An improved model for the use of facial stimulation in hybrid SSVEP+P300 brain-computer interfaces

Abstract

Purpose: This research proposes a hybrid BCI that integrates Steady State Visual Evoked Potentials (SSVEP) and Event Related Potentials (P300) simultaneously. We included human facial structure into a visual stimulus to elicit stronger cortical responses in a hybrid SSVEP+P300 BCI. We also discussed the possibilities of triggering one potential with facial stimuli and another with non-facial stimuli. Methods: To elicit SSVEP and P300 responses, non-face and neutral-face stimulus paradigms are presented. We also tested the neutral-face and flicker paradigm, in which non-face stimuli would elicit SSVEP and neutral-face stimuli would elicit P300. Results: The results showed that the latter paradigm evoked more robust cortical potentials, leading to enhanced system accuracy and ITR. The neutral-face and flicker paradigm has an average accuracy of 91.62%, with an average system communication rate of 22.04 bits per second. Conclusions: The author talked about visual stimulus characteristics that might change the way that multiple brain potentials are activated simultaneously and how that affects the individual potentials.