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A Neural Network Model for Predicting Epileptic Seizures based on Fourier-Bessel Functions
Shaik.Jakeer Husain,Dr.K.S.Rao 보안공학연구지원센터 2014 International Journal of Signal Processing, Image Vol.7 No.5
To improve the social life of drug resistant epilepsy persons, a patient specific algorithm is needed that can predict seizures based on EEG with high sensitivity and specificity before the occurrence of a seizure. This algorithm predicting the seizure occurrence from Inter-ictal (seizure free) and pre-ictal (before seizure) transition. In this algorithm features are extracted by Fourier Bessel Expansion from inter-ictal and pre-ictal EEG signals. A neural network using back propagation algorithm is implemented for classification of epileptic states. The performance of algorithm is evaluated based on three measures, sensitivity, and specificity and classification accuracy. The results illustrate that the algorithm can predict seizures of two subjects before five minutes with an accuracy of 99.6%