Design of EEG data acquisition system based on Raspberry Pi 3 for acute ischemic stroke identification

Abstract

This study demonstrates the feasibility of identifying and quantifying pathological changes in brain electrical activity with a portable eight-channel data acquisition system based on Raspberry Pi 3 and MATLAB-based Graphical User Interface (GUI) to perform analyses on Electroencephalogram (EEG) signal including Fast Fourier Transform (FFT), Power Spectral Density (PSD), Relative Power Ratio (RPR), and Brain Symmetry Index (BSI). These parameters are important for analyzing various electrical brain activities including confirmation of acute ischemic stroke and EEG biofeedback analysis for stroke rehabilitation. The data acquisition system is using Raspberry Pi 3 and Front-End Analog to Digital Converter (ADC) ADS1299EEG-FE to stream the data that will be processed and displayed in the MATLAB-based GUI. The accuracy error obtained from validation result of the developed system is 2.18% and the Total Harmonic Distortion (THD) performance criterion resulting in 1.58% for square wave and 1.73% for sine wave. The system will be used in another study to identify acute ischemic stroke and as the rehabilitation tool, especially the post-stroke motor function.