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Smart SMS-SMS Application Management Platform

BRAIN COMPUTER INTERFACE APPLICATION

FRAMEWORK

T.N. Malalasekera

(IT 10 0560 80)

Degree of Bachelor of Science in Information Technology

Department of Information Technology

Sri Lanka Institute of Information Technology

October 2013

H. H. Rajamanthrie IT 10 0296 64

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Smart SMS-SMS Application Management Platform

BRAIN COMPUTER INTERFACE APPLICATION

FRAMEWORK

T.N. Malalasekera

(IT 10 0560 80)

Dissertation submitted in partial fulfillment of the requirements for the degree

of Science

Department of Information Technology

Sri Lanka Institute of Information Technology

October 2013

H. H. Rajamanthrie IT 10 0296 64

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DECLARATION

I declare that this is my own work and this dissertation does not incorporate without

acknowledgment any material previously submitted for a Degree or Diploma in any Other

University or Institute of higher learning and to the best of my knowledge and belief it does

not contain any material previously published or written by another person except where the

acknowledgment is made in the text.

Also, I hereby grant to Sri Lanka Institute of Information Technology the nonexclusive right

to reproduce and distribute my dissertation, in whole or in part in print, electronic or other

medium. I retain the right to use this content in whole or part in future works (such as articles

or books)

Signature: Date: 23.10.2013

The above candidate has carried out research for the B.Sc. Dissertation under my supervision.

Signature of the supervisor: Date: 23.10.2013

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BRAIN COMPUTER INTERFACE APPLICATION FRAMEWORK

ACKNOWLEDGEMENT

We take this opportunity to express our deep sense of gratitude to those who contributed to

either our collective or individual efforts. Particularly, our special thanks go to Sri Lanka

Institute of Information Technology (SLIIT) for providing necessary resources to complete

the project successfully. Special thanks are extended to the lecture in-charge, Mr. Jayantha

Amararachchi who provided the required lecture materials and the necessary guidance to

complete the project successfully. Our heartfelt thanks go out to the supervisor of our project,

Dr. Rohana Priyantha Thilakumara and the co-supervisor, Mr. Darshika Koggalahewa for the

kind patience, guidance and constant support rendered to us at all the stages of the project,

right from the very beginning, till the final presentation of our completed project. The team

extends sincere gratitude to all colleagues, who forwarded their enthusiastic ideas during the

requirements gathering phase of the project. The teammates would also like to thank all the

staff members of the SLIIT Malabe campus for their valuable suggestions and opinions that

appear in the final product. Finally, we thank all who lend their kind support; friends and

families who continued to give their insights, patience, support and co-operation which

motivated us in reaching greater heights.

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ABSTRACT

Brain-Computer Interface (BCI) technology is a potentially powerful communication and

control option in the interaction between Human Brain and Computer systems. A BrainComputer Interface (BCI) is a direct communication pathway between the brain and an

external device. As many companies have introduced many BCI devices in to the market

developers have focused on developing BCI based applications. Even though there are many

devices available, they are not capable enough for focusing on developing advanced

application. Neurosky is one of the leading company which producing BCI devices to the

industry. Neurosky mind wave device is capable of giving brain signals according to the

attention and meditation level as well as the eye blink strength. In the proposed project the

team intended to develop a framework which will be utilized every functions needed by game

developers. But according to the data has collected using various users it clarified that the

device is not capable of developing an advance application as it was failed to give a stable

value which will be helped in developing advanced applications. Therefore within the project,

the team is introduced some applications which will be useful for disable people and which

will be giving entertainment for the users.

