User-Specific Channel Selection Method to Improve SSVEP BCI Decoding Robustness against Variable Inter-Stimulus Distance

Aravind Ravi1, Sarah Pearce1, Xin Zhang, Ning Jiang1

  • 1University of Waterloo

Details

16:30 - 18:30 | Thu 21 Mar | Grand Ballroom B | ThPO.71

Session: Poster Session I

Abstract

Steady-state visual evoked potentials (SSVEP) are responses elicited when a user is presented with a repetitive visual stimulus. Change in stimuli proximity has been shown to have an influence on the performance of SSVEP-based BCI, where the inter-stimulus distance has a positive correlation with the overall performance. This limits the flexibility in stimulus design by imposing a constraint on the acceptable inter-stimulus distance, consequently limiting the range of applicability for SSVEP-based BCIs in real-world applications. Another limitation that needs to be addressed is the required number of EEG channels. In this study, we investigated these two challenges. A process of selecting optimal user-specific channel set was proposed. We demonstrated that the user-specific channel set is more robust against variable inter-stimulus distance. A significant improvement in accuracy (p=10-3) of 5% and a reduction in variation (p=10-3) of 55% was achieved on average when compared to the performance using the classic 3-channel set (O1, O2, Oz) and 6-channel set (O1, O2, Oz, PO3, PO4, POz).