Electrocardiography Signal Analysis Using Neural Networks on FPGA: System Design and Implementation

This book presents a proposed design and implementation for an integrated ECG diagnosing system. The system employs machine learning algorithms to analyze ECG signals. The proposed system discusses the block architecture for every pattern recognition system,from data acquisition, data cleansing, feature extraction and classification algorithm.The design uses back propagation neural network as a classifier block. The whole system is finally implemented on XILINX Field Programming Gate Array(FPGA) board to verify the functionality of the integrated architecture.

Mohamed G. Egila received his Bachelor degree, and Master degree in Electronics and Communications from Cairo University, Egypt, and PhD degree in Electronics and Communications from Ain Shams University, Egypt, in 2016. His research interests are focusing on Analytics and Machine Learning algorithms. He is now a Postdoctoral Fellow at École Polytechnique de Montréal, Québec, Canada, since 2017.