2. Contents
• Introduction
• History
• Techniques use
• Recording and measurements
• Variations in EEG
• Advantages and disadvantages
• Challenges
• Future aspects
• References
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3. Introduction
• Electroencephalography(EEG) is a technique to analyse the neural
activities occurring in the brain.
• EEG signal is measure of current flow in dendrites of neurons in
cerebral context
• EEG activity always reflects the summation of the synchronous
activity of thousands or millions of neurons that have similar
spatial orientation
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4. History
• Carlo Matteucci (1811–1868) and Emil Du Bois-Reymond (1818–
1896) were the first people to register the electrical signals
emitted from muscle nerves using a galvanometer and
established the concept of neurophysiology.
• Analysis of EEG signals started during the early days of EEG
measurement. Berger assisted by Dietch (1932) applied Fourier
analysis to EEG sequences
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5. Techniques used in EEG
• Monopolar Technique : Uses one active recording electrode placed
on area of interest, a reference electrode in an inactive area
• Bipolar Technique : Uses two active electrodes on areas of interest,
Measures brain waves (graphs voltage over time) through electrodes
by using the summation of many action potentials sent by neurons in
brain.
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6. EEG Recording and Measurement
The functional and physiological changes within brain can registered by
EEG,MEG and FMRI
Signal
EEG FMRI MEG
• EEG :- Electroencephalogram.
• FMRI:- Functional Magnetic Resonance imaging.
• MEG:- Magnetoencephalogram.
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7. reasons of not using FMRI about using EEG,MEG
• Time resolution of FMRI image is very low (2 frames/sec).
• Many types of mental activities brain disorders cannot be
registered using FMRI.
• Accessibility of FMRI systems is limited and costly.
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8. Alpha Wave
Characteristics:
- frequency: 8-13 Hz
-amplitude: 20-60 μV
• Easily produced when quietly sitting in relaxed position with eyes
closed (few people have trouble producing alpha waves)
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11. Delta Waves
Characteristics:
-frequency: .5-3.5 Hz
-amplitude: 20-200μV
• Found during periods of deep sleep in most people
• Characterized by very irregular and slow wave patterns
• Also useful in detecting tumours and abnormal brain behaviours.
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14. Variations in EEG pattern
• EEG signal patterns may significantly change when using drugs for the
treatment and suppression of various mental and CNS abnormalities.
• Variations in EEG patterns may also arise by just looking at the TV
screen or listening to music without any attention.
• Among the external effects the most significant ones are the
pharmacological and drug effects.
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15. Advantages and Disadvantages
Advantages
• It is a relatively cheap, fast, and safe way to check functioning of
different areas of the brain.
• Does not cause any pain and is effective in displaying the metabolical
state of the cortical structures.
Disadvantage:
• It is not very exact. It can only measure activity in general areas, not
specific neural connections
• May experience discomfort from sticky paste and electrodes
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16. The electroencephalograms are widely used in biofeedback systems
for clinical purposes, but their usage as a computer input devices is
limited due to the low level of accuracy.
• Wet Electrodes
EEG electrodes are small metal plates that are attached to the
scalp using a conducting electrode gel. They can be made from
various materials like tin(Sn) , AgCl, Pt and gold
Alternatives:
• MEMS-based, dry electrodes
• Wireless EEG system
Challenges in EEG
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17. Applications:
• An attention-powered car, developed in Australia, uses real-time
sensors to monitor the driver’s concentration and slow the car down
if fatigue or distraction is detected.
• “Brainpal”, a BCI racing game developed in Singapore, uses
neurological feedback (also known as electrical or EEG feedback) to
help improve a player’s attention.
• Used for medical diagnosis and therapy for human beings.
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18. • Operation of computers, wheelchairs other devices using only brain
signals.
• Brainwaves as a game controller
• Brainwaves for controlling robot
• Person identification using brainwaves
brain-wave pattern of every individual is unique and, therefore, the
EEG can be used for building personal identification and authentication
systems.
Future advancement in EEG technology
1. mobile electroencephalogram device
Future Applications of EEG
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19. Refernces
• Jin-Chern Chiou et al“Using Novel MEMS EEG Sensors in Detecting
Drowsiness Application”
• SHARMILA .P, “ELECTROENCEPHALOGRAPHY AND MEMS BASED HYBRID
MOTION CONTROL SYSTEM” International Journal of Industrial Electronics
and Electrical Engineering, ISSN: 2347-6982 Volume-3, Issue-5, May-2015
• MYnd Analytics, Inc“Using Electroencephalography for Treatment Guidance
in Major Depressive Disorder” Biological Psychiatry
• Virgílio Bento et al “Advances in EEG-based Brain-Computer Interfaces for
Control and Biometry”
• A Review of Eeg Sensors used for Data Acquisition:
https://www.researchgate.net/publication/308259085_A_Review_of_Eeg_
Sensors_used_for_Data_Acquisition
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