A new brain-computer interface paradigm based on P300 and SSVEP

Brain-Computer Interface (BCI) is a novel communication system without depending on conventional brain output paths (such as peripheral nerve and muscle tissue) of the brain. The evaluation of effective EEG patterns is one of the crucial issues in the current research of BCI. Most of the traditional visual evoked paradigms only evoke one kind of EEG pattern for the subsequent feature classification. This study presents a new paradigm based on P300 and Steady-State Visual Evoked Potential (SSVEP) that involves event-related stimulation and frequency flashing stimulation. P300 and SSVEP patterns are evoked simultaneously to enhance the discriminability of features. Offline comparison is implemented among the proposed paradigm and the traditional P300 and SSVEP paradigms. The results show that the new paradigm evokes more significant P300 features while weaken SSVEP features a little without destroying the online feasibility of the BCI system. Therefore, the proposed paradigm can satisfy requirements from different subjects to enlarge the user of group.