Brain Computer Interface

BRAIN COMPUTER INTERFACE
FICTION OR FUTURE
6/1/2017 1

GROUP MEMBERS
 SUBHAM KUNDU
 UJWAL ARORA
 SUBHRAM BISWAS
 VIKAS KUMAR
6/1/2017 2

CONTENTS
 INTRODUCTION
 WHAT IS BCI?
 BACKGROUND
 PRINCIPLE OF OPERATION
 TYPES OF BCI
 APPLICATIONS
 CHALLENGES
 PROPOSED SOLUTION
 ADVANTAGES AND
LIMITATIONS.
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INTRODUCTION
 Brain computer interface is a direct communication
pathway between a wired brain and an external device.
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WHAT IS BCI??
 Brain Computer interface (BCI) is a
technology which allows a human to
control a computer , peripheral ,or
other electronic device with thought.
 It does so by using electrodes to detect
electric signals in the brain which are
sent to a computer.
 The computer then translates these
electric signals into data which is used
to control a computer or a device linked
to a computer.
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BACKGROUND
 In 1924 Hans Berger a German
scientist was the first to record
human brain activity by means of
an EEG.
 In 1970 research on BCI began at
the University of California Los
Angeles(UCLA).
 Following years of animal
experimentation , the first
neuroprosthetic devices implanted
in humans appeared in mid 1990s.
 In 2004 Matthew Nagle became the
first human to be implanted with a
BCI.
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PRINCILPLE OF OPERATION
 BCI system consists of four basic components:-
-> Signal acquisition
-> Signal preprocessing
-> Feature extraction
-> Translational Algorithms
Signal
acquisition
Preprocess
ing
Feature
extraction
Translation
BCI
Application

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SIGNAL
ACQUISITION
METHODS
INVASIVE
Electrocortico
graphy(ECOG)
INTRACORTICAL
NON- INVASIVE
EEG MEG fMRI fNIRS
TYPES OF BCI

INVASIVE TECHNIQUES
 INTRACORTICAL :-
->Intracortical acquisition
technique represents the most
invasive method. It is planted
under the cortex surface of the
brain. It can be achieved using
single electrode, or array of
electrodes that measure the
action signals out of individual
neurons.
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 Electrocorticography (ECoG) is a
recording method that brings a less
invasive option while at the same
time preserves the advantages of
invasive approach. It involves
implanting electrode grids or strips
over the cortex surface through a
surgical operation

TECHNICAL BACKGROUND..
(Invasive)
Electrocorti
cographyan
dEpilepsy
Data
Acquisition
Preprocessing
Channel
Selection
DataAnalysis
 The electrode grids were placed on the cortex under the dura mater and
covered the primary motor and premotor area as well as the fronto-temporal
region either of the right or left hemisphere. The grid-sizes ranged from 20
to 64 electrodes.
 High pass filters with a cut-off frequency of usually less than 0.5 Hz are
used to remove the disturbing very low frequency components such as those
of breathing. On the other hand, high-frequency noise is mitigated by using
low pass filters with a cut-off frequency of approximately 40–70 Hz.
 ECoG offers a temporal resolution of approximately 5 ms and a spatial
resolution of 1 cm. Using depth electrodes, the local field potential gives a
measure of a neural population in a sphere with a radius of 0.5–3 mm around
the tip of the electrode. With a sufficiently high sampling rate (more than
about 10 kHz), depth electrodes can also measure action potentials.

NON INVASIVE TECHNIQUES
 FUNCTIONAL MAGNETIC
RESONANCE IMAGING (FMRI):-
->FMRI detects the
changes in blood flow which
are related to neural activity
in the brain using the device
shown in figure.
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 Functional near-infrared
spectroscopy (FNIRS):-
->FNIRS is a noninvasive technique
that measures blood dynamic in the
brain in order to detect the neuronal
activity. It uses light in the near-
infrared range to determine the
blood flow .

