Removal of Artifacts in Electroencephalogram Using Adaptive Infomax Algorithm of Blind Source Separation

Authors:
Wanyou Guo;Liyu Huang;Li Gao;Tianqiao Zhu;Yuangui Huang
Affiliations:
Department of Biomedical Engineering, Xidian University, Xi'an, China 710071;Department of Biomedical Engineering, Xidian University, Xi'an, China 710071;Department of Biomedical Engineering, Xidian University, Xi'an, China 710071;Department of Biomedical Engineering, Xidian University, Xi'an, China 710071;Xijing Hospital, The Fourth Military Medical University, Xi'an, China 710032
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Year:
2008

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Abstract

Infomax algorithm is one of the main strategies in blind source separation. The principle and improvement of the algorithm are introduced firstly in this paper. Nineteen-channel Electroencephalograms (EEGs) which include electromyogram, eye-movement and some other artifacts were decomposed by using this algorithm. Afterwards, three kinds of nonlinear parameters were calculated for all the independent components, and artifact components can be identified automatically by threshold settings. Finally, putting all the artifact components into zero, and projecting the other components to the scalp electrodes, then the purer Electroencephalograms can be gained. The study shows that the various artifacts can be separated from the EEGs successfully with the use of adaptive Infomax algorithm and removal of artifacts can be realized by signal reconstruction. Adaptive Infomax algorithm is a potential tool in removal of artifacts in physiological signal.