Effect of the visual signal structure on Steady-State Visual Evoked Potentials detection

The detection of Steady-State Visual Evoked Potential (SSVEP) responses in the Electroencephalogram (EEG) is a current challenge in signal processing applied on Brain-Computer Interfaces (BCI). BCI based on SSVEP requires visual stimuli. When these stimuli are displayed on an LCD screen, the number of frequencies for flickering object on the screen is limited. We propose to extend the number of frequencies by composing different visual patterns. We evaluate the relation ship in the frequency domain between the visual stimuli and the recorded EEG signal. The signal detection across seven types of SSVEP responses is achieved by considering spatial filters based on the generalized Rayleigh quotient. The mean detection accuracy across three subjects is 89.58%.