Research on removing ocular artifact automatically from EEG signals

被引：0

作者：

机构：

[1] College of Electronic Information and Control Engineering, Beijing University of Technology

来源：

Li, M.-A. (limingai@bjut.edu.cn) | 1600年 / Chinese Institute of Electronics卷 / 41期

关键词：

Automatic removal; Discrete wavelet transform (DWT); Electroencephalography; Independent component analysis (ICA); Ocular artifact;

D O I：

10.3969/j.issn.0372-2112.2013.06.026

中图分类号：

学科分类号：

摘要：

Electroencephalography (EEG) is easily affected by ocular artifact (OA), which appears in EEG randomly as a big pulse. Based on discrete wavelet transform (DWT) and independent component analysis (ICA), a novel automatic method of OA removal, denoted as DWICA, was proposed. Firstly, DWT was applied to the recorded EEG and electrooculogram (EOG) to obtain multiple scale coefficients, and the combined coefficients were considered as the input for ICA. Secondly, the independent components were acquired based on FastICA algorithm with negentropy criterion. The angle cosine criterion was introduced to recognize ocular artifact component. Furthermore, the inverse algorithm of ICA was applied to project the independent components without OA to original electrodes. Finally, the EEG were reconstructed using the inverse algorithm of DWT, and then the pure EEG were obtained. Experimental results show that DWICA is preferable in automatic removal of OA. The method provides a new idea for on-line preprocessing of EEG signals.

引用

页码：1207 / 1213

页数：6

共 10 条

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