Towards an EEG-based Intuitive BCI Communication System Using Imagined Speech and Visual Imagery

Communication using brain-computer interface (BCI) has developed in attempts toward an intuitive system by decoding the imagined speech or visual imagery. However, discrimination between the two paradigms may be ambiguous because the user intention contains their original meaning. A clear distinction between the two paradigms may facilitate the active use of them leading to an intuitive BCI conversation system. In this study, we compared imagined speech and visual imagery in the perspective of its presence, spatial features, and classification performance based on electroencephalography. Seven subjects performed both imagined speech and visual imagery of twelve words/phrases. We showed the presence of the two paradigms, having distinct brain region from each other. The maximum thirteen-class classification accuracy including rest class was 34.2 % for imagined speech and 26.7 % for visual imagery. Therefore, we investigated the possibility of multiclass classification of more than ten classes in both paradigms, showing the potential of them to be used in the real world communication system. These findings could further be utilized in the intuitive communication for locked-in patients sending commands to the external world simply by thinking of ‘the very thing’ that the user wants to deliver.