Design of an Electro Encephalo Gram Module and Processing the signals through Savitzky –Golay filter for Machine Learning Applications
Keywords:
EEG, Instrumentation amplifier, Sallen-Key low pass filter, Savitzky Golay filter, Machine learning techniquesAbstract
Electroencephalography, Magneto Encephalo Graphy (MEG), and Positron Emission Tomography (PET), and also functional Magnetic Resonance Imaging (fMRI), are noninvasive neurosignal recording techniques. Epilepsy is the world's second most prevalent psychosomatic illness, affecting around 40 million people globally. The methodology includes the implementation of an Electroencephalogram(EEG)module that captures the brain signals to analyze the different emotions of a person. The elements of a circuit that use frequency modulation to improve signal-to-noise communications and it has been developed using proteus software and generated 3d module of the same. The Sallen-Key low pass filter is the most often used second-order active low pass filter because of its high input impedance, strong stability, and low output impedance. The proposed method comprises a protection circuit, an instrumentation amplifier, and a Sallen-key circuit that can increase the efficiency of signal to noise ratio. The retrieved signal is fed into the methodological circuit, with the resulting EEG signal being processed using the Savitzky Golay filter. The filtered output was then used to prepare a dataset that could be used for machine learning techniques.
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