inkGear hardware

device during connect()

STATE_ERR_NO_DEVICE ere are no Bluetooth devices paired to this

Android device

STATE_NOT_FOUND Could not nd any of the inkGear hardware

devices that are paired to this Android device

STATE_CONNECTED e data stream has been opened

STATE_DISCONNECTED e connection to the module is lost after close()

Using the TGDevice Object

With the Handler object ready to receive data and the TGDevice object created, your app can now

instruct the TGDevice object to try to connect to your physical inkGear hardware device and start

processing the incoming data.

• Call the connect() method of your tgDevice to start the connection process. e tgDevice

will search through your Android device's list of all paired Bluetooth devices, and try to connect

to the rst one that it recognizes as a inkGear-compatible device (see Supported Devices):

tgDevice.connect( true );

Note: Setting the connect() method's rawEnabled parameter to true allows raw sample data to

be sent to your app. Setting to false will prevent raw data from being parsed and sent to your app,

possibly saving some CPU from parsing and saving your app's Handler from having to receive many

raw sample messages that your app may not need to use.

• After successfully nding and connecting to a inkGear hardware device through Bluetooth,

the tgDevice will send a STATE_CONNECTED Message to your app's Handler. To start receiving

data upon receiving this message, call the tgDevice's start() method:

tgDevice.start();

• When your app no longer needs data from the TGDevice, close the connection by calling the

close() method:

tgDevice.close();

At this point, your app should now be able to connect to a inkGear hardware device and receive

values! To learn more details about the TGDevice class, you may refer to the inkGear SDK for

Using the TGDevice Object

Chapter 3 – Developing Your Own ThinkGear-enabled Apps for Android

Android: API docs at any time, found in the reference/ folder of your inkGear SDK for An-

droid.

Or, read on to the next section below to nd out what your app can (or should) do with some of those

inkGear values it's now receiving.

Using the TGDevice Object

Chapter 4

ThinkGear Data Types

e inkGear data types are generally divided into three groups: data types that are only applicable

for EEG sensor devices, types that are only applicable for ECG/EKG (CardioChip) sensor devices, and

data types that are typically applicable to all inkGear-based devices, including EEG and ECG/EKG.

General

ese data types are generally available from most or all types of inkGear hardware devices.

POOR_SIGNAL/SENSOR_STATUS

is integer value provides an indication of how good or how poor the bio-signal is at the sensor. is

value is typically output by all inkGear hardware devices once per second.

is is an extremely important value for any app using inkGear sensor hardware to always read,

understand, and handle. Depending on the use cases for your app and users, your app may need to alter

the way it uses other data values depending on the current value of POOR_SIGNAL/SIGNAL_STATUS.

For example, if this value is indicating that the bio-sensor is not currently contacting the subject, then

any received RAW_DATA or EEG_POWER values during that time should be treated as oating

noise not from a human subject, and possibly discarded based on the needs of the app. e value

should also be used as a basis to prompt the user to possibly adjust their sensors, or to put them on in

the rst place.

In order to interpret this value you must rst decide which type of NeuroSky sensor you are using.

As the interpretation is diﬀerent for the diﬀerent types of sensors.

For EEG sensor hardware: A value of 0 indicates that the bio-sensor is not able to detect any obvious

problems with the signal at the sensor. Higher values from 1 to 199 indicate increasingly more detected

problems with the signal. A value of 200 means the sensor contacts detect that they are not even all

properly in contact with a conductive subject (for example, the EEG headset may currently not even

be worn on any person's head).

For ECG/EKG (CardioChip) sensor hardware: A value of 200 indicates the bio-sensor contacts are

all currently in contact with a conductive subject (such as a user's skin), while a value of 0 indicates

the opposite: that not all the contacts are in proper contact with a conductive subject.

Poor signal may be caused by a number of diﬀerent things. In order of severity, they are:

• Sensor, ground, or reference electrodes not being on a person's head/body (i.e. when nobody is

wearing the inkGear equipment).

• Poor contact of the sensor, ground, or reference electrodes to a person's skin (i.e. hair in the

way, or headset which does not properly t a person's head, or headset not properly placed on

the head).

Chapter 4 – ThinkGear Data Types

• Excessive motion of the wearer (i.e. moving head or body excessively, jostling the headset/sen-

sor).

• Excessive environmental electrostatic noise (some environments have strong electric signals or

static electricity buildup in the person wearing the sensor).

