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


TOPRAK İ. B. , Caglar M. F. , Merdan M.

IEEE 15th Signal Processing and Communications Applications Conference, Eskişehir, Turkey, 11 - 13 June 2007, pp.1122-1123 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2007.4298758
  • City: Eskişehir
  • Country: Turkey
  • Page Numbers: pp.1122-1123

Abstract

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.