DocumentCode :
3376622
Title :
Epileptic seizure detection in grouped multi-channel EEG signal using ICA and wavelet transform
Author :
Chang, Han-Yen ; Yang, Sheng-Chih ; Lan, Sheng-Hsing ; Chung, Pau-Choo
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
fYear :
2010
fDate :
May 30 2010-June 2 2010
Firstpage :
1388
Lastpage :
1391
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.
Keywords :
blind source separation; electroencephalography; feature extraction; independent component analysis; medical signal detection; medical signal processing; seizure; signal resolution; wavelet transforms; ICA; blind sources; epileptic seizure detection; feature extraction; grouped multichannel EEG signal; independent component analysis; multilevel analysis; multiresolution analysis; wavelet transform; Data mining; Electroencephalography; Epilepsy; Feature extraction; Independent component analysis; Medical signal detection; Principal component analysis; Signal analysis; Wavelet analysis; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-5308-5
Electronic_ISBN :
978-1-4244-5309-2
Type :
conf
DOI :
10.1109/ISCAS.2010.5537262
Filename :
5537262
Link To Document :
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