AUTHOR(S): 

Ying-Fang Lai, Hsiu-Sen Chiang

TITLE

Applying Data Mining for Epileptic Seizure Detection

KEYWORDS

Electroencephalograph, Epilepsy, Discrete Wavelet, Data Mining

ABSTRACT

Epilepsy is a common neurological disorder of the brain to produce sudden illness. The incidence is surpassed only the cerebrovascular. Characterized by measuring brain waves can objectively detect whether subjects are suffering from epilepsy. We analyze physiological parameters of electroencephalogram and retrieve a plurality of sub-band through discrete wavelet transform. Datamining methods including multilayer perceptron neural network, support vector machine and Bayes nets were develops diagnostic mode for epilepsy detection. This result finds Bayes nets had a better performance than other datamining methods.

Cite this paper

Ying-Fang Lai, Hsiu-Sen Chiang. (2016) Applying Data Mining for Epileptic Seizure Detection. Biology and Biomedicine, 1, 88-92