Preface to the Supplement Issue on New Trends on Biomedical Knowledge Acquisition and Information Processing Systems

Authors:
Giner Alor-Hernández;Ruben Posada-Gómez;Alejandro Rodríguez-González
Affiliations:
Technological Institute of Orizaba, Orizaba, Mexico;Technological Institute of Orizaba, Orizaba, Mexico;Centre for Plant Biotechnology and Genomics, Polytechnic University of Madrid, Madrid, Spain
Venue:
Journal of Medical Systems
Year:
2012

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Abstract

In this study, it has been intended to perform an automatic classification of Electroencephalography (EEG) signals via Artificial Neural Networks (ANN) and to investigate these signals using Wavelet Transform (WT) for diagnosing epilepsy syndrome. EEG signals have been decomposed into frequency sub-bands using WT and a set of feature vectors which were extracted from the sub-bands. Dimensions of these feature vectors have been reduced via Principal Component Analysis (PCA) method and then classified as epileptic or healthy using Multilayer Perceptron (MLP) and ELMAN ANN. Performance evaluation of the used ANN models have been carried out by performing Receiver Operation Characteristic (ROC) analysis.