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Analog Filtering of EEG signals in the Presence of Artifact Signals


Analog Filtering of EEG signals in the Presence of Artifact Signals

Asamoah, Kwabena (2022) Analog Filtering of EEG signals in the Presence of Artifact Signals. Masters thesis, Concordia University.

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Recovery of bio-electric signals, such as EEG, ECG, have been routinely done in the past via sophisticated numerical algorithms and extensive computing resources. Current works on filtering of EEG signals does not clearly reveal the electronic circuit operations by which the artifact signals can be obtained to serve as a reference signal for filtering operation. A technique to isolate the artifact signals mixed with intended bio-electric signals (i.e., EEG), by using analog circuit components has been proposed in the thesis. The artifact signal band is assumed to be separated from the intended signal bands.
The novelty of the approach lies in recovering the artifact signal from the mixture of contaminated biomedical signals and then re-using it to recover the intended signals. Prior knowledge about the artifact signal is not needed, except for demonstration of the principles through simulation work. Data base of CMOSP 18 technology available in the VLSI laboratory of Concordia University has been used for all simulations.
The use of recovered artifact signal as a reference signal for the filtering process by elimination of the intended signal, is presented in the thesis. All these operations were easily implemented with analog circuit components. Further work along this direction will be very useful in developing wearable electronic devices for communication of point-of-care health data from a human body, wirelessly to distant medical center locations for further processing. This is expected to provide relatively inexpensive solutions toward current day trend of wireless point-of-care electronic circuits and systems for public health monitoring.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Asamoah, Kwabena
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:October 2022
Thesis Supervisor(s):Rabin, Raut and M.N.S, Swamy
ID Code:991351
Deposited By: Kwabena Asamoah
Deposited On:21 Jun 2023 14:29
Last Modified:21 Jun 2023 14:29
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