• Excessive biometric noise (i.e. unwanted EMG, EKG/ECG, EOG, EEG, etc. signals)

For EEG modules, a certain amount of noise is unavoidable in normal usage of inkGear sensor

hardware, and both NeuroSky's ltering technology and algorithms have been designed to detect,

correct, compensate for, account for, and tolerate many types of signal noise. Most typical users who

are only interested in using the eSense values, such as Attention and Meditation, do not need to worry

as much about the POOR_SIGNAL Quality value, except to note that the Attention and Meditation

values will not be updated while POOR_SIGNAL is greater than zero, and that the headset is not being

worn while POOR_SIGNAL is 200. e POOR_SIGNAL Quality value is more useful to some applica-

tions which need to be more sensitive to noise (such as some medical or research applications), or

applications which need to know right away when there is even minor noise detected.

RAW_DATA

is data type supplies the raw sample values acquired at the bio-sensor. e sampling rate (and

therefore output rate), possible range of values, and interpretations of those values (conversion from

raw units to volt) for this data type are dependent on the hardware characteristics of the inkGear

hardware device performing the sampling. You must refer to the documented development specs of

each type of inkGear hardware that your app will support for details.

As an example, the majority of inkGear devices sample at 512Hz, with a possible value range of

-32768 to 32767.

As another example, to convert TGAT-based EEG sensor values (such as TGAT, TGAM, MindWave

Mobile, MindWave, MindSet) to voltage values, use the following conversion:

(rawValue * (1.8/4096) / 2000

Note that ECG/EKG raw values from CardioChip/BMD10X-based devices must use a diﬀerent con-

version.

RAW_MULTI

is data type is not currently used by any current commercially-available inkGear products. It is kept

here for backwards compatibility with some end-of-life products, and as a placeholder for possible future

products.

EEG

ese data types are only available from EEG sensor hardware devices, such as the MindWave Mobile,

MindSet, MindBand, and TGAM chips and modules.

ATTENTION

is int value reports the current eSense Attention meter of the user, which indicates the intensity of

a user's level of mental "focus" or "attention", such as that which occurs during intense concentration

EEG

Chapter 4 – ThinkGear Data Types

and directed (but stable) mental activity. Its value ranges from 0 to 100. Distractions, wandering

thoughts, lack of focus, or anxiety may lower the Attention meter levels. See eSense\texttrademark

Meters below for details about interpreting eSense levels in general.

By default, output of this Data Value is enabled. It is typically output once a second.

MEDITATION

is unsigned one-byte value reports the current eSense Meditation meter of the user, which indicates

the level of a user's mental "calmness" or "relaxation". Its value ranges from 0 to 100. Note that

Meditation is a measure of a person's mental levels, not physical levels, so simply relaxing all the

muscles of the body may not immediately result in a heightened Meditation level. However, for

most people in most normal circumstances, relaxing the body often helps the mind to relax as well.

Meditation is related to reduced activity by the active mental processes in the brain, and it has long

been an observed eﬀect that closing one's eyes turns oﬀ the mental activities which process images

from the eyes, so closing the eyes is often an eﬀective method for increasing the Meditation meter level.

Distractions, wandering thoughts, anxiety, agitation, and sensory stimuli may lower the Meditation

meter levels. See "eSense Meters" below for details about interpreting eSense levels in general.

By default, output of this Data Value is enabled. It is typically output once a second.

eSense™ Meters

For all the diﬀerent types of eSenses (i.e. Attention, Meditation), the meter value is reported on a

relative eSense scale of 1 to 100. On this scale, a value between 40 to 60 at any given moment in time

is considered "neutral", and is similar in notion to "baselines" that are established in conventional EEG

measurement techniques (though the method for determining a inkGear baseline is proprietary and

may diﬀer from conventional EEG). A value from 60 to 80 is considered "slightly elevated", and may

be interpreted as levels being possibly higher than normal (levels of Attention or Meditation that may

be higher than normal for a given person). Values from 80 to 100 are considered "elevated", meaning

they are strongly indicative of heightened levels of that eSense.

Similarly, on the other end of the scale, a value between 20 to 40 indicates "reduced" levels of the

eSense, while a value between 1 to 20 indicates "strongly lowered" levels of the eSense. ese levels

may indicate states of distraction, agitation, or abnormality, according to the opposite of each eSense.

An eSense meter value of 0 is a special value indicating the inkGear is unable to calculate an eSense

level with a reasonable amount of reliability. is may be (and usually is) due to excessive noise as

described in the POOR_SIGNAL section above.

e reason for the somewhat wide ranges for each interpretation is that some parts of the eSense

algorithm are dynamically learning, and at times employ some "slow-adaptive" algorithms to adjust

to natural uctuations and trends of each user, accounting for and compensating for the fact that

EEG in the human brain is subject to normal ranges of variance and uctuation. is is part of the

reason why inkGear sensors are able to operate on a wide range of individuals under an extremely

wide range of personal and environmental conditions while still giving good accuracy and reliability.

