EEG Artifact Removal Method Based on CuBICA Algorithm
Cai Xin-bo · Jisuanji gongcheng · 2012
According to high order cumulant and Independent Component Analysis(ICA),this paper proposes a method of removing artifacts from Electroencephalogram(EEG) based on CuBICA.The Electroencephalogram which mixing with EOG and EKG signals are denoised by wavelet package analysis,after centering and whitening,the EEG signals which still containing EOG and EKG is separated by CuBICA algorithm.The cross correlation coefficient of the separated signals is analyzed,result shows that CuBICA algorithm can efficiently separate EOG and EKG from EEG,and get pure EEG.