NON INVASIVE TECHNIQUES
 MAGNETOENCEPHALOGRAP
HY (MEG):-
->It is a non-invasive method
that measures magnetic fields
produced by electrical currents
occurring naturally in the brain.
6/1/2017 13
Electroencephalogram
(EEG):-
->Electroencephalography (EEG)
is the recording of electrical
activity along the scalp through
measuring voltage fluctuations
accompanying neurotransmission
activity within the brain.

TECHNICAL BACKGROUND
(NON-INVASIVE)
 MEG:-The magnetic signal outside of the
head is acquired using the
superconducting quantum interference
device (SQUID).
 EEG:-
->The amplified signal is digitized via
an analog-to-digital converter after
being passed through an anti-aliasing
filter.
-> Analog-to-digital sampling typically
occurs at 256–512 Hz in clinical scalp
EEG; sampling rates of up to 20 kHz are
used in some research applications.

BCI APPLICATIONS
 Bioengineering
 Medicinal
 Games & Entertainment
 Security & authentication
 Robotics
 Military & Civil search
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BCI IN MEDICINE
 It acquires brain signals and
translate them to carry out the
desired actions.
 Goal is to replace or restore
functions of disabled people.
 It is also helpful for
rehabilitation after stroke and
for disorders.
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BCI IN GAMING
 BCI in Gaming provide additional
channel of control in games
 It is being employed for emotional
control and nueroprosthetic
rehabilitation and also for dropping
the stress levels.
 Top 4 games which involve BCI are
Invaders Reloaded, Dagaz, Flappy
Mind, Blink Shot.
6/1/2017 17

BCI IN ROBOTICS
 BCI has been widely used in robotics.
 It is used to control robot arms or any
robot with the help of non invasive
technique.
 It eases the work but the thinking
should be correctly done in order to
move the arm successfully.
6/1/2017 18

BCI IN MILITARY & CIVIL
SERVICES
 BCI is done with the help of EEG-based
helmets and headwear.
 It monitors the attention in long distance
aircraft pilots
 It also sends out alert and warning for aircraft
pilots
 Example of BCI in military projects is
DARPA(The US Defense Advanced Research
Projects Agency).
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Other Applications…
 “Google search” through brain.
 Controls robots that function in
dangerous situations(e.g.:
underwater).
 Provides enhanced control of devices
such as wheelchairs and vehicles.
 Monitor stages of sleep
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Advantages
 BCI has increased the possibility of
treatment of disabilities related to
nervous system.
 It helps creating a Direct
Communication pathway between
human and computers.
 Techniques like EEG,MEG have come
into discussion.
 Provided a new work area for scientist
and researchers.
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Limitation
 Difficulty in adaption and
learning
 Very expensive
 Lack of sensor modality
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CHALLENGES
 Training Process:-Training the user is a time consuming
activity.
 Information Transfer Rate
 Non-Linearity
 Non-stationarity
 Noise

PROPOSED SOLUTIONS
 Compared to imagery BCI, selective attention
strategies achieve higher ITR.
 EEG signals can be better characterized by nonlinear
dynamic methods than linear methods.
 Noise removal:-
 ->Preprocessing in spatial, time or frequency
domains enhances the signal and reduces noise caused
especially by external factors. Improving the signal to
noise ration (SNR) of EEG signals is done by increasing
the signal level and/or decreasing the noise level.

Conclusion
 We can say as detection techniques improve, the BCI
will improve as well and would provide greater
alternatives for individuals to interact with the
machine.
 The electrocardiogram is still considered to be the "gold
standard" for defining epileptogenic zones; however,
this procedure is risky and highly invasive
 Recently, independent component analysis (ICA)
techniques have been used to correct or remove EEG
contaminants. These techniques attempt to "unmix" the
EEG signals into some number of underlying components
 Artifact Correction(Beginning Of An New Era Of
ARTIFICAL Intelligence.
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REFERENCE
 Youtube.com
 Wikipedia.com
 Linkedin.com
 Sciencedirect.com
6/1/2017 26

ThankYoufor
listening…..
6/1/2017 27

Brain Computer Interface

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