Developers are encouraged to further interpret and adapt these guideline ranges to be ne-tuned for

their application (as one example, an application could disregard values below 60 and only react to

values between 60-100, interpreting them as the onset of heightened attention levels).

BLINK

is int value reports the intensity of the user's most recent eye blink. Its value ranges from 1 to 255

and it is reported whenever an eye blink is detected. e value indicates the relative intensity of the

blink, and has no units.

EEG

Chapter 4 – ThinkGear Data Types

EEG_POWER

is Data Value represents the current magnitude of 8 commonly-recognized types of EEG frequency

bands.

e eight EEG powers are: delta (0.5 - 2.75Hz), theta (3.5 - 6.75Hz), low-alpha (7.5 - 9.25Hz),

high-alpha (10 - 11.75Hz), low-beta (13 - 16.75Hz), high-beta (18 - 29.75Hz), low-gamma (31 -

39.75Hz), and mid-gamma (41 - 49.75Hz). ese values have no units and are only meaningful for

comparison to the values for the other frequency bands within a sample.

By default, output of this Data Value is enabled, and it is output approximately once a second.

THINKCAP_RAW

is data type is not currently used by any current commercially-available inkGear products. It is kept

here for backwards compatibility with some end-of-life products, and as a placeholder for possible future

products.

POSITIVITY

Values -100 to +100, indicates that the subject is attentive, the more negative values mean the subject

is less attentive and the more positive values mean more attentive.

FAMILIARITY

Can be used to compare a test subjects familiarity with a newly learned motor skill. One minute of

collected data could constitute a trial, and will produce a familiarity index value for this subject. e

familiarity index of separate trials of the motor skill can be compared for the same subject.

DIFFICULTY

Can be used to compare a diﬃcult a test subjects nds a newly learned motor skill. One minute of

collected data could constitute a trial, and will produce a diﬃculty index value for this subject. e

diﬃculty index of separate trials of the motor skill can be compared for the same subject.

ECG/EKG

ese data types are only available from ECG/EKG sensor (CardioChip) hardware devices, such as

the CardioChip Starter Kit Unit and BMD10X chips and modules.

HEART_RATE

is int value reports the current heart rate of the user, in units of beats per minute (BPM). Unlike

many other commonly seen reports of heart rate from other devices, this value is calculated precisely

in real time based on the actual time between each and every one of the user's actual R-peaks. is

results in a very precise and continuous reporting of Heart Rate that changes with the actual beat-to-

beat uctuations of every single one of the user's actual heart beats.

To easily get an "smoothed, averaged" heart rate value which is more commonly seen as reported by

other ECG/EKG devices, use these values as inputs to the Smoothed Heart Rate described below.

ECG/EKG

Chapter 4 – ThinkGear Data Types

Smoothed Heart Rate

Typically, when viewing a "Heart Rate" value on many ECG/EKG devices, a "smoothed" value is dis-

played so that there aren't rhythmic uctuations in the viewed heart rate based on the subject's natural

HRV rhythms. e same sort of "smoothed" eﬀect can be achieved against the precise HEART\_RATE

values, by using the getAcceleration() method of the HeartRateAcceleration class provided

in this SDK.

See the section on Heart Rate Acceleration for a description of how to calculate the Smoothed Heart

Rate, and then refer to the API Reference for full details on the HeartRateAcceleration class.

Heart Rate Acceleration

A potentially useful metric of Heart Rate is the acceleration rate. A positive acceleration value indicates

the user's heart rate is speeding up by a certain number of BPM over a given period of time (such as

over 10 seconds), while a negative acceleration value indicates the user's heart rate is slowing down by

a certain number of BPM over a given period. When starting exercise, or during rest after exercise,

this acceleration metric could be used as an indicator of how quickly a person's heart is speeding up

to match the activity, or how quickly it is slowing down back to normal, respectively.

To calculate Heart Rate Acceleration (and/or Smoothed Heart Rate), rst initialize a HeartRateAccel-

eration() object in your app:

HeartRateAcceleration heartRateAcceleration = new HeartRateAcceleration();

is will initialize the calculation to use a period of 10 second. (You can instead choose to use the over-

loaded constructors to initialize the calculation using a longer or shorter period of time, as appropriate

for your app).

en, whenever a new Heart Rate value becomes available to your app, get the Smoothed Heart Rate

and acceleration values like this:

int[] result = heartRateAcceleration.getAcceleration( heartRate, poorSignal );

if( result[0] != -1 ) {

int smoothedHeartRate = result[0];

int heartRateAcceleration = result[1];

}

Refer to the API Reference documentation for full details of the HeartRateAcceleration class.

