Neural Networks for Chaotic Signal Processing: Application to the Electroencephalogram Analysis for Epilepsy Detection

Abstract

Many techniques were used in order to detect and to predict epileptic seizures on the basis of electroencephalograms. One of the approaches for the prediction of epileptic seizures is the use the chaos theory, namely determination largest Lyapunov's exponent or correlation dimension of scalp EEG signals. This paper presents the neural network technique for epilepsy detection. It is based on computing of largest Lyapunov's exponent.The results o f experiments are discussed.