Elimination of Ocular Artifacts from EEG signals using the wavelet transform and empirical mode decomposition

Electroencephalogram (EEG) is a biological signal that represents the electrical activity of the brain. EEG signal may be highly distorted by the eye-blinks and movements of the eyeballs that are collectively known as ocular artifacts (OA). OA severely limit the utility of the recorded EEG and thus need to be removed for better clinical evaluation. The frequency range of EEG signal is 0 to 64 Hz and the OA occur within the range of 0 to 16 Hz. Therefore, simple filtering techniques cannot be used to eliminate OA from EEG. This paper present a method based on the wavelet transform to automatically identify the OA zones in contaminated EEG signal. Then, only removing it's to obtain the clean EEG by the recently developed empirical mode decomposition (EMD) algorithm. Simulation results show the superiority of the proposed method in identification and removal of ocular artifacts from EEG signal comparison with other filtering approaches.