Presentation 2004/6/18
Applying a Novel ICA Algorithm to Single-trial Flat EEG Analysis
Jianting CAO, Liangyu ZHAO, Enhua SHEN, Yan CAO, Fanji GU, Zhijie CAI, Jiong RUAN,
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Abstract(in English) As a typical example of lost consciousness, studying on the flat EEG and brain death judgment criteria are the most important social issues. Due to the lower-power activities, artifacts such as heart action and environmental noise are contaminated in the EEG signals, therefore, the judgment of brain death based on the flat EEG wave is always debatable in clinic. In this report, we present a robust approach for decomposing unaveraged single-trial EEG data. Our approach has two procedures. In the first step, a PCA-like pre-whitening technique with an additive noise reduction technique is presented. In the second step, a robust nonlinear function derived by the parameterized t-distribution model is applied to decompose the mixtures of sub-Gaussian and super-Gaussian source components.
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Keyword(in English) Independent component analysisi / Electroencephalography (EEG) / single-trial data analysis
Paper # NC2004-29
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Committee NC
Conference Date 2004/6/18(1days)
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Registration To Neurocomputing (NC)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Applying a Novel ICA Algorithm to Single-trial Flat EEG Analysis
Sub Title (in English)
Keyword(1) Independent component analysisi
Keyword(2) Electroencephalography (EEG)
Keyword(3) single-trial data analysis
1st Author's Name Jianting CAO
1st Author's Affiliation Saitama Institute of Technology:Brain Science Institute, RIKEN()
2nd Author's Name Liangyu ZHAO
2nd Author's Affiliation Saitama Institute of Technology
3rd Author's Name Enhua SHEN
3rd Author's Affiliation Fudan University
4th Author's Name Yan CAO
4th Author's Affiliation Fudan University
5th Author's Name Fanji GU
5th Author's Affiliation Fudan University
6th Author's Name Zhijie CAI
6th Author's Affiliation Fudan University
7th Author's Name Jiong RUAN
7th Author's Affiliation Fudan University
Date 2004/6/18
Paper # NC2004-29
Volume (vol) vol.104
Number (no) 140
Page pp.pp.-
#Pages 6
Date of Issue