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ContentsDECLARATION.................................................................................................................................... 1

ACKNOWLEDGEMENT....................................................................................................................... i

ABSTRACT............................................................................................................................................ ii

List of figures......................................................................................................................................... iv

List of Abbreviations.............................................................................................................................. v

1 INTRODUCTION.......................................................................................................................... 1

1.1 Background Context............................................................................................................... 1

1.2 Research Problem to be addressed.......................................................................................... 3

1.3 Research Questions........................................................................................................................... 5

2 CONTENT...................................................................................................................................... 6

2.1 Addressing the Literature........................................................................................................ 6

2.2 Methodology........................................................................................................................... 9

2.2.1 Overview......................................................................................................................... 9

2.2.2 Overview of the System Design.................................................................................... 10

2.2.3 User Characteristics...................................................................................................... 11

2.2.4 Product functions.......................................................................................................... 12

2.2.5 Tools and Technologies................................................................................................ 13

2.2.6 Product Constraints....................................................................................................... 14

2.2.7 Assumptions and Dependencies.................................................................................... 15

2.3 Research Findings................................................................................................................. 16

3 RESULT AND DISCUSSION..................................................................................................... 22

4 CONCLUSION............................................................................................................................. 31

References ............................................................................................................................................ 32

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List of figures

Figure 1................................................................................................................................................... 8

Figure 2................................................................................................................................................. 10

Figure 3................................................................................................................................................. 18

Figure 4................................................................................................................................................. 18

Figure 5................................................................................................................................................. 19

Figure 6................................................................................................................................................. 19

Figure 7................................................................................................................................................. 20

Figure 8................................................................................................................................................. 20

Figure 9................................................................................................................................................. 21

Figure 10............................................................................................................................................... 22Figure 11............................................................................................................................................... 23

Figure 12............................................................................................................................................... 24

Figure 13............................................................................................................................................... 25

Figure 14............................................................................................................................................... 26

Figure 15............................................................................................................................................... 27

Figure 16............................................................................................................................................... 28

Figure 17............................................................................................................................................... 29

Figure 18............................................................................................................................................... 30

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List of Abbreviations

EEG Electro - Electroencephalogram

BCI Brain Computer InterfacefMRI functional Magnetic Resonance Imaging

EEC Encephalogram

SSVEP Steady State Visual Evoked Potential

ALS Amyotrophic Lateral Sclerosis

API Application Programming Interface

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1 INTRODUCTION1.1 Background ContextAlthough it seems a science fiction, there are currently brain-computer interfaces, and

innovative research are rapidly expanding the level of control that can be achieved. The

researchers, psychologists, artists, and others have been experimenting with brain-computer

interfaces that read noninvasive brain signals with an electroencephalogram (EEG).

Computer Interfaces based on EEG of the brain by sensors placed on the head to detect brain

waves and feed them as input to a computer.

BCI has always been a topic of interest in the field of Rehabilitation and Assistive

Technology. BCI The potential is limitless when it comes to improving the lives of people

with disabilities. For example, BCI-based systems could be used for people who are severely

restricted or cannot move their hands (Eg:- spinal cord injury) to conduct an electric

wheelchair, operate appliances and so on. Or even to help someone in a vegetative state to

communicate by speaking the words that the individual would like to say.

There are two main categories of BCI systems - "invasive" and "noninvasive". Invasive

systems interact directly with the brain via electrodes / sensors are implanted in the brain or

on its surface. While non-invasive brain interact indirectly via electrodes / sensors on the

surface of the head that detects emissions brain signals (eg electroencephalography (EEG),

magnetic resonance imaging (fMRI), and magnetic sensor systems).

Noninvasive BCI systems usually consist of a head cover (aka EEG cap) with multiple holes /

slots to put the electrodes in the relevant areas of the surface of the head to detect and recordelectrical signals from the brain emitter. Electro gel is used in the electrodes to improve the

contact between the scalp and the electrode. Due to the requirement of a gel such electrodes

are also known as wet electrodes. Existing systems can be from a few to more than 100

electrodes. The Practical using wet electrodes, as an example of gel drying, repeated cleaning

of the electrodes and the skin head to configure EEG Cap, sensitive skin irritation due to the

application of gel, etc. - does not make them suitable for a quick setup and everyday use. Due

to the above disadvantages that prompted the development of dry electrodes. Unlike wet

electrode, dry electrodes do not require the use of gel and can be configured directly direct

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into the EEG Cap. Although still in the infancy of its developmental cycle, dry electrodes are

quickly catching up in terms of detecting high quality brain signals as their wet counterpart.

Regular comparison studies are being carried out to evaluate the performance of Wet vs. Dry

Electrodes within the context of EEG based noninvasive BCI.

