Abstract:

Considering the prior probability of EEG signals is non-equal in some application scenario of brain-computer interface, we propose a asynchronous detection algorithm of steady-state visual evoked potential brain-computer interface (SSVEP-BCI) based on maximum posterior criterion. Using spatio-temporal equalization multi-window technology, a dynamic window algorithm based on sequential detection is designed by introducing maximum posterior criterion, which makes full use of prior information to improve the performance of brain-computer interface systems. Experiments show that compared with the traditional spatio-temporal equalization multi-window algorithm, the target recognition accuracy of the proposed algorithm is increased, and the average practical bit rate has a substantial improvement. Besides, the instruction time and the average false alarm rate are significantly reduced. Thus the effectiveness and practicability of the proposed algorithm are verified.

Key words: steady-state visual evoked potential, brain-computer interface, maximum posterior criterion; asynchronous detection algorithm