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CHAPTER-1
INTRODUCTION
1.1GENERAL
There are more than 9.5 million paralyzed people in India. Most of them constantly
rely on their family members or caretakers to move to different places.
This brain controlled robot is based on Brain–computer interfaces (BCI). BCIs are
systems that canbypass conventional channels of communication (i.e., muscles and
thoughts) to provide direct communication and control between the human brain and
physical devices by translating different patterns of brain activity into commands in
real time.
With thesecommands a robot can be controlled. The intention of the project work is
to develop a robot that can assist the disabled people in their daily life to do some
work independent on others.
1.2AIMANDOBJECTIVEOF PROJECT.
Millions of people around the world suffer from mobility impairments and hundreds
of thousands of them rely upon powered wheelchairs to get on with their activities of
daily living.
However, many patients are not prescribed powered wheelchairs at all, either because
they are physically unable to control the chair using a conventional interface, or
because they are deemed incapable of driving safely.
1.3PROBLEMSPECIFICATION
?According to 2011 census, 2.21% of total population in India has disability.
?2.41% of male population isdisabled.
?2.01% of female population is disabled.
?Overall there are 2 crores 68 lakhs persons with disability.

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1.4LITERATUREREVIEWANDPRIORARTSERACH
PATENT:(US7260430B2)Architecture of an embedded internet robot system
controlled by brain waves
?Embedded internet robot system that is controlled by brain waves.
?Brain Computer Interface
?System cooperate with the alertness level detection technology and instruction
translation technology, so the user can control adistal-end robot purely via
consciousness activities.
?Can interact with the environment as if there were an entity representing the
user’s consciousness appearing in the distal end.
PATENT:(US9211078B2)Process and device forbrain computer interface
a)Non-invasively obtaining brain signals.
b)Processing said signals with an electroencephalograph (EEG).
c)Transducing said signals into functional commands by means of feature
extraction from EEG signals.
d)Providing the signals further for application through serial communication over
bluetooth, etc.
PATENT:(US9092055B2)Platform and method for BCI control
?The BCI(Brain Computer Interface) control is utilized tocontrol a plurality of
brain control devices. The brain control devices are capable of executing an
operation.
?A brain-wave control supplying a first signal and a second signal, wherein the
first and second signals are utilized to visually evoke a user’sfirst and second
brain waves, respectively.
?The brain-wave control selects one of the brain control devices as a to-be-
controlled device by the first brain wave, and the to-be-controlled device is
controlled to finish an operation by the second brain wave.
PATENT:(US9962837B2)System and method of controlling robot by brain
electrical signals
?The BCI(Brain Computer Interface) control is utilized tocontrol a plurality of
brain control devices. The brain control devices are capable of executing an
operation.

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?A brain-wave control supplying a first signal and a second signal, wherein the
first and second signals are utilized to visually evoke a user’sfirst and second
brain waves, respectively.
?The brain-wave control selects one of the brain control devices as a to-be-
controlled device by the first brain wave, and the to-be-controlled device is
controlled to finish an operation by the second brain wave.
PATENT:(US9539118B2)Brain-controlled body movement assistance devices
and methods
?Systems including computer programs encoded on a computer storage
medium.
?A device includes a brain-controlled body movement assistance device
with a brain-computer interface (BCI) component adapted to be mounted
to a user.
?Then connected to the BCI component and adapted to be worn by the user.
?The feedback mechanism being configured to output information relating
to a usage session of the brain-controlled body movement assistance
device.
1.5METHODS/TOOLSTOBEUSED
Electroencephalograph(EEG):
•Electroencephalography is an electrophysiological monitoring method to
record electrical activity of the brain.
•EEG measures voltage fluctuations resulting within the neurons of the brain.
•The brain waves fallin the range of 1–20 Hz.
•The waves are subdivided into band widths known as
?Alpha,
?Beta,
?Theta and
?Delta.

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Applicationsof EEG:
•It is used to evaluate several types of brain disorders.
•It is also used to determine the overall electrical activity of the brain to
evaluate trauma, drug intoxication, or during surgical procedures.
•Brain-Computer Interfacing based on EEG was primarily focused on Neuro-
prosthetics applications.
•Increasingly more alternative applications in healthy
human subjects are proposed and investigated.
NeuroSky MindWave:
•The MindWave, safely measures and outputs the EEGpower spectrums (alpha
waves, beta waves, etc), NeuroSky eSense meters (attention and meditation)
and eye blinks.
•The device consists of a headset, an ear-clip, and a sensor arm. The headset’s
reference and ground electrodes are on the ear clip and the EEG electrode is
on the sensor arm, resting on the forehead above the eye (FP1 position).
•It uses a single AAA battery with 8 hours of battery life.
Features:
•Single Sensor on FP1
•Can detect multiple mental states simultaneously

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•Reference electrodeon Ear clip to remove ambient noises
•IP involves noise cancellation and signal amplification
•Provides EMG feature for Eye Blink detection
Specifications:
•Bluetooth TM Wireless communication
•Passive Dry Sensor EEG
•Single AAA battery
•10 Hours Run TimeeSense.
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•Reference electrodeon Ear clip to remove ambient noises
•IP involves noise cancellation and signal amplification
•Provides EMG feature for Eye Blink detection
Specifications:
•Bluetooth TM Wireless communication
•Passive Dry Sensor EEG
•Single AAA battery
•10 Hours Run TimeeSense.
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•Reference electrodeon Ear clip to remove ambient noises
•IP involves noise cancellation and signal amplification
•Provides EMG feature for Eye Blink detection
Specifications:
•Bluetooth TM Wireless communication
•Passive Dry Sensor EEG
•Single AAA battery
•10 Hours Run TimeeSense.