Target Heart Rate for Physical Training

Given information about a user's age and gender, it is possible to determine a target range of heart

rates for them to achieve particular physical training "zones". Combined with the HEART\_RATE

information reported by the sensor, an app could advise a user whether their current heart rate is

within their target training zone (such as right after a workout).

To determine the target range of heart rates for a person, rst create a TargetHeartRate object:

TargetHeartRate targetHeartRate = new TargetHeartRate();

en, at any time, to determine the target range of heart rates (min to max values) for a a user to

achieve a particular physical training zone, use the getTargetHeartRate() method:

ECG/EKG

Chapter 4 – ThinkGear Data Types

int age = 25;

String gender = "Male";

String zone = "Aerobic";

int[] range = targetHeartRate.getTargetHeartRate( age, gender, zone );

int lowerBound = range[0];

int upperBound = range[1];

e lowerBound and upperBound could then be compared to the user's HEART\_RATE or Smoothed

Heart Rate to determine if the user is within the their target range for the target physical training zone.

e gender must be either "Male" or "Female". e zone must be one of:

•"Light Exercise"

•"Weight Loss"

•"Aerobic"

•"Conditioning"

•"Athletic"

If any of the arguments are incorrect, then the method will return an int[] of -1, -1 .

Important: e heart rate should not be measured while the user is engaged in physical activity; the

user should temporarily stop the activity and then measure their heart rate.

(References)

1. http://www.heart.org/HEARTORG/GettingHealthy/PhysicalActivity/Target-Heart-Rates\_UCM\_434341\_Article.jsp

2. http://www.cdc.gov/physicalactivity/everyone/measuring/heartrate.html

3. http://www.heart.com/heart-rate-chart.html

4. http://www.thewalkingsite.com/thr.html

Heart Fitness Level

Given a person's age, gender, and current resting heart rate, it is possible to get a general idea of the

person's current heart health and tness, labeling them as one of "Poor", "Below Average", "Average",

"Above Average", "Good", "Excellent", or "Athlete".

To determine the heart tness level for a person, rst create a HeartFitnessLevel object:

HeartFitnessLevel heartFitnessLevel = new HeartFitnessLevel();

en, once you have the age, gender, and current resting heart rate of the person, use the getHeart-

FitnessLevel() method:

int age = 25;

String gender = "Male";

String restingHR = 60;

string heartFitnessLevel = heartFitnessLevel.getHeartFitnessLevel( age, gender, restingHR );

ECG/EKG

Chapter 4 – ThinkGear Data Types

e gender must be one of "Male" or "Female", otherwise the method will simply return the empty

string ("").

e heartFitnessLevel will be returned as one of "Poor", "Below Average", "Average", "Above

Average", "Good", "Excellent", or "Athlete".

(References)

1. http://www.topendsports.com/testing/heart-rate-resting-chart.htm

RELAXATION

e Relaxation data value gives an indication of whether a user's heart is showing indications of relax-

ation, or is instead showing indications of excitation, stress, or fatigue, based on the user's Heart Rate

Variability (HRV) characteristics. It is reported on a scale from 1 to 100. High Relaxation values tend

to indicate a state of relaxation, while low values tend to indicate excitation, stress, or fatigue.

To receive these values via MSG_RELAXATION messages to your app's Handler, simply have the

TGDevice connected to a inkGear ECG/EKG sensor (CardioChip), and a user contacting the

ECG/EKG sensor hardware properly for at least one minute continuously with a good, clean signal

(SENSOR_STATUS == 200 for 1 minute). If the signal is interrupted, and SENSOR_STATUS

becomes anything other than 200, then this calculation is reset and starts over, requiring another

minute of clean data to report a MSG_RELAXATION.

For best results, the user should be sitting calmly during data collection.

(References)

1. Neurosci Biobehav Rev. 2009 Feb; 33(2): 71-80. Epub 2008 Jul 30. Heart rate variability

explored in the frequency domain: a tool to investigate the link between heart and behavior.

Montano N, Porta A, Cogliati C, Costantino G, Tobaldini E, Casali KR, Iellamo F.

2. Int J Cardiol. 2002 Jul; 84(1): 1-14. Functional assessment of heart rate variability: physio-

logical basis and practical applications. Pumprla J, Howorka K, Groves D, Chester M, Nolan

3. International Conference on Computer and Automation Engineering. A Review of Measure-

ment and Analysis of Heart Rate Variability. Dipali Bansal, Munna Khan, A. K. Salhan.