With the advancement of technology, several companies have been motivated in producing

BCI devices to the industry. Most commercially available devices are produced using dry

electrodes. NeuroSky wave mobile headsets mind and brain waves are one of the most

popular devices among developers and new users. In application development, developers are

driven in using these devices. However, some devices are not able to meet the requirements

of the developer in the development of advanced applications. When collecting data

regarding the level of attention and meditation levels of users can vary from one to another.

And when comparing the final results that you can make the output given by the device is not

much more able to use in developing applications. Because it is a mandatory to achieve a

stable average value of meditation and the level of care.

But most devices on the market are not good enough for the development of advanced

applications. Instead, they are suitable for use in applications simple BCI joined Simple

assistive technology and entertainment purposes such as developing improved BCI games

etc.

Neurosky has developed a sensor, noninvasive bio dry reading of electrical activity in the

brain to determine states of relaxation. NeuroSky is a low cost easy to use Encephalogram

(EEC) developed for leisure. Capture neuronal activity with three dry electrodes placed

below the ears, forehead and decoded by algorithms that apply. NeuroSky provides user

information on Delta, Theta, Alpha, Beta and power levels of gamma brain waves band.

NeuroSky detects attention, meditation and eye blinking levels based directly on the brain

activity of the user, and outputs a number per second on a numerical scale every emotion

captured. Using these figures, users can be grouped in different care, meditation and eye

blink categories and looked at the possibility that the timestamp precise moments when the

user makes a mistake.

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1.2 Research Problem to be addressedBCI serious games measure brainwaves using BCI functions provided by a diverse range of

third parties, and game developers may spend a lot of time supporting diverse BCI devices.

Thus, various devices should be controlled by a unified interface to reduce development time.

When considering the development of Brain Computer Interface serious games following

issues should be taken into consideration. First, the necessary awareness of characteristics of

brainwaves and brain function should be minimized, as this can be a considerable burden for

development. It is difficult for game developers to effectively develop BCI entertainment

serious games to its users. Therefore, a number of projects that cannot be started due to lack

of qualified experts or due to cost issues. To minimize the knowledge required by the game

developers, expert knowledge must be described in such a way that the entertainment game

developers can understand and apply to BCI serious games easily.

It is very difficult to use brain waves to control BCI serious games, as each user will have a

different level of brain wave emission. For example, some users brainwaves have measured

amplitude is larger than the other. Therefore, it requires a process that normalizes individual

characteristics, and then transfers the brain waves of the signal for the BCI serious game.

The development process requires systematic BCI serious game experts and game developers

dealing with the functions of the brain and brain waves. This will allow different developers

to quickly and easily produce games together.

Existing research on the development of BCI applications has been generally approaches to

extract features of brain waves, instead of the functions necessary for the development of the

game. Some researchers have integrated 3D engine for developing 3D games. However, these

studies have not provided a solution to the following requirements for BCI various serious

game development.

It is difficult for game developers to apply brainwave entertainment to games because usually

do not have enough knowledge of the characteristics of brainwaves and brain functions.


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Consequently, the development process related BCI must be separated from BCI

development of serious games and managed by experts in the field of brain waves.

Existing frameworks (with the exception of Open-ViBE) usually are not compatible with

economic BCI devices suitable for BCI serious games. In general, the devices used for BCI

BCI applications are expensive multi-channel accurately analyze a user's brain waves.

However, BCI serious games can use low-cost devices BCI to allow more users to access

these devices include EPOC Emotiv and NeuroSky Mindset, but its accuracy is relatively low

compared to more expensive devices. In some cases, a number of functions cannot be used

because the devices used in BCI serious games are different from those used in BCI

applications.

The above researches have not provided a transform function to allow the measured

brainwaves to be used as the game control signals

Therefore, in the proposed project, is supposed to implement a framework that is suited for

the use of all the needs of developers. Although the requirements are met in order to

overcome past conflicts by developers, the application of the framework is a much more

complex when considering the procedure has to be followed. Also the use of the head

assembly provides mind wave signals generated from the user's brain and provides the

resulting signals as level classified and extracted. Therefore, the application of the framework

has been changed from the device used by the team is able to deal with signals extracted and

classified as well as the strength to open and close his eyes.

