Electroencephalogram Analysis Based on Artificial Neural Network and Adaptive Segmentation

Abstract

This paper presents the assistant diagnostic system for epilepsy detection based on the neural network technique. A goal of EEG signals analysis is not only human psychologically and functionality states definition but also pathological activity detection. In this paper we describe an approach for epileptiform activity detection by the artificial neural network technique for EEG signal segmentation and for the highest Lyapunov’s exponent computing. The EEG segmentation by the neural network approach makes it possible to detect an abnormal activity in signals. We examine our system for segmentation and anomaly detection on the EEG signal where the anomaly is an epileptiform activity.