A contralateral channel guided model for EEG based motor imagery classification

Conclusions The proposed method could exclude interference among the EOG channels and the cross-interference between the EOG and EEG channel. The results proved that the EOG signal does have certain useful information for MI classification. The proposed method could emphasize ERD/ERS features, and improve MI classification performance. Significance Compared to the regression method, the raw data based and the ipsilateral EOG channel based methods, the proposed method has significantly improved the MI classification performance. In addition, compared to other state-of-the-art methods, our approach also has obtained the best performance.
Source: Biomedical Signal Processing and Control - Category: Biomedical Science Source Type: research