Then the problem to be solved is how to use properly signals in order to reach applications,

including games and assistive technology. Through the device that indicates the row data for

care, meditation level user to open and close his eyes. Next, you should check with many

users comparing the results to see if it is suitable to develop advanced applications.

Many developers use BCI devices for their development purposes. But the problem is if you

are capable enough to meet your requirements or not. Until the user to carry the device and

use it, they cannot predict whether that device is best suited for your development purposes.


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1.3 Research Questions

How are brain waves captured?

What is the age range and duration of brains waves taken from a person?

How are brain waves collected accurately without any error occurred?

How is the accuracy of collected brain waves tested?

How is BCI Device used in suitable Application?

How BCI application is develop to suit anyone at different age ranges and gender?

How is BCI device utilize efficiently?


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2 CONTENT2.1 Addressing the Literature

In what research has been done so far, the field information technology & BCI technologyhas develop a wealth of computer technology to support the various aspect of BCI

technology, software applications and Hardware applications. Primarily there are two

categories of BCI systems invasive and noninvasive. Invasive systems interact with the

brain directly via electrodes / sensors that are implanted into the brain or its surface. While

noninvasive systems interact with the brain indirectly via electrodes / sensors placed on the

surface of the head that detect brain signal emissions (e.g. Electro-Encephalography (EEG),

functional Magnetic Resonance Imaging (fMRI), and Magnetic Sensor Systems).

Researchers, psychologists, artists, and others have been experimenting with non-invasive

brain-computer interfaces that read brain signals with an electroencephalogram (EEG). EEG

based brain computer interfaces use sensors placed on the head to detect brainwaves and feed

them into a computer as input.

The three major Technologies used in BCIs.

BCIs are categorized according to the users mental activity that is performed to send

commands and messages. There are three main types of mental activities.

- Motor Imagery

- P300

- Steady State Visual Evoked Potential (SSVEP)

Motor Imagery

In Motor Imagery, an individual rehearses or simulates a given action mentally.

An example for the Motor Imagery - A person imagines performing an action, like squeezing

a ball. The EEG data are classified online and the result is graphically presented to the

subject as a horizontal bar on the screen that moves according to the hand movement of the


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subject. The bar goes to the right if the right hand was moved or to the left if the left hand

was moved. To optimize the feature, the offline analysis of the data can be supported

P300

The P300 (P3) wave is a measured brain response that is evoked in the process of decision

making.

When recorded by electroencephalography (EEG), it is shown as a latency (a delay between

stimulus and response).

The signal is normally measured most strongly by the electrodes covering the parietal lobe

area of the head.

Steady State Visually Evoked Potentials (SSVEP)

In neurology, Steady State Visually Evoked Potentials (SSVEP) are the signals that are

responses made by brain to visual stimulation at specific frequencies.

As an example when a person gazes at a light or focuses his/hers attention it, the EEG activity

over Occipital Lobe area of the brain will show an increase in power at the corresponding

frequency.


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Comparison of consumer Brain Computer

Figure 1


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2.2 Methodology2.2.1 OverviewThe brain computer interface technology, not only as a technical aid can be used to bring the

technology to a new level by using the concept of a way to entertain users. As can be used to

develop games and allow users to play the game using their attention and meditation levels or

eyes blink without being restricted to just mouse click. The proposed method previously tried

to transfer some knowledge of the game and BCI communities shared a preliminary

framework to be aware of the investigation of each. Since the team has used the wave head

NeuroSky mind and according to the results found in the testing phase, it could be noted that

the device is not long enough to be able to develop an early implementation. Therefore, the

team decided to implement applications based on assistive technology and entertainment

purpose as the development of games based on the concept of BCI and satisfied with the

device's capabilities.

The overall system objectives are common to all members and we are forced to merge our

individual components at the end to form the final system as a single module. The following

are the main expected outcomes of the research, considering the project as a module. Since

the team has intended to implement a framework that can bridge the gap between the gaming

community and BCI technology were expected results,

A BCI framework that can work on many kinds of BCI devices without any

incompatibility issues

A BCI framework that can be used by developers to make applications

A more accurate and flexible brain wave Feature Extraction technology comparing to

existing BCI Framework

A Game that can be controlled by mind for our demonstration purposes

But since the proposed framework has been changed based on limitations of the device and

conflicts of the developing procedure the team has developed applications as BCI enhanced

Simple Key Board, Keyboard, Snake and Ladders game which are working using the users

eye blink and the Ludo game and a sound generator based on the users attention and the

focus level.


