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.
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2017, Vol. 38 
