一种基于SSVEP和P300的联合脑-机接口范式

Hybrid BCI based on multiple electroencephalographs could effectively improve the performance comparing to the traditional BCI based on single EEG. In consideration to the combination of SSVEP and P300, A new encoding-stimulus model is proposed and then a hybrid BCI paradigm model based on the combination of SSVEP and P300 EEG is devised. In a 3 by 3 character stimulus matrix, columns of characters are flicked at a set frequency to induced SSVEP and a random blue frame is shown on rows to induce P300. Experiments show that when subjects stared a target character, SSVEP and P300 can be induced simultaneously. Therefore, the identification of P300 and SSVEP can detect the target character which subjects selected. Comparing to the traditional P300 BCI paradigm for character-input, the proposed system is able to reduce running time and fundamentally improve the system processing speed. The more practical enhancement with more characters matrix can be extended such as 6 by 6, and a more practical BCI system by multi signal features can be achieved.