基于子空间分解的脑电信号眼电伪迹自动去除方法研究

doi:10.3969/j.issn.1000-1158.2017.06.20

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Abstract To solve the electrooculogram (EOG) artifact elimination problem of electroencephalogram (EEG) signals,an automatic EOG artifact removal method is proposed based on geometric subspace decomposition. Geometric subspace is constructed by maximum noise fraction (MNF) approach, the decomposition in geometric subspace is used to separate multichannel EEG into a series of MNF components. The MNF components have the high correlation degree contain EOG artifact based on Spearman rank correlation coefficient. Thus EOG artifacts can be extracted in this detail way. Then the artifact free EEG signals are obtained by accumulating and reconstructing the processed components after projected back in signal space. Both generated data set and raw recordings were studied, combining the advantage of energy distribution visualization in brain mapping plots, the experiment results showed the effectiveness of the proposed method in artifact elimination.

Key words： metrology EEG signals geometric subspace maximum noise fraction Spearman rank correlation coefficient EOG artifact elimination

Received: 21 September 2016 Published: 27 September 2017

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TB973

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	Articles by authors
	FU Rong-rong
	HOU Pei-guo
	SHI Pei-ming
	MENG Zong

Cite this article:

FU Rong-rong,HOU Pei-guo,SHI Pei-ming, et al. Automatic EOG Artifact Elimination of EEG based on subspace decomposition[J]. Acta Metrologica Sinica, 2017, 38(6): 749-753.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2017.06.20 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2017/V38/I6/749

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