The seminar discusses a technology that allows physically disabled individuals to control electronic devices using brainwaves, facilitated by an EEG headset and a brain-computer interface (BCI). It details the methodology of detecting brain activity, processing signals, and implementing control commands to operate devices like motors or bionic limbs. The presentation concludes with applications, advantages, and disadvantages of the technology, highlighting its potential to improve the quality of life for users.

1. A seminar on
“Controlling electronic devices using brainwaves”
SUPERVISED BY:
Ms B. Gowthami ,M-Tech.,
Assistant Professor
Dept. of ECE.
PRESENTED BY:
S.Lakshmi Teja
15121A04K4
IV- B-Tech
ECE-C Section
Department of Electronics and Communication Engineering

2. CONTROLLING ELECTRONIC DEVICES USING
BRAIN WAVES

3. CONTENTS
• Objective
• Introduction
• Methodology
• Requirements
• Block diagram
• Functional flow
• Applications
• Advantages
• Disadvantages
• Conclusion
• References

4. OBJECTIVE
Enabling physically disabled people to communicate and control devices
with their thought commands.

5. INTRODUCTION
• Brain is made up of billions of brain cells called neurons, which use electricity to
communicate with each other. The combination of millions of neurons sending
signals at once produces an enormous amount of electrical activity in the brain,
which can be detected using sensitive medical equipment (such as an EEG),
measuring electricity levels over areas of the scalp.
• The combination of electrical activity of the brain is commonly called a Brain
Wave pattern, because of its cyclic, "wave-like" nature.

7. METHODOLOGY

8. METHODOLOGY
• The brain activity of the user is detected by electroencephalogram (EEG) headset.
• The headset has a single electrode with a ground and reference, the electrode situated
in the frontal position of the user’s scalp. This means that there are two metallic things
touching the head.
• The reference electrode goes on the left side of the fore head, measuring electrode to
the scalp, the ground clip is attached to the ear.
• The measuring electrode receives physiological signals along with noise, at the
forehead bone the reference electrode receives only noise.
• The differential amplifier present at the front end of the electrodes differentiates the
brainwaves from noise.
• The corresponding values are recorded by the electrode by detecting the electrical
activity of the brain at a rate of hundreds of samples per second.

9. METHODOLOGY
• Lab view software is used to examine this signal.
• Later by applying signal conditioning procedures different brain waves like alpha, beta,
gamma, theta and delta are acquired are analyzed by Lab view or MATLAB
application.
• Depending upon the attention, an appropriate algorithm(Fuzzy Logic) is applied for
distinguishing the commands and creates relating data signal.
• Signal shifting is done using Max 232 IC to interface with microcontroller.
• The controller recognizes these commands creates relating control signals, and sends it
to motor or any other circuitry.

10. REQUIREMENTS

11. REQUIREMENTS
HARDWARE:
• BCI
• MAX 232
• PIC MICROCONTROLLER
• ENCODER
• RF TRANSMITTER
• RF RECEIVER
• DECODER
• CURRENT BUFFER
• MOTOR DRIVER
SOFTWARE:
• MATLAB OR LAB VIEW APPLICATION
• ARDUINO

12. BLOCK DIAGRAM

13. FUNCTIONAL FLOW
• The Brain machine interface fetches the different brain signals that are responsible for the commands and
attention level of a person wearing the device.
• The signals that are obtained from BMI are processed with the help of Lab View, an appropriate
algorithm(Fuzzy Logic) is applied for distinguishing the commands and creates relating data signal
• From Lab View these data are converted into serial data and are given to the IC MAX232.
• This IC converts the serial data of +15V to -15V to 0V to 5V and this serial data is given to
microcontroller.
• This microcontroller gives the data to the encoder in a controlled manner for modulation. The encoder
encodes the data and performs amplitude modulation.
• This modulated data is given to the RF transmitter for transmitting. The RF receiver that lies within the
range. It can receive the modulated data and give this data to the decoder

14. FUNCTIONAL FLOW
• The decoder decodes the data.
• The current of the signal produced by these data is very low which cannot be
detected by the microcontroller. In order to avoid this, current buffer which
regulates the current and produce a standard 5V output is further given to the
microcontroller for processing.
• Based on the data, the program gives instruction for the movement of the motors.
• The output of the microcontroller is 5V which is insufficient to run a motor
effectively. This problem is rectified by using a motor driver.
• This motor driver amplifies the 5V signal to 12V signal. This 12V signals are given
to relay circuits.
• Each motor requires two relays which work in the format of logic gate. The output
of the relay is given to the motors and the motors runs according to the command
from the relay.

15. APPLICATIONS
• "Bionic" Limbs
• Drive a Wheelchair—And a Car
• Screen Mobile Phone Calls
• Control Mobile Games With Brain Waves

17. ADVANTAGES
• It is also used to relax the mind
• BCI’s will help creating a direct communication pathway between a human or animal brain and any
external devices like computers
• Better living , More features ,More advancements in technologies etc.

18. DISADVANTAGES
• Very expensive
• Complexity of brain
• Research is still in the beginning stage

19. CONCLUSION
This technology is sort of making disabled people physically courageous and
mentally strong enough to face and make their beautiful life even more
beautiful with their reborn artificial physical strength.

20. REFERENCES
[1] Christian I. Penaloza, Yasushi Mae, Francisco F. Cuellar, Masaru Kojima, Tatsuo Arai, "Brain
Machine Interface System Automation Considering User Preferences and Error Perception
Feedback", IEEE Transactions On Automation Science and Engineering, vol. 11, no. 4, October
2014.
[2]https://www.wikipedia.org
[3] http://www.brain-waves-technology.com/
[4] https://ieeexplore.ieee.org/Xplore/home.jsp
[5] https://github.com/MexsonFernandes/NeuroskyMindwaveMobile2

21. THANK YOU