Robot-Assisted Rehabilitation System Based on SSVEP Brain-Computer Interface for Upper Extremity

Abstract

Traditional rehabilitation therapies have limited effect on the motor recovery for a tetraplegia patient. Brain-computer interface (BCI) systems allow patients to send commands or intents to control external devices without depending on the normal way of peripheral nerves and muscles. And hence it can provide an alternative control and communication method with a potential to replace, restore, even reinforce lost movement ability for individuals with neurological damages. In the study, we proposed a robot-assisted rehabilitation system for upper extremity based on non-invasive electroencephalogram (EEG) BCI, which enables the injured upper extremity to achieve motor function. Six participants conducted three speed modes of movement with a BCI-controlled robot. The steady-state visual evoked potentials (SSVEPs) was adopted to establish the BCI system. Experimental results of the healthy participants were analyzed to indicate the feasibility of a BCI-driven robot-assisted rehabilitation system, with an average accuracy of about 80 %. This study gives a preliminary evidence that the integrated robot-assisted rehabilitation system combined with SSVEP-based BCI will make future rehabilitation therapy more effective.