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http://dx.doi.org/10.5369/JSST.2004.13.3.199

Prediction and Classification System for Temporal lobe Epilepsy  

Kim, Min-Soo (Department of Electronic Engineering, Yeungnam University)
Seo, Hee-Don (Department of Electronic Engineering, Yeungnam University)
Publication Information
Journal of Sensor Science and Technology / v.13, no.3, 2004 , pp. 199-206 More about this Journal
Abstract
Epileptic seizures result from a temporary electrical disturbance of the brain. In this paper, a method of discriminating EEG for diagnoses of temporal lobe epilepsy is proposed. The proposed method for classification of epilepsy and sleep EEG is based on the wavelet transform and the fuzzy c-means. The magnitude and mean of wavelet coefficients for each EEG band are applied to the cluster of the FCM classifier. The proposed system show a little more accurate diagnosis for EEG by analysis of frequency for Wavelet and the success rate of 95% classification using FCM. From the simulation results by the implemented system, we demonstrated this research can be reduce doctor's labors and realize quantitative diagnosis of EEG.
Keywords
epileptic; sleep EEG; FCM; wavelet transform;
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