This document discusses brain-computer interfaces (BCI). It defines BCI and describes the different types - invasive, non-invasive, and semi-invasive. It explains the implementation process for BCI, including signal acquisition using EEG, feature extraction, translation to device commands, and feedback. Examples of BCI applications in India are provided. The global BCI market and conclusions are also briefly mentioned.

1. BRAIN COMPUTER
INTERFACE
BY:
PRIYANSHI PANDEY
B.Tech (I.T) 5th Sem.
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2.  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
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3. • 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.
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4. BCI TYPES
NON SEMI
INVASIVE
INVASIVE INVASIVE
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5.  Invasive BCIs are implanted
directly into the grey matter of
the brain during neurosurgery. Invasive BCI
 As they rest in the grey matter,implant
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.
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6. • Easy to wear.
• Do not give rise to any Electrodes placed
scar tissue formation. on scalp
• Produce poor signal
resolution.
• The skull dampens the
brain waves or signals,
deflecting and blurring
them.
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7. Semi -invasive BCI devices are Semi-invasive BCI imp
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. 7

8.  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.
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9.  Implementation of BCI involves six stages:
1)User Training
2)Signal Acquisition
3)Digitization of signals
4)Feature Extraction
5)Signal Translation
6)Feedback Signal Processing
Digitization
Feature Extraction Translation algo
Signal Acquisition
Feedback
Device Command
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10.  The user is trained by instructing
them to perform specific cognitive
tasks.
 The mental tasks to be performed
can be: 14+69=?
- 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. fig: BCI user
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11.  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 fig: Signal
device. acquisition
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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
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13.  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. fig: Conductive
 The electrodes used are either gold paste
or silver.
 Each electrode has a small amount
of conductive paste applied to it ,
which is then placed underneath a
cap .
fig: EEG cap
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14.  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.
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15.  Mu and Beta rhythms
 Visual evoked potentials
 P300 evoked potentials
 EEG signal differences during
different mental calculations
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16.  The signals acquired are in analog
form. Analog Signals
 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 Signals
digital form using analog to digital
converters.
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17.  Digitized signals are
subjected to a variety of Digitized signals
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 Extracted Signal
frequency domain(e.g. mu or Features
beta rhythm amplitudes)
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18.  The translation algorithm
Signal Features
translates these signal
features into device
commands or orders that
carry out the user’s intent.
 Effective algorithms adapt to
user on 3 levels:
Device
-First level of adaptation Commands
-Second level of adaptation
-Third level of adaptation
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19.  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
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20. 20

21. CLASSIFICATION OF 5 MENTAL
TASKS
Tasks Classification
Movement Imagery 10000
Trivial 01000
Multiplication
Geometric Figure 00100
Rotation
Nontrivial 00010
Multiplication
Relax 00001
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22. Path a TM/ MI/ MI/ MI/ R/
Forward Right Right Right Stop
Path b TM/ MI/ MI/ GFR/ R/
Forward Right Right Left Stop
B
A
start
start goal
goal
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23. Random buttons flashing at periodic time intervals
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24.  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 Prof. Neeraj
NBRC.[1] Jain
 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]
Mr. Suresh 24

25. Brainfingers Mindwave EPOC
Brainfingers hardware and It safely measures It uses a set of
software allow you to brainwave signals and sensors to tune into
control your computer monitors the attention electric signals
totally hands-free. levels. produced by the brain.
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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.
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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
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