Electrocardiography(EKG) and electro-oculogram (EOG) are the most common interference in electroencephalogram(EEG)

and this paper presents an algorithm to filter artifacts in EEG based on blind source separation of maximum signal noise ratio.The algorithm takes separation matrix as a variable to establish the objective function of original signal to noise ratio

looking for the separation matrix which makes the objective function reach a maximum (or minimum ) value.Then the estimated signal can be obtained through the separation matrix.The algorithm has the following steps in the implementation process.Firstly

part noise in the original EEG is removed through wavelet transform.Then the denoised EEG which still contains EKG and EOG is separated by the algorithm to filter artifacts based on blind source separation of maximum signal noise ratio.And correlation coefficient is introduced to verify the consistency between the outputs of blind source separation and the original signals.The experimental results indicate that the cross-correlation coefficient between the output signals of blind separation dropped significantly compared with the original signals.Thus the algorithm is effective for removing EKG and EOG in EEG.