Towards increasing the number of commands in a hybrid brain-computer interface with combination of gaze and motor imagery

Non-invasive brain-computer interface (BCI) provides a novel means of communication. This can be achieved by measuring electroencephalogram (EEG) signal over the sensory motor cortex of a person performing motor imagery (MI) tasks. However, the performance of BCI remains currently too low to be of wide practical use. A hybrid BCI system could improve the performance by combining two or more modalities such as eye tracking, and the detection of brain activity responses. In this paper, first, we propose a simultaneous hybrid BCI that combines an event-related de-synchronization (ERD) BCI and an eye tracker. Second, we aim to further improve performance by increasing the number of commands (i.e., the number of choices accessible to the user). In particular, we show a significant improvement in performance for a simultaneous gaze-MI system using a total of eight commands. The experimental task requires subjects to search for spatially located items using gaze, and select an item using MI signals. This experimental task studied visuomotor compatible and incompatible conditions. As incorporating incompatible conditions between gaze direction and MI can increase the number of choices in the hybrid BCI, our experimental task includes single-trial detection for average, compatible and incompatible conditions, using seven different classification methods. The mean accuracy for MI, and the information transfer rate (ITR) for the compatible condition is found to be higher than the average and the incompatible conditions. The results suggest that gaze-MI hybrid BCI systems can increase the number of commands, and the location of the items should be taken into account for designing the system.