Study on Applying Independent Component Analysis to Remove Blink Artifacts and Power Noise in EEG

Blink artifacts and power noise are constantly found:to strongly iufluence the acquisition and analysis of EEG signals.In this paper,by comparing the efficiencies of two ICA algorithms-Infomax ICA and Extended Infomax ICA methods in extracting blink artifacts and power noise in the EEG signals,it was shown that ICA algorithms were insensitive to disturbance in the conditions of low signal noise ratio,and ICA algorithms demonstrated a strong robustness in processing non stationary signals.Though blink slow waves could be extracted by infomax algorithm,but power noise was unlikely to be removed by it.Therefore,Extended Infomax ICA algorithm should be used.By applying Extended Infomax algorithms,blink artifacts and power noise contained in the 16 channel EEG signals of Alzheimer disease patients were removed successfully(the lowest signal noise ratio for power noise can be -40dB).Meanwhile,it proved by calculating approximation entropy (ApEn) that ICA algorithms could preserve the nonlinear characteristics of EEG after removing the interference.