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Journal of Biomedicine and Biotechnology
Volume 2004 (2004), Issue 1, Pages 5-9
http://dx.doi.org/10.1155/S111072430421004X
Research article

Automatic Discrimination of Abnormal Subjects Using the Visual Evoked Potential Spectral Components

Centre for Medical Electronics, Anna University, Chennai 600 025, India

Received 25 November 2002; Accepted 26 November 2002

Copyright © 2004 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Study of visual evoked potential (VEP) is one of the utilized methods in clinical diagnosis of ophthalmology and neurological disorders. The automatic detection of VEP spectral components is an important tool in the diagnosis of mental activity. This paper presents a novel computational approach using feedforward neural network to identify abnormal subjects from changes in spectral components. The output vector from the feedforward neural network is based on the VEP spectral components. The software was developed to identify mental state from the VEP spectral components using Matlab software package. Using this approach, it is possible to perform real-time abnormality identification accurately on personal computers.