Automatic Recognition of Epilepsy from EEG using Artificial Neural Network and Discrete Wavelet Transform

In this study, it was aimed that making epilepsy diagnosis by automatically evaluation of EEG records. Diagnosis system consists two steps which are feature extraction/selection and classification. Discrete wavelet transform (DWT) and artificial neural networks (ANN) were used to determine attribute vectors and classification, respectively. Classification accuracy was achieved as 99.62% by examining effects of varied wavelets on multi layer perceptron (MLP) networks which have different architecture and were trained different learning algorithms.