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In the testing phase of the calculator and the key board it was found that eye blink strength

varies from person to person. Age gender also remarkable factor of the different of eye blink

strength. So the software had to be develop to adjust itself to suit different people According

to their eye blink strength. After testing different people eye blink strength average (mean) of

their strength had to be calculated and using the application.

In the development application the comfort of the eye also much consider because of that

time gap between two eye blink was carefully considered after analyzing previous gather

data. The key board and Simple key Board control by thread. This thread decided the timing

between two eye blink. The user should have enough training to use this application properly.

A Train user can easily operate and save time.

This Simple Key Board and Key Board operate only using eye blink signal. So the functions

of this applications are limited.

2.2.2 Overview of the System Design

Figure 2


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2.2.3 User CharacteristicsThe users of the system can be categorized under two user groups as follows

Normal user

Disabled user

The characteristics of those identified user groups are as follow

Normal user - Physical fit person

Both Ludo game and Snake & Ladders games are targeted to this use group. Neurosky BCI is

used to get the focus level and eye blink strength of the users. This games are meant to get

new experience and leisure time activities and it also can be used to improve their attention

and focus level.

Disabled user who have no limbs and unable to speak

Both Mind Simple Key Board and Advanced Blinking Key Board targeted to this user group.

Neurosky BCI is used to get only eye blink strength of the users. User can fully control

calculator & Key Board using Neurosky BCI so they can use this application solve

mathematical equation & communicate with other people without any barriers.


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2.2.4 Product functionsThinkGear API

This API is the bridge between the NeuroSky BCI device and the developed

applications. It provides the functions to deal with the row data collected from the users based

on the attention, meditation level and the eye blink strength

BCI enhanced Advanced Blink Keyboard

This application is a keyboard that makes it easy for disable users to control and use the

keyboard to the device based on the blinking eyes instead of using hand. There are some

functions that gives users press the corresponding key board button using only the blinking

eyes with his hand and automatic search function will reduce the time taken to type a word.

BCI enhanced Simple Blink Key Board

This application also is same as the above mentioned keyboard. It also provides the same

functionality to the users with symbols which are represent the day today activities for easy

usage of the users as it allows users to control the options using the eye blink. For calculating

purposes user have to train his/her way of blinking in order to get the correct options.

BCI enhanced Ludo Game

This implementation of the game is for the entertainment of users that provide the

opportunity to play the game with the attention and the focus level. Depending on the user-

level approach is to roll the dice and win the game. Therefore, providing users a great

opportunity to train their level of attention and the focus level, and to keep them at a good

level.


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BCI enhanced Snake and Ladders Game

This implementation of the game is for the entertainment of users that provide the

opportunity to play the game with his blinking care use and the level of focus. According to

the user to open and close your eyes have to roll the dice and win the game. Therefore,

providing users a great opportunity to play the game in a new way, apart from the traditional

way.

2.2.5 Tools and Technologies

The latest technologies deployed to develop this application the following

Neurosky mindwave BCI Device

Microsoft Visual Studio 2010

.Net Framework 3.5

Neurosky mindwave is used take meditation, attention & eye blinking brain signals

separately from the user.

.Net Framework needs to operate ThinkGearNET API properly. ThinkGearNET API is a C

sharp application. This application classify raw data signal in to meditation, attention & eye

blinking. Efficiency of this application is little bit slowly because it has been written in C

Sharp Programming Language.

C sharp programming language is used to develop Ludo game, Snake and Ladders game,

Mind Controlling Calculator and Mind Controlling Key Board


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2.2.6 Product ConstraintsNeurosky mindwave detected only limited range of signals because it has only one dry

electrode (sensor)

The output of Neurosky mindwave is not much accurate and its varies from person to person

without any combination.

Neurosky mindwave API is written in C Sharp programming language so the efficiency of

code is not up to the required level and its takes considerable time to process the data of

brain signals.

