Asynchronous P300 BCI: SSVEP-based control state detection

Rajesh Chandrasekhara Panicker, Sadasivan Puthusserypady, Ananda P. Pryana, Ying Sun

Abstract: An asynchronous hybrid brain-computer interface (BCI) system combining the P300 and steady-state visually evoked potentials (SSVEP) paradigms is introduced. A P300 base system is used for information transfer, and is augmented to include SSVEP for control state detection. The proposed system has been validated through off-line and online experiments. It is shown to achieve fast and accurate control state detection without significantly compromising the performance. For the two subjects who participated in the online experiments, the system achieved an average data transfer rate of 20.13 bits/min, with control state classification accuracy of more than 97%.