By Topic

Epileptic seizure detection in grouped multi-channel EEG signal using ICA and wavelet transform

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Han-Yen Chang ; Department of Electrical, Engineering National Cheng Kung, University Tainan, Taiwan, ROC ; Sheng-Chih Yang ; Sheng-Hsing Lan ; Pau-Choo Chung

In this paper, we propose a new scheme which combines two algorithms to detect epileptic seizure in the grouped multi-channel EEG signals. For the proposed scheme, a recent technique, Independent Component Analysis (ICA), is first adapted to separate blind sources and extract feature from grouped EEG signals. Then, Wavelet transform is followed for multi resolution and multi-level analysis on those primary signals extracted by ICA. Finally, a threshold method based on wavelet transform again is applied to detect the epileptic seizure. A series of experiments using different method combination are conducted and the experimental results show that the proposed method has a superior quality.

Published in:

Proceedings of 2010 IEEE International Symposium on Circuits and Systems

Date of Conference:

May 30 2010-June 2 2010