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CHAPTER–2
DESIGN:ANALYSIS,DESIGNMETHODOLOGYAND
IMPLEMENTATIONSTRATEGY
3.1GENERAL
Design Engineering is a subject based on Design Thinking that will change the mind-
set of young engineers to create innovation, entrepreneurship, skill development
culture in India. Design Thinking is Human Centred process with specific steps like
Observation, Empathy, Ideation, Product Development, Prototype and Test with lots
of iterations. All Canvases, framework, tools & techniques are useful to enhance
creativity and innovation in the projects. Design Engineering must be considered as
philosophy rather a subject
3.2AEIOUSUMMARYCANVAS.

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3.3EMPATHYMAPPINGCANVAS.

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3.4IDEATIONCANVAS.
3.5PROUCTDEVELOPMENTCANVAS.

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CHAPTER–3
IMPLEMENTATION
3.1GENERAL
The brain controlled robot basically works on the principle of capturing the brain
wave signals utilizing it for the movement of robot.
Steps:
1. The EEG signals are captured by the MindWave sensor.
2. The signals are sent to microcontroller with the help of Bluetooth through serial
communication.
3. The signals are processed by the microcontroller and according to the signals,
motors are operated.
4. Hence the robot movement takes place.
3.2BLOCKDIAGRAM.
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CHAPTER–3
IMPLEMENTATION
3.1GENERAL
The brain controlled robot basically works on the principle of capturing the brain
wave signals utilizing it for the movement of robot.
Steps:
1. The EEG signals are captured by the MindWave sensor.
2. The signals are sent to microcontroller with the help of Bluetooth through serial
communication.
3. The signals are processed by the microcontroller and according to the signals,
motors are operated.
4. Hence the robot movement takes place.
3.2BLOCKDIAGRAM.
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CHAPTER–3
IMPLEMENTATION
3.1GENERAL
The brain controlled robot basically works on the principle of capturing the brain
wave signals utilizing it for the movement of robot.
Steps:
1. The EEG signals are captured by the MindWave sensor.
2. The signals are sent to microcontroller with the help of Bluetooth through serial
communication.
3. The signals are processed by the microcontroller and according to the signals,
motors are operated.
4. Hence the robot movement takes place.
3.2BLOCKDIAGRAM.

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3.3FLOWCHART.

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CHAPTER–4
CONCLUSION&FUTURESCOPE
4.1CONCLUSION
Brain-Computer Interface (BCI) is a method of communication based on voluntary
neural activity generated by the brain and independent of its normal output pathways
of peripheral nerves and muscles. The neural activity used in BCI is recorded using
noninvasive techniques (Mindwave sensor). The BCI will provide better alternatives
for individuals to interact with their environment in an efficient way. Thus enabling
the control of robotic wheel chair by using EEG.
3.2FUTURESCOPE.
•Voice Recognition can be used.
•Obstacle detection
•Take the images through distal end robot and give it back to person

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REFERENCES
JournalReferences:
?EEG Based Brain Controlled Robot Lavanya Thunuguntla et al Int. Journal of
Engineering Research and Applications ISSN : 2248-9622, Vol. 4, Issue 4( Version
1), April 2014, pp.195-198 Lavanya Thunuguntla1 , R Naveen Venkatesh Mohan2 ,
P Mounika3
?International Journal of Innovative and Emerging Research in Engineering
Volume 3, Issue 3, 2016R.S.Shekhawat1a, Rajat Sharma2band Ravi Rao2ba
Assistant Professor Department of Electrical Engineering, B. K. Birla Institute of
Engineering & Technology, Pilani,IndiabStudent, Electrical, B. K. Birla Institute
of Engineering & Technology, Pilani, India
?Brain Controlled Mobile Robot Using Brain Wave Sensor IOSR Journal ofVLSI
and Signal Processing (IOSR-JVSP) e-ISSN: 2319–4200, p-ISSN No. : 2319–
4197 PP 77-82 V. Rajesh kannan1 , K.O.Joseph 2 1PG Student, Communication
Systems, Department of ECE, G.K.M College of Engineering and Technology,
India. 2Professor, Departmentof ECE, G.K.M College of Engineering and
Technology, India
WebReferences:
•http://www.kscst.iisc.ernet.in/spp/41_series/40S_awarded_&_selected_pro
js_further_devpt/40S_BE_0571.pdf
•http://www.uninettunouniversity.net/allegati/1/CommonFiles/Eventi/it/30/
705/Brain%20Computer%20Interface%20System.pdf
•https://www.youtube.com/watch?v=bz1BF9yEXXI&feature=youtu.be