Automatic detection of epileptic spike using fuzzy ARTMAP neural network

Authors:
Ali Farrokhi;Nemat Talebi;Fatemeh Safari
Affiliations:
Electrical and Electronic Engineering, Islamic Azad University, Tehran, Iran;Electrical and Electronic Engineering, Islamic Azad University, Tehran, Iran;Electrical and Electronic Engineering, Islamic Azad University, Tehran, Iran
Venue:
ISCGAV'10 Proceedings of the 10th WSEAS international conference on Signal processing, computational geometry and artificial vision
Year:
2010

Citing 5
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Abstract

The present paper attempts to introduce a new approach for the automatic detection of epileptic spikes in EEG signal which plays a vital role in diagnosing epilepsy. In this approach, we have detected and classified epileptic spikes by using extracted features and Fuzzy ARTMAP neural network. The performance of classifying system is evaluated by three criteria of sensitivity, selectivity and specificity. For the classifying system applied in the current study, the obtained values of these three criteria are 88.24%, 93.75% and 90.9%, respectively, which compared with MLP classifier system, benefits from a higher speed and precision.