4. Neurosci Biobehav Rev. 2009 Feb; 33(2): 81-8. Epub 2008 Aug 13. Claude Bernard and the

heart-brain connection: further elaboration of a model of neurovisceral integration. ayer JF,

Lane RD.

RESPIRATION

e Respiration data value reports a user's approximate respiration rate in breaths per minute. It is

calculated from the user's ECG/EKG and Heart Rate Variability (HRV) characteristics.

To receive these values via MSG_RESPIRATION Messages to your app's Handler, simply have the

TGDevice connected to a inkGear ECG/EKG sensor (CardioChip), and a user contacting the

ECG/EKG sensor hardware properly for at least 64 seconds continuously with a good, clean sig-

nal (SENSOR_STATUS >= 200 for 64 seconds). Once the rst MSG_RESPIRATION Message is

received, updated values will be sent via subsequent MSG_RESPIRATION Messages every 10 sec-

onds. If the signal is ever interrupted, and SENSOR_STATUS becomes anything less than 200,

then this calculation is reset and starts over, requiring another 64 seconds of clean data to report a

MSG_RESPIRATION.

ECG/EKG

Chapter 4 – ThinkGear Data Types

For best results, the user should be sitting calmly during data collection.

(References)

1. Rosenthal, Talma, Ariela Alter, Edna Peleg, and Benjamin Gavish. "Device-guided breathing

exercises reduce blood pressure: ambulatory and home measurements." American Journal of

Hypertension. 14. (2001): 74–76.

Heart Risk Awareness

e Heart Risk Awareness data value aims to raise awareness if the HRV is very low, as low HRV has

been shown to be associated with increased risk of mortality.

To determine the Heart Risk Awareness for a person, rst create a NeuroSkyHeartMeters object:

NeuroSkyHeartMeters neuroSkyHeartMeters = new NeuroSkyHeartMeters();

en, use one of the following two methods to calculate:

Using R-R Intervals Collection

Whenever your app's Handler receives a MSG_EKG_RRINT Message, save the R-R Interval value

into a buﬀer. Once you have at least 60 R-R Intervals in the buﬀer, use the calculateHear-

tRiskAware( Integer[] rrIntervalInMS ) method of the NeuroSkyHeartMeters class:

private final Handler handler = new Handler() {

ArrayList<Integer> temp_rrintBuffer = new ArrayList<Integer>();

Integer[] rrinterBuffer = new Integer[60];

@Override

public void handleMessage( Message msg ) {

switch( msg.what ) {

//...

case MSG_EKG_RRINT:

temp_rrintBuffer.add( msg.arg1 );

if( temp_rrintBuffer.size()==60 ) {

for( int i = 0; i<60; i++ ) {

rrintBuffer[i] = temp_rrintBuffer.get(i);

}

temp_rrintBuffer.clear();

int heartRiskAwareness = neuroSkyHeartMeters.calculateHeartRiskAware(

rrintBuffer );

}

break;

//...

} /* end switch on message type */

} /* end handleMessage() */

}; /* end Handler */

ECG/EKG

Chapter 4 – ThinkGear Data Types

Using Storage Data

Simply use the calculateHeartRiskAware( String fileName ) method in the NeuroSkyHeart-

Meters class:

int heartRiskAwarness = neuroSkyHeartMeters.calculateHeartRiskAware( "john" );

Note: e parameter "leName" in the method is the name of the le that stored calculated heart age.

Results

e return value will be a "Heart Risk Awareness" index that will be one of "0", "1","2" or "3". e

following information could be provided by the app to the user based on their "Heart Risk Awareness":

HeartRiskAwareness = 0

Your HRV does not appear to be low at this time. Low HRV has been shown to be related to increased

risk of heart attack and mortality. is means your HRV suggests you currently have limited or no

risk.

HeartRiskAwareness = 1

Your HRV is a relatively low. Low HRV has been shown to be related to increased risk of heart attack

and mortality. It is recommended that you stay active and be careful about what you eat. You could

eat foods that can prevent heart attack, such as nuts, sh, coarse grains, vegetables, and you may also

drink green tea.

HeartRiskAwareness = 2

Your HRV is low. Low HRV has been shown to be related to increased risk of heart attack and

mortality. Bad habits that inuence the health of your heart include consumption of food with high

fat and sugar content, smoking, drinking alcohol, lack of exercise, high mental pressure, and long

periods of sleep deprivation. It is recommended that you change your bad habits by drinking only

a moderate amount of alcohol, eating healthy, getting appropriate exercise, controlling your body

weight, developing good sleeping habits, and keeping a peaceful state of mind.

