Performance estimation of a cooperative brain-computer interface based on the detection of steady-state visual evoked potentials

To be better suited for the expectations of healthy people, new brain-computer interface (BCI) paradigms should be proposed. To tackle this problem, we investigate the emerging field of cooperative BCIs, which involves several users in a single BCI system. Because combining trials over time improves performance, combining trials across subjects can significantly improve performance compared to a single user. However, cooperative BCIs can only be used in particular settings, and new paradigms must be proposed to efficiently use this approach. To show the advantages of a cooperative BCI based on steady-state visual evoked potentials (SSVEP), we evaluate and compare the performance of combining decisions across subjects, and over time. By considering a reliable brain response such as SSVEP responses, this study represents a first evolution for the combination, and the choice of the combination method for creating a cooperative SSVEP based BCI. The results suggest that six people would be enough to obtain a perfect accuracy within one second of EEG signal.