Design and Simulation of Front End 3-in-1 EEG, ECG, EMG Bio-Potential Signal Acquisition System
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Date
2020-06
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Addis Ababa University
Abstract
The last couple of years have given birth to meticulously mapped and innovative solutions in
regards to product as well as research of medical analysis tools and diagnostic equipment. The
industry has shown a major transformation on the general process of diagnosis tools providing
flexibility and enhanced accuracy. However, despite the astonishing progress of the bio-medical
industry, the status of medical provision is still a concern in third world countries. The
inaccessibility and unaffordability of medical equipment in such countries needs immediate
attention as many people fall prey to this problem which can be solved through the provision of a
supplementary solution that can aid the process of preliminary diagnosis.
In this thesis, the design of a front-end system for EEG, ECG and EMG signal acquisition is done.
The design addresses the problem of medical provision in under developed nations by providing a
supplementary hardware that is portable making it cost-efficient and readily available. Moreover,
it extends the research aspect in the area through the combination of a 3-in-1 signal acquisition
hardware and optimizing the design in regards to performance, complexity and scalability.
Owing to the fact that the signals operated by the hardware are very weak in nature, the utilization
of low noise amplifiers with very high common-mode rejection ratio and gain adjustment is
critical. Moreover, the implementation of analog-to-digital conversion needs a thorough analysis
in regards to the architecture, resolution and area of application. Accordingly, the design in this
thesis is specifically done so as to improve the performance in regards to noise cancellation,
minimization of filter circuitry, number of channels and overall circuit complexity.
Verification of the design is done with the co-simulation of PSPICE and SIMULINK. The
simulation is carried out for individual cases of EEG, EMG and ECG application by using
physiological signals of patients from PhysioNet.org through the addition of noise signals to mimic
actual physical application of the hardware. Furthermore, the output is analyzed and compared
with existing products and previous researches in the area which yielded a 21% improvement in
common-mode rejection ratio and a 33% increase in channel capacity.
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Keywords
Simulation, End 3-in-1 EEG, ECG, EMG Bio-Potential Signal