Sometime BCI device driver conflict with windows default driver if it happen so BCI Driver

should to be manually installed.

Application are little bit slow due to the capabilities of BCI device and its ThinkGearNET

API

Our development environment is Microsoft visual Studio 2010. C Sharp Programming

Language is used to develop Mind controlled Games, Mind controlled Key Board and Mind

Controlling Calculator.

Developers may not be always capable of providing an extreme user friendly Control

functions since that may affect the efficiency of the BCI Device.

This BCI Application Framework only support Windows base platforms


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2.2.7 Assumptions and DependenciesIt assumed that user should have Neurosky mindwave BCI devise and the computer which

runs BCI Application Framework on the windows XP or higher version of windows

operating system.

The user must have Neurosky mindwave BCI with a fresh battery and device must be turn on.

Then should be connected to ThinkGearNET API. In order to run BCI Application

Framework successfully, the environment should be satisfied below mentioned conditions.

Microsoft Windows based supported architecture should be available and implemented

x86 x64 USB 2.0 or higher version port should be available Windows XP service pack 2 or higher version .Net Framework 3.5 or higher version available.

Neurosky mindwave drivers should be installed in the computer

Neurosky mindwave Bluetooth dongle should be connected to the computer

Above mentioned hardware and software requirements should be satisfied and integrated

within computer system to perform BCI Application Framework.


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2.3 Research FindingsSince the proposed framework has been changed by the implementation owing to some

conflicts the team was decided to develop applications which are compatible with the device.

In the framework the proposed functions are to be developed has been already facilitate by

the device. Therefore the signal classification is already done by the device and it generates

the outputs and gives the signals as alpha, beta and gamma ranges. So being struggle with

implementing the framework the team decided to implement the applications which are

simply compatible with the BCI mindwave headset.

In the next step the biggest problem was for the team is whether the given values of the

device as output is reliable or is to the point of accuracy or not. Therefore the team conductedmany tastings using many various users (at the initial stage the students of the SLIIT

including the team members). For the each and every user we have given the same time of

period as the testing time and first we collected the raw data which are generating by the

users brain according to the given behavior. By giving a paragraph of a book which is not

read by the users previously we have counted the attention level of the each and every user.

Then according to the raw data counted the mean value of the data for and each and every

user and generated the graphs. When comparing the final results the fact could be understand

is the variation of the data is not in a considerable level as the attention level of some users

are in a high level of value and some are in low level.

When it starts from a high level of value then it spreads up and down in a range and it became

for an average level. But the values are not stable and could not find any certain pattern

which can be generic for all users. If the users lose their focus level owing to any kind of

disturbance then the kept level of the attention level rapidly changed for a low value and we

could notice a wide difference between two values. Therefore the achieved values cannot be

guaranteed whether they would be usable for an advance application development.

Next aim was to collect the raw data regarding the attention level using background music.

For that purpose even we followed the same method as mentioned earlier. We played

background music for a certain time of period and let users to listen for the playing music and

collected the data. Finally when analyzing the results the attention level of some users was in

a considerably good level and some users were the worst. Also one point we could notice is


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the meditation level of the users when listening to the music were at a good level of value and

spread to a certain range of value.

In that experiment even the team has to decide that the given values by the device are not

much reliable and in an accurate level as depending on the way of responses by the users for

an activity and also the device is not much compatible in giving wide range of brain signal

values since it has only one sensor which can be capture only from the users forehead.

When considering about the users desires on playing games also the team has collected the

data regarding the attention and the focus level. In that situation even some of the users

performed well and responded to the experiment. But some users who are novel for playing

games were not highly responsive for the brain activity.

Another function of the device is generates signal regarding the eye blink of the users. In that

situation even the strength of the blinking speed is vary from person to person. Therefore

when testing that value even w could realize that the generating values are changing time to

time and we have to define an average value for the blink when using it for controlling an

application as a game. Because when users get tired the strength and the speed of the blinking

can be degraded to a low level. Therefore relying on the eye blink even cannot go for

developing an advance application as well as the capabilities of the device.

