An Efficient P300-based Brain-Computer Interface with Minimal Calibration Time

Brain-Computer Interfaces (BCI) are communication systems that enable subjects to send commands to computers by using only their brain activity [1]. Most existing BCI are based on ElectroEncephaloGraphy (EEG) as the measure of brain activity [1]. So far, BCI have been proven to be very promising communication and control tools for disabled people [1]. A promising brain signals used in the design of assistive BCI for disabled people is the P300, a positive waveform occuring roughly 300 ms after a rare and relevant stimulus [1, 2]. In order to use a P300-based BCI, subjects have to focus their attention on a given stimulus randomly appearing among many others, each stimulus corresponding to a given command. The appearance of the desired stimulus being rare and relevant, it is expected to trigger a P300 in the subject’s brain activity. As such, detecting the P300 enables the system to identify the desired stimulus and hence the desired command. Interestingly enough, P300-based BCI have been successfully used to control a wheelchair (see, e.g., [3]) or to enable severely disabled users to spell words [2, 4].