Aiming at the problems such as the overestimation of ocular artifact, the need of human intervention, and the difficulty for online application in traditional blind source separation (BSS)-based methods for artifacts removal, a totally automatic method for removing ocular artifacts was proposed. BSS was used to separate electroencephalogram (EEG) signals to obtain the independent components. With the criterion of correlation coefficient, different time windows according to vertical electrooculogram (VEOG) and horizontal electrooculogram (HEOG)'s respective characteristics were used to find the best components combination, by which the time intervals that have blink or eye movement activities could be calibrated. Then, the calibrated time intervals were removed and the EEG signals were reconstructed. With experiments of P300 signals processing, this method was proved to be effective and practical in removing ocular artifact automatically and overcoming the drawbacks above. Compare with related literatures, the experiment results showed that the proposed method increased the average correlation coefficient between the reconstructed EEG signals and the original EEG signals from 0.8513 and 0.9006 to 0.9237 respectively, while the mean square error was decreased by 19.3% and 16.6%, contributing to online application.
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