Abstract
•A novel approach that maps EEG data onto an exactly periodic subspace is proposed.•EPSD employs the periodic characteristics of the SSVEP response to enhance its SNR.•EPSD exhibits robust performance compared to the other commonly used spatial filters.•The study confirms that EPSD is promising detection algorithm for SSVEP based BCI.
A novel exactly periodic spatial filtering (EPSD) approach, that provides a robust detection performance, is introduced and evaluated in this study. The proposed method exploits the temporal properties of the steady-state visual evoked potential (SSVEP) response to construct an orthogonal and exactly periodic mapping that enhances the signal to noise ratio (SNR) of the SSVEP embedded in the electroencephalogram (EEG) data. The subspace of interest is constructed via the elimination of the signals spaces that does not constitute the exact period of the target frequency. The EPSD is evaluated on a 35 subject benchmark dataset collected using a 40 target SSVEP BCI system. The results reveal that the proposed EPSD spatial filter significantly enhances the performance of target detection. Further statistical tests also confirm that the EPSD is a potential alternative to the existing SSVEP spatial filters for realizing an efficient BCI system.