A BCI speller based on SSVEP using high frequency stimuli design

We developed and studied a Steady-State Visual Evoked Potential (SSVEP) based BCI system using a high frequency visual stimuli (>25Hz) design for reducing visual fatigue. Existing SSVEP based BCI designs primarily use low frequency visual stimuli (<20Hz) for eliciting relatively higher SSVEP signal, while the low frequency stimuli can provocate photosensitivity epileptic seizure. On the other hand, high frequency stimuli are visually more comfortable and cause less visual fatigue and seizure. To detect the weak high frequency SSVEP signal, we used multi-channel EEG and introduced canonical correlation analysis to identify the elicited SSVEP frequency. We designed and built a 30-character SSVEP BCI speller system without calibration and evaluated the performance metrics including classification accuracy and subjective fatigue ratings, in both high-frequency and low frequency SSVEP modes. The result indicates that the high frequency stimuli system archieved higher classification accuracy (averaged 80% in the 30-class classification) comparable to that by the low frequency system. Moreover, no subjects rated the visual feeling as unacceptable or uncomfortable with the high frequency system.