HeartRiskAwareness = 3

Your HRV is very low. Low HRV has been shown to be related to increased risk of heart attack and

mortality. It is recommended that you change some of your habits. You may consider to quit smoking,

stop drinking alcohol. You should also make sure to get appropriate amount of exercise, control your

body weight, develop good sleeping habits, eat more ber and less salt, and keep a peaceful state of

mind. Symptoms of heart attack include chest pain, shoulder pain, trouble breathing, poor digestion,

and severe fatigue. Please see a doctor if these symptoms occur to you.

(for References, see Heart Age)

HEART_AGE

e Heart Age data value provides an indication of the relative age of a subject heart, based on their

Heart Rate Variability (HRV) characteristics as compared to the general population. A low HRV is

associated with an increased risk of mortality, and is represented by a Heart Age that is possibly higher

than the user's biological age (such as a 35 year old with HRV characteristics that suggest a heart age

of 45). e calculation will take into account the user's reported biological age. Use of this data value

is only recommended for subjects that are at least 10 years old (biological age).

ECG/EKG

Chapter 4 – ThinkGear Data Types

To receive these values via MSG_HEART_AGE Messages to your app's Handler, rst set the user's

biological age via the TGDevice object: tgDevice.inputAge = 25 (of course replacing 25 with

the user's actual age). en, simply have the TGDevice connected to a inkGear ECG/EKG sensor

(CardioChip), and a user contacting the ECG/EKG sensor hardware properly for at least 60 heart

beats continuously with a good, clean signal (SENSOR_STATUS >= 200 for 60 heart beats). If

the signal is ever interrupted, and SENSOR_STATUS becomes anything less than 200, then this

calculation is reset and starts over, requiring another 60 heart beats of clean data before it can report

a MSG_HEART_AGE.

For best results, the user should be sitting calmly during data collection.

An example of how your app and users could potentially use this information would be if your app

displayed messages like the following to the user based on their Heart Age value:

Adolescent heart: <25 years old

Your heart age is xx years old, which is greater/less than your actual age by xx years. Your young heart

age allows you to be energetic and to think actively, which helps you deal with demanding work and

exercise. A young heart also needs to be taken care of. It is recommended that you avoid staying up

late at night, get appropriate amounts of exercise, and maintain a peaceful and positive attitude. You

should also eat more fresh fruits and vegetables and cut down on fatty foods to keep your heart at its

young state.

Young heart: 26 – 39

Your heart age is xx years old, which is greater/less than your actual age by xx years. You have a mature

heart. While in a tense working environment, please don’t forget to get good amounts of sleep and

exercise, eat well, and take good care of yourself.

Middle-aged heart: 40 – 55

Your heart age is xx years old, which is greater/less than your actual age by xx years. Please pay close

attention to your heart health and plan your work and life accordingly to lessen the burden on your

heart. It is recommenced that you eat foods that are good for your heart, such as sh, whole grains,

beans, nuts, vegetables, red wine, and green tea. You should also get a reasonable amount of exercise

to strengthen your heart.

Young elderly heart: 56 – 70

Your heart age is xx years old, which is greater/less than your actual age by xx years. Your heart’s

function is taking a step towards old age. It is recommended that you live with discipline and avoid

straining your body or becoming overly excited or nervous. You should also have regular physical

examinations and eat more foods that are good for your heart, such as sh, coarse grains, beans, nuts,

vegetables, red wine, and green tea. It is also important for you to get a reasonable amount of exercise

so that your heart continues to work eﬀectively.

Elderly heart: >70 years old

Your heart age is xx years old, which is greater/less than your actual age by xx years. It is recommended

that you regularly visit your doctor to get physical examinations and carefully follow your doctor’s

instructions in order to prevent and treat heart disease. You should also get appropriate amounts of

exercise and keep a peaceful state of mind. Living with discipline and eating healthy can improve the

function of your cardiovascular system and prevent heart disease.

(References)

1. Res Sports Med. 2010 Oct; 18(4):263-9. Age and heart rate variability after soccer games. Yu

S, Katoh T, Makino H, Mimuno S, Sato S.

ECG/EKG

Chapter 4 – ThinkGear Data Types

2. J Am Coll Cardiol. 1998 Mar 1; 31(3): 593-601. Twenty four hour time domain heart rate

variability and heart rate: relations to age and gender over nine decades. Umetani K, Singer

DH, McCraty R, Atkinson M.

3. Am J Cardiol. 2010 Apr 15; 105(8): 1181-5. Epub 2010. Relation of high heart rate variability

to healthy longevity. Zulqar U, Jurivich DA, Gao W, Singer DH.

