An asynchronous SSVEP-BCI based on variance statistics of Multivariate synchronization index

Abstract

In this paper, a threshold calculated from simple variance statistics of Multivariate synchronization index (MSI) was proposed to construct an asynchronous Brain-computer interface (BCI) paradigm based on steady-state visual evoked potential (SSVEP). Compared with simplified Linear discriminant analysis (LDA) classification, the threshold helped system judge control/idle state more effectively and robust. And it was used in control a robot which with obstacle avoidance, helping to reduce the mental burden with the shared control strategy. To some extent, it can be explained, the use of simple methods can also achieve better control in human-computer interface and integration.