A Novel Automatic Recognition and Removal Method of Ocular Artifacts
LI Ming-ai1,2, GUO Shuo-da1, TIAN Xiao-xia1, YANG Jin-fu1,2, HAO Dong-mei3
1. College of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100124, China;
2. Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing 100124, China;
3. College of Life Science and Bio-Engineering, Beijing 100124, China
In order to improve the overestimation of ocular artifacts (OA) in electroencephalogram (EEG) and the OA removal effect of nonlinear mixture caused by environmental interference coupling, a novel automatic removal method is proposed based on fast kernel independent component analysis (FastKICA) and discrete wavelet transform (DWT), and it is denoted as FKIWT.The independent components are separated from the mixed EEG by using the FastKICA algorithm, and the correlation coefficient is applied to identify OA component;Then, the Multiresolution analysis of OA is achieved with DWT, the approximation wavelet coefficients are set to zero and the detail wavelet coefficients are not changed.So more useful EEG is remained in the reconstructed OA component;Furthermore, the clean EEG is restored with the inverse algorithm of FastKICA.The experimental results show that FKIWT can effectively improve the overestimation of OA and has perfect anti-interference ability and robustness.Meanwhile, the better effects of OA elimination are also obtained on the condition that the linear or nonlinear mixed model is adopted, and the latter's advantage is especially obvious.The FKIWT is suitable for on-line application.
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