Therefore when conducting the research the team could realize that the currently using BCI

mindwave headset is not much reliable in given signal values which can be usable in

implementing advance applications. The capabilities of the device as it does not contain many

sensors which can be absorbable in brain signals by many areas of the head restricted the

developers in developing advance applications. As a major fact by using this device the

developers cannot implement fully functional advance games or any other application.


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Figure 3

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118

127

136

145

154

163

172

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190

199

208

217

226

235

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271

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307

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325

Attention Level Values


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Figure 7

Figure 8

0

10

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110

19

28

37

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136

145

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163

172

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190

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226

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Running Average of Attention Level Values

0

5

10

15

20

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1 917

25

33

41

49

57

65

73

81

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113

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169

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185

193

201

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265

273

281

289

Variance Between Attention Level Values


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Figure 9

0

50

100

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1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65

Eye Blink Strength


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3 RESULT AND DISCUSSION

Figure 10

Main interfaces of the system

This interface contain two options

Simple Mode Blink advanced mode

Using this interface user can select Simple Blink Key Board and the Advanced Blink Key

Board

Two button of the main interface highlight one after the other then the user can select the

relevant button by blinking his eyes when the relevant button is highlighted. The main

fracture of this applications are can be used by any person who have different level of eye

blink strength without any hesitation.


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Interface of Simple Blink Keyboard

This application has been design for disabled users to communicate very easily without

bothering English language and the users with symbols which are represent the day today

activities for easy usage of the users as it allows users to control the options using the eye

blink. The NeuroSky device detect the brain signal of eye blink. These eye blink is used to

control button of the Simple Blink Keyboard.

First user has to select the relevant row by blinking user eye when its highlighted. (Wen the

Simple Blink Keyboard is open button row of it are automatically highlighted from bottom to

top)

After that the button of the selected row highlighted from the left right

Blinking eyes user has to select the correct button when it is highlighted.

Figure 11


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As explain above disabled use can use the Simple Blink Keyboard by selecting rows from left

Eg :- l2- First user has to select relevant row of buttons by blinking users eye

Figure 12


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Then user select relevant button of the selected row by blinking users eye

Figure 13


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Then user select relevant button of the selected row by blinking users eye. After selecting the

particular symbol it will pronounce the idea relevant to for the symbol.

Figure 14


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Figure 15

Interface of Advance Blink Key Board

This application has been design for disabled users to communicate with the world without

any communication barriers. The Neurosky device detect the brain signal of eye blink. These

eye blink is used to control button of the Blink Key Board.

First user has to select the relevant row by blinking user eye when its highlighted. (Wen the

Key Board is open button row of it are automatically highlighted from bottom to top)

After that the button of the selected row highlighted from the left right

Blinking eyes user has to select the correct button when it is highlighted.

After typing all the word of the text SAY IT button should be selected then what you have

type is pronounced.


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Figure 16

First type the text that are to be pronounced


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Figure 17

After selecting the relevant button it will automatically search for the matching word

beginning with the sleeted letter


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Then select SAY IT button and it will pronounce the text.

Figure 18


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4 CONCLUSIONFor a long time, researchers have been working on a marriage of human and machine that

sounds like something out of science fiction: a brain computer interface. The technologyholds great promise for people who cant use their arms or hands normally because they have

had spinal cord injuries or suffer from conditions such as amyotrophic lateral sclerosis (ALS)

or cerebral palsy. BCI could help them control computers, wheelchairs, televisions, or other

devices with brain activity.

To success with the projects like above mentioned, the capabilities of the used BCI devices

should be in a high standard level with the fully functional options. Also there should be

many sensors which are capable of capturing brain signal within vast areas of the brain.

Since we are using the NeuroSky mindwave head set which is contain only one sensor is not

much capable of developing advance systems and applications. And the generated raw data

also not much accurate and reliable as it can be used for a considerable application since it

does not gives a stable value and cannot find a certain pattern in order to use as an average

value for controlling an application

Therefore the team decided to implement applications depending on the capabilities of the

using BCI mindwave headset. So the implemented applications are Mind controlling

Calculator and a Keyboard which is working based on the users eye blink. Also a Ludo Game

controlling based on the users attention level and the focus level as well as a Snakes and

Ladders game based on the eye blink. The sound generator is an application working based

on the alpha, beta and gamma brain signals.


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