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Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis

Detecting artifacts produced in EEG data by muscle activity, eye blinks and electrical noise is a common and important problem in EEG research. It is now widely accepted that independent component analysis (ICA) may be a useful tool for isolating artifacts and/or cortical processes from electroencep...

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書誌詳細
主要な著者: Delorme, Arnaud, Sejnowski, Terrence, Makeig, Scott
フォーマット: Artigo
言語:Inglês
出版事項: 2006
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC2895624/
https://ncbi.nlm.nih.gov/pubmed/17188898
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2006.11.004
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