4. Cardiovasc Electrophysiol. 2003 Aug; 14(8): 791-9. Circadian prole of cardiac autonomic

nervous modulation in healthy subjects: diﬀering eﬀects of aging and gender on heart rate vari-

ability. Bonnemeier H, Richardt G, Potratz J, Wiegand UK, Brandes A, Kluge N, Katus HA.

5. Pacing Clin Electrophysiol. 1996 Nov; 19(11 Pt 2): 1863-6. Changes in heart rate variability

with age. Reardon M, Malik M.

Personalization

is algorithm allows the TGDevice to try to recognize a connected user based on their ECG/EKG

data. To use it, one or more users should "train" their ECG/EKG data into the TGDevice. en,

whenever the TGDevice is reading ECG data from a user, it can attempt to identify which of the

trained users (if any) is the one it is reading from.

ere are two steps to use the Personalization algorithm:

Training

e rst part records ECG/EKG data of user, using the EKGstartLongTraining( String user-

Name ) method in the TGDevice class. If the user then keeps good, clean contact with the ECG/EKG

sensor hardware properly, a MSG_EKG_TRAIN_STEP Message will be sent to your app's Handler to show

which step you are currently on. After two steps are nished, it will send a MSG_EKG_TRAINED Mes-

sage to your app's Handler to indicate that the recording is nished, then your Handler should use

the EKGstopTraining() method to stop.

Detection

is part is used to recognize user based on saved data from the rst part. To recognize user, invoke the

EKGstartDetection() method. en, if the user keeps a good, clean contact with the ECG/EKG

sensor hardware, the TGDevice will send a MSG_EKG_IDENTIFIED Message to your app's Handler.

e return value will be one of the registered user names, or "Unknown".

private final Handler handler = new Handler() {

@Override

public void handleMessage( Message msg ) {

switch( msg.what ) {

//...

case MSG_EKG_TRAIN_STEP:

int trainStep = msg.arg1;

break;

case MSG_EKG_TRAINED:

tgDevice.EKGstopTraining();

break;

ECG/EKG

Chapter 4 – ThinkGear Data Types

case MSG_EKG_IDENTIFIED:

String result = msg.arg1;

tgDevice.EKGstopDetection();

break;

//...

} /* end switch on message type */

} /* end handleMessage() */

}; /* end Handler */

//...

tgDevice.EKGstartLongTraining( "John" );

//...

tgDevice.EKGstartDetection();

EKG_RRINT

Whenever an R-peak is detected along a user's PQRST ECG/EKG, then a MSG_EKG_RRINT Mes-

sage is sent to your app's Handler indicating the R-R interval, in milliseconds, since the last R-peak.

ECG/EKG

Chapter 5

Proper App Design

Important: Before releasing an app for real-world use, make sure your app considers or handles the

following:

• If your app's Handler receives a MSG_STATE_CHANGE Message with any value other than STATE_CONNECTING

or STATE_CONNECTED, it should carefully handle each possible error situation with an appropri-

ate message to the user via the app's UI. Not handling these error cases well in the UI almost

always results in an extremely poor user experience of the app. Here are some examples:

–If a STATE_ERR_BT_OFF Message is received, the user should be prompted to turn on their

Bluetooth adapter, and then they can try again.

–If a STATE_ERR_NO_DEVICE Message is received, the user should be reminded to rst pair

their inkGear hardware device to their Android device's Bluetooth, according to the

instructions they received with their inkGear hardware device.

–If a STATE_NOT_FOUND Message is received, the user should be reminded to check that

their inkGear hardware device is properly paired to their Android device (same as the

STATE_ERR_NO_DEVICE case), and if so, that their inkGear hardware device is turned

on, in range, and has enough battery or charge.

–See TGDevice States for more info.

• Always make sure your app is handling the POOR\_SIGNAL/SENSOR\_STATUS Data Type.

It is output by almost all inkGear devices, and provides important information about whether

the sensor is properly in contact with the user. If it is indicating some sort of problem (problem

== not 0 for EEG devices, or not 200 for ECG/EKG devices), then your app should notify the

user to properly wear the inkGear hardware device, and/or disregard any other reported data

values while the POOR\_SIGNAL/SENSOR\_STATUS continues to indicate a problem, as

appropriate for your app.

• To make the user experience consistent, familiar, and easy-to-learn and use for end customers

across platforms and devices, your app should be designed to follow the guidelines and conven-

tions described in NeuroSky's App Standards.

Chapter 6

Troubleshooting

Note: ere are currently no known issues. If you encounter any bugs or issues, please visit

http://support.neurosky.com, or contact support@neurosky.com.

If you need further help, you may visit http://developer.neurosky.com to see if there is any new infor-

mation.

To contact NeuroSky for support, please visit http://support.neurosky.com, or send email to sup-

port@neurosky.com.

