Abstract
A robust space-time-frequency signal extraction algorithm has been developed with an application to brain computer interface (BCI). The algorithm is based on extending time-frequency masking methods to accommodate the spatial domain. The space-time-frequency masks are then clustered in order to extract the desired source. Then the motion of the extracted source it tracked over the scalp. Finally, the trials are classified based on their directionality and locations over the scalp. The proposed method outperforms traditional systems by exploiting the motion of the sources.