Using ICA for removal of ocular artifacts in EEG recorded from blind subjects

被引：73
|
作者：
Flexer, A
Bauer, H
Pripfl, J
Dorffner, G
机构：
[1] Austrian Res Inst Artificial Intelligence, A-1010 Vienna, Austria
[2] Univ Vienna, Dept Psychol, A-1010 Vienna, Austria
[3] Med Univ Vienna, Ctr Brain Res, Dept Med Cybernet & Artificial Intelligence, A-1010 Vienna, Austria
来源：
NEURAL NETWORKS | 2005年 / 18卷 / 07期
基金：
奥地利科学基金会;
关键词：
independent component analysis; electroencephalogram;
D O I：
10.1016/j.neunet.2005.03.012
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
One of the standard applications of Independent Component Analysis (ICA) to EEG is removal of artifacts due to movements of the eye bulbs. Short blinks as well as slower saccadic movements are removed by subtracting respective independent components (ICs). EEG recorded from blind subjects poses special problems, since it shows a higher quantity of eye movements, which are also more irregular and very different across subjects. It is demonstrated that ICA can still be of use by comparing results from four blind subjects with results from one subject without eye bulbs who therefore does not show eye movement artifacts at all. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码：998 / 1005
页数：8
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