A hybrid paradigm based on steady-state visual evoked potentials and motor imagery

Abstract

Hybrid brain-computer interfaces have the advantage of higher accuracy and more commands. This paper presents a hybrid brain-computer interface (BCI) paradigm based on steady-state visual evoked potentials (SSVEP) and motor imagery(MI).The subject started the first SSVEP task, and 2 seconds later the subject was asked to perform the second MI task and keep both tasks running simultaneously. The moment when the second task was joined was defined as the moment of switching. The performance of SSVEP was improved after the switch. Five healthy subjects participated in the experiment. The experimental results demonstrated the improvement of SSVEP classification accuracy, in addition to demonstrating that the performance of most of the subject MI was not affected in the paradigm.