Seminar

BRAIN COMPUTER

INTERFACE

BY:

PRIYANSHI PANDEY

B.Tech (I.T) 5th Sem.

1

What is BCI?

BCI approaches

Implementation of BCI

BCI based real time control of wheelchair

using EEG

BCI in India

BCI in the global market

Conclusion

References

2

• Brain-computer interface (BCI) is a fast-growing emergent technology, in which researchers aim to build a direct channel between the human brain and the computer.

• A Brain Computer Interface (BCI) is a collaboration in which a brain accepts and controls a mechanical device as a natural part of its representation of the body.

• Computer-brain interfaces are designed to operate external devices.

3

4

BCI TYPES

INVASIVENON

INVASIVE

SEMI

INVASIVE

Invasive BCIs are implanted directly into the grey matter of the brain during neurosurgery.

As they rest in the grey matter, invasive devices produce the highest quality signals among

BCI devices.

They are prone to scar- tissue build-up, causing the signal to become weaker.

Even lost as the body reacts to a foreign object in the brain.

5

Invasive BCI

implant

• Easy to wear.

• Do not give rise to any

scar tissue formation.

• Produce poor signal

resolution.

• The skull dampens the

brain waves or signals,

deflecting and blurring

them.

6

Electrodes placed

on scalp

7

Semi -invasive BCI devices are

implanted inside the skull but rest

outside the brain.

They produce signals with better

resolution than those produced in

non-invasive BCI.

As compared to invasive technique

they have lower risk of scar tissue

formation.

Electrodes are embedded in a thin

plastic pad that is placed above the

cortex beneath the Dura mater.

Semi-invasive BCI implant

Over the years invasive technique has been

implemented in the form of BCI device implanted in

the brain of humans and animals.

But the risk of scar tissue formation is always there.

Besides the idea of implanting a device inside a

normal brain is itself disturbing.

Over the years there has been a shift in focus from

invasive techniques to non-invasive techniques.

With improvement in signal processing systems

non-invasive techniques give better result.

Nowadays most research work is in the field of non-

invasive BCI implementation.

8

Implementation of BCI involves six stages: 1)User Training2)Signal Acquisition3)Digitization of signals4)Feature Extraction5)Signal Translation6)Feedback

9

Signal AcquisitionDigitization

Feature Extraction Translation algo

Signal Processing

Device CommandFeedback

The user is trained by instructing them to perform specific cognitive tasks.

The mental tasks to be performed can be:- imaginary motor movements- non-trivial mental arithmetic- visualizing rotation of 3D object- trivial mental arithmetic

The signals produced during these tasks are recorded and the user is trained to focus on performing a specific task to produce required signal.

10

fig: BCI user

14+69=?

The most important element in a bci model is signal acquisition.

Different thought processes give rise to different types of signals in the brain.

The purpose of signal acquisition is to acquire these brain signals.

The device used to acquire these signals is called an EEG device.

11

fig: Signal

acquisition

12

•EEG or electroencephalogram is

a record of the oscillations of

brain electric potentials recorded

from 20 to 256 electrodes

attached to the scalp.

•Key role of EEG is signal

amplification.

•The signals received from

electrodes are minute and to

generate a usable signal they

must be amplified.

fig: An EEG Machine

It uses an array of electrodes attached to the subject’s scalp.

User’s scalp is first prepared with an abrasive paste to remove any dead skin and sweat which may interfere with the signal.

The electrodes used are either gold or silver.

Each electrode has a small amount of conductive paste applied to it , which is then placed underneath a cap .

13

fig: Conductive

paste

fig: EEG cap

Alpha waves(8-13Hz):associated with relaxed state of brain.

Beta waves(13-40Hz):associated with alertness , problem solving and concentration.

Theta waves(4-7Hz):associated with sleep but can also be associated with anxiety, epilepsy, traumatic brain injury.

Delta waves(0-4Hz):associated with deep sleep .

Mu waves(7-11Hz):Mu rhythms are associated with motor cortex and can be used to recognize motor movement.

14

Mu and Beta rhythms

Visual evoked potentials

P300 evoked potentials

EEG signal differences during

different mental calculations

15

The signals acquired are in analog

form.

For use in controlling external devices

these signals need to be digitized.

Before digitization, the signals are

amplified and passed through filtering

circuits that filters out signals in the

required frequency range.

The signals are then converted to

digital form using analog to digital

converters.

16

Analog Signals

Digital Signals

Digitized signals are subjected to a variety of extraction processes.

This analysis extracts the signal features that correspond to user’s message.

BCIs can use signal features that are in the time domain(e.g. P300)or the frequency domain(e.g. mu or beta rhythm amplitudes)

17

Digitized signals

Extracted Signal

Features

The translation algorithm

translates these signal

features into device

commands or orders that

carry out the user’s intent.

Effective algorithms adapt to

user on 3 levels:

-First level of adaptation

-Second level of adaptation

-Third level of adaptation

18

Signal Features

Device

Commands

BCI system provides feedback and

interacts in a productive fashion with

the adaptations the brain makes in

response to that feedback.

The feedback can be in the form of:

-movement of robotic arm

-motion of wheelchair

-word processing

-motion of cursor

screen

-neurofeedback

19

20

CLASSIFICATION OF 5 MENTAL

TASKS

Tasks Classification

Movement Imagery 10000

Trivial

Multiplication

01000

Geometric Figure

Rotation

00100

Nontrivial

Multiplication

00010

Relax 00001

21

22

Path a TM/Forward

MI/Right

MI/Right

MI/Right

R/Stop

Path b TM/Forward

MI/Right

MI/Right

GFR/Left

R/Stop

start

goal

start goal

A B

23Random buttons flashing at periodic time intervals

National Brain Research Centre

Professor , Prof. Neeraj Jain has

been doing research on BCI.

A research project on developing

a brain controlled robot, funded

by DRDO has been taken up by

NBRC.[1]

BCI developed by DAIICT

Professor Mr. Suresh Ranjan has

helped an IIM-A alumnus Mr.

Suresh Karat who had been

paralyzed for 13 years.[2]

24

Prof. Neeraj

Jain

Mr. Suresh

Karat

25

Brainfingers

Brainfingers hardware and software allow you to control your computer totally hands-free.

Mindwave

It safely measures

brainwave signals and

monitors the attention

levels.

EPOC

It uses a set of

sensors to tune into

electric signals

produced by the brain.

26

•BCI has opened new avenues for scientific research.

•It has raised new hopes for patients with ALS,

Locked-in Syndrome and other neurodegenerative

diseases.

•In the past invasive techniques have helped patients to

regain their eyesight and have also helped them to

operate robotic arms .

•The current BCI research has shifted towards non-

invasive techniques.

•Various companies are developing neuroheadsets to give

a new channel of monitoring thoughts and making use of

them in new gaming experience.

•Currently BCI systems are still expensive and away from

reach of many patients.

•Continued research in this field will surely solve all such

problems and prove to be a boon for many.

27

[1]http://neurogadget.com/2011/03/23/indian-scientists-working-

on-brain- controlled-robot-to-help-disabled-patients/1438

[2] http://articles.timesofindia.com/2012-04-

07/news/31304725_1_device-iim-1- graduate-daiict

[3]http://www.jisce.org/attachments/File/Vol-1_Issue-

5/E0143081511.pdf

•http://www.aksioma.org/brainloop/bci_dependent.html

•http://computer.howstuffworks.com/brain-computer-interface2.htm

•http://www.nbrc.ac.in/

•http://www.emotiv.com/

•http://store.neurosky.com

•http://mybrainnotes.com/memory-language-brain.html

28

29