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使用独立成分分析(ICA)去除盲人受试者脑电图记录中的眼电伪迹。

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

作者信息

Flexer Arthur, Bauer Herbert, Pripfl Jürgen, Dorffner Georg

机构信息

The Austrian Research Institute for Artificial Intelligence, Freyung 6/6, A-1010 Vienna, Austria.

出版信息

Neural Netw. 2005 Sep;18(7):998-1005. doi: 10.1016/j.neunet.2005.03.012.

Abstract

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.

摘要

独立成分分析(ICA)在脑电图(EEG)中的标准应用之一是去除由于眼球运动产生的伪迹。通过减去各自的独立成分(IC),可以去除短暂眨眼以及较慢的扫视运动。从盲人受试者记录的脑电图带来了特殊问题,因为它显示出更多的眼球运动,而且这些运动在受试者之间更不规则且差异很大。通过将四名盲人受试者的结果与一名没有眼球、因此完全没有眼球运动伪迹的受试者的结果进行比较,证明ICA仍然有用。

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