A Hybrid Brain Computer Interface Driven by Motor Imagery of Right Hand Versus Right Forearm

Abstract

Motor imagery (MI) based brain-computer interface (BCI) is an important technology for the rehabilitation of motor injured. Although it has been developing for a long time, the recognition of MI location with high spatial resolution still faces great challenges. In this paper, we explored the performance of hybrid paradigm used to recognize MI task of right hand versus right forearm. Seven subjects participated in this study, who were required to imagine clenching hand and lifting forearm under MI and hybrid paradigm respectively. MI paradigm asked subjects to only perform the motor imagery tasks, while in the hybrid paradigm, subjects were given electrical stimulation during imagination. Hybrid paradigm requires subjects perform the same tasks in the same way as MI paradigm and not to pay attention to electrical stimulation deliberately. The time-frequency analysis showed that both the ERD and steady-state somatosensory evoked potential (SSSEP) features could be induced during the hybrid paradigm. Classification results show that the mean classification accuracy of the hybrid paradigm reaches 83%, which is significantly higher than the MI paradigm, with an increase around 14%. This indicates that the hybrid paradigm proposed in this paper can effectively improve the spatial resolution of MI location, which can promote MI-BCI system to complete the reach-andgrasp action naturally.