FPGA-based ANN Design for Detecting Epileptic Seizure in EEG Signal

Abstract

This study aims to represent an FPGA (FieldProgrammable Gate Array) design of Artificial Neural Network(ANN) for Electroencephalography (EEG) signal processing inorder to detect epileptic seizure. For analyzing brain’s electricalactivity, feedforward ANN model is used for classification ofEEG signals. The designed ANN output layer makes a decisionwhether the person has epilepsy or not. In the proposed system,the ANN model is programmed and simulated on Xilinx ISEeditor via computer and then, EEG signal data are transferred toFPGA-based ANN emulator core. The Core is trained on datawhich are patient’s data and healthy person’s data. Aftertraining, test data is loaded to ANN Emulator Core to detect anyepileptic seizure of person’s EEG signal. The main advantage ofFPGA in the system is to improve speed and accuracy forepileptic seizure detection.