Epilepsy diagnosis based on generalized feed forward neural network
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Updated: May 15, 2026

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
Published on: December 18, 2016
1Department of Information Techanology, Anuradha Engineering College, Chikhli, 443201, India. pravinakharat82@gmail.com
Abstract:
Epilepsy is a common neurological disorder that is characterized by recurrent unprovoked seizures. Epilepsy can develop in any person at any age. 0.5% to 2% of people will develop epilepsy during their lifetime. This paper aims to develop the clinical decision support system (DSS) for the diagnosis of epilepsy. In this paper a simple, reliable and economical Neural Network (NN) based DSS was proposed for the diagnosis of epilepsy. The generalized feed forward neural network (GFFNN) was designed for the diagnosis. Eleven statistical parameters along with the 64 FFT were extracted for the electroencephalogram (EEG) signal. Data used for the experimentation purpose was obtained from the University of Bonn. The classification rate of GFFNN was 100 % for the training data and 86.67% for the cross validation data.
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