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

Han Yen Chang, Sheng Chih Yang, Sheng Hsing Lan, Pau Choo Chung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems
Subtitle of host publicationNano-Bio Circuit Fabrics and Systems
Pages1388-1391
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010 - Paris, France
Duration: 2010 May 302010 Jun 2

Publication series

NameISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems

Other

Other2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010
Country/TerritoryFrance
CityParis
Period10-05-3010-06-02

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Epileptic seizure detection in grouped multi-channel EEG signal using ICA and wavelet transform'. Together they form a unique fingerprint.

Cite this