中国电子科技2005，Vol.3Issue(4)：369-371,3.
Extracting Epileptic Feature Spikes Using Independent Component Analysis
Extracting Epileptic Feature Spikes Using Independent Component Analysis
摘要
Abstract
In recent years, blind source separation (BSS) by independent component analysis (ICA) has been drawing much attention because of its potential applications in signal processing such as in speech recognition systems, telecommunication and medical signal processing. In this paper, two algorithms of independent component analysis (fixed-point ICA and natural gradient-flexible ICA) are adopted to extract human epileptic feature spikes from interferential signals. Experiment results show that epileptic spikes can be extracted from noise successfully. The kurtosis of the epileptic component signal separated is much better than that of other noisy signals. It shows that ICA is an effective tool to extract epileptic spikes from patients' electroencephalogram EEG and shows promising application to assist physicians to diagnose epilepsy and estimate the epileptogenic region in clinic.关键词
independent component analysis/epilepsy/feature spikes/electro- encephalogram (EEG)Key words
independent component analysis/epilepsy/feature spikes/electro- encephalogram (EEG)分类
信息技术与安全科学引用本文复制引用
YAN Hong-mei,XIA Yang,LIU Yan-su,LAI Yong-xiu,YAO De-zhong,ZHOU Dong..Extracting Epileptic Feature Spikes Using Independent Component Analysis[J].中国电子科技,2005,3(4):369-371,3.基金项目
Supported by 973 Project (No. 2003CB71606) and National Natural Science Foundation of China (No.30400105, 90208003) （No. 2003CB71606）