For developer community support, please visit our community forum on http://www.linkedin.com/groups/NeuroSky-

Brain-Computer-Interface-Technology-3572341

Chapter 7

Important Notices

e algorithms included in this SDK are solely for promoting the awareness of personal wellness

and health and are not a substitute for medical care. e algorithms are not to be used to diagnose,

treat, cure or prevent any disease, to prescribe any medication, or to be a substitute for a medical

device or treatment. In some circumstances, the algorithm may report false or inaccurate results. e

descriptions of the algorithms or data displayed in the SDK documentation, are only examples of the

particular uses of the algorithms, and NeuroSky disclaims responsibility for the nal use and display

of the algorithms internally and as made publically available.

e algorithms may not function well or may display accurate data if the user has a pacemaker.

All ECG data should be collected while the user is seated quietly, breathing regularly, with minimal

movement, for best results.

Warnings and Disclaimer of Liability

THE ALGORITHMS MUST NOT BE USED FOR ANY ILLEGAL USE, OR AS COMPO-

NENTS IN LIFE SUPPORT OR SAFETY DEVICES OR SYSTEMS, OR MILITARY OR NU-

CLEAR APPLICATIONS, OR FOR ANY OTHER APPLICATION IN WHICH THE FAIL-

URE OF THE ALGORITHMS COULD CREATE A SITUATION WHERE PERSONAL IN-

JURY OR DEATH MAY OCCUR. YOUR USE OF THE SOFTWARE DEVELOPMENT KIT,

THE ALGORITHMS AND ANY OTHER NEUROSKY PRODUCTS OR SERVICES IS “AS-IS,”

AND NEUROSKY DOES NOT MAKE, AND HEREBY DISCLAIMS, ANY AND ALL OTHER

EXPRESS AND IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, WAR-

RANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE, AND

ANY WARRANTIES ARISING FROM A COURSE OF DEALING, USAGE, OR TRADE PRAC-

TICE.

IN NO EVENT SHALL NEUROSKY BE LIABLE FOR ANY SPECIAL, INCIDENTAL OR CON-

SEQUENTIAL DAMAGES, INCLUDING BUT NOT LIMITED TO LOSS OF PROFITS OR

INCOME, WHETHER OR NOT NEUROSKY HAD KNOWLEDGE, THAT SUCH DAM-

AGES MIGHT BE INCURRED.

Chapter 8

APPENDIX A: Additional

References

•http://developer.android.com/guide/topics/wireless/bluetooth.html

Chapter 9

APPENDIX B: UART (Non-Bluetooth)

Connections

For Android devices, such as phones or tablets, that are designed to be physically connected to inkGear

hardware devices via UART (especially CardioChip), the TG-SDK for Android oﬀers an alternate

constructor and connect method:

public TGDevice( InputStream s, OutputStream o, Handler h );

public synchronized void connectStream( boolean rawEnabled );

Instead of taking a BluetoothAdapter in the constructor and using Bluetooth for communication,

it instead takes an InputStream and OutputStream for communication. e connectStream()

method is then analogous for this constructor as the connect() method for the Bluetooth-based

constructor.

To use this API of the SDK, you must rst prepare the Android/Linux system as follows:

1. Physically connect the UART pins of the inkGear hardware device to the UART pins of the

Android device

2. Make sure the Linux OS layer beneath the Android OS layer makes the UART port available as

a serial port, such as "/mnt/uart1"

en, because Android does not provide APIs to directly access serial ports, we must go around the

Android layer to the Linux serial port layer using JNI:

1. Compile the uart.cpp le (provided separately by NeuroSky, along with a makele) into a

native library le called libJRDBCM.lib that JNI will be able to call. is library will make it

possible for your app to open the serial port.

2. Use JNI in your app to call the SerialJNI_open() method from within your app. is will

open a FileDescriptor, from which you can obtain a FileInputStream and FileOutput-

Stream for use with the TGDevice constructor:

public class Native {

static {

System.loadLibrary( "JRDBCM" );

}

String dev = "/mnt/uart1";

  FileDescriptor serialPort = Native.SerialJNI_open( dev );

InputStream iStream = new FileInputStream( serialPort );

OutputStream oStream = new FileOutputStream( serialPort );

TGDevice tgDevice = new TGDevice( iStream, oStream, handler );

tgDevice.connectStream( true );

From here on out, the TG API is exactly the same as for Bluetooth described in the rest of this doc-

ument. Just remember to close your FileDescriptor using Native.SerialNJI.close() when

you are done with the TGDevice, after the TGDevice is closed.

ThinkGear Development Guide For Android Think Gear

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