The extension of multivariate synchronization index method for SSVEP-based BCI

Abstract

Multichannel frequency detection methods for SSVEP-based BCI have received increasing interest in recent years. Among the alternative methods, multivariate synchronization index (MSI) is a potential one to achieve robust performance for SSVEP-based BCI. This study further presents an extension to MSI (termed as EMSI) for frequency recognition, which leverage the method of time delay embedding. The new method incorporates the first-order time delayed version of the EEG data during calculation the synchronization index. The effectiveness of the proposed method is validated by comparing it with the standard MSI on the actual SSVEP datasets collected from eleven subjects. The experimental results indicate that the EMSI significantly outperforms the MSI at four time windows. It suggests that the EMSI is a promising methodology for frequency recognition and could further improve the performance of SSVEP-based BCI system.