Endogenous sensory discrimination and selection by a fast brain switch for a high transfer rate brain-computer interface

We present a novel multi-class brain-computer interface (BCI) for communication and control. In this system, the information processing is shared by the algorithm (computer) and the user (human). Specifically, an electro-tactile cycle was presented to the user, providing the choice (class) by delivering timely sensory input. The user discriminated these choices by his/her endogenous sensory ability and selected the desired choice with an intuitive motor task. This selection was detected by a fast brain switch based on real-time detection of movement-related cortical potentials from scalp EEG. We demonstrated the feasibility of such a system with a four-class BCI, yielding a true positive rate of
$\sim {\hbox{80}}\%$
and
$\sim {\hbox{70}}\%$
, and an information transfer rate of
$\sim {\hbox{7}}~{\hbox{bits}}/{\hbox{min}}$
and
$\sim {\hbox{5}}~{\hbox{bits}}/{\hbox{min}}$
, for the movement and imagination selection command, respectively. Furthermore, when the system was extended to eight classes, the throughput of the system was improved, demonstrating the capability of accommodating a large number of classes. Combining the endogenous sensory discrimination with the fast brain switch, the proposed system could be an effective, multi-class, gaze-independent BCI system for communication and control applications.