Ren Shixin, Wang Weiqun, Hou Zeng-Guang, Liang Xu, Wang Jiaxing, Shi Weiguo
IEEE Trans Neural Syst Rehabil Eng. 2020 Aug;28(8):1846-1855. doi: 10.1109/TNSRE.2020.3001990. Epub 2020 Jun 12.
Motor imagery based brain-computer interface (MI-BCI) has been studied for improvement of patients' motor function in neurorehabilitation and motor assistance. However, the difficulties in performing imagery tasks limit its application. To overcome the limitation, an enhanced MI-BCI based on functional electrical stimulation (FES) and virtual reality (VR) is proposed in this study. On one hand, the FES is used to stimulate the subjects' lower limbs before their imagination to make them experience the muscles' contraction and improve their attention on the lower limbs, by which it is supposed that the subjects' motor imagery (MI) abilities can be enhanced. On the other hand, a ball-kicking movement scenario from the first-person perspective is designed to provide visual guidance for performing MI tasks. The combination of FES and VR can be used to reduce the difficulties in performing MI tasks and improve classification accuracy. Finally, the comparison experiments were conducted on twelve healthy subjects to validate the performance of the enhanced MI-BCI. The results show that the classification performance can be improved significantly by using the proposed MI-BCI in terms of the classification accuracy (ACC), the area under the curve (AUC) and the F1 score (paired t-test, ).
基于运动想象的脑机接口（MI-BCI）已被研究用于改善神经康复和运动辅助中患者的运动功能。然而，执行想象任务的困难限制了其应用。为克服这一限制，本研究提出了一种基于功能性电刺激（FES）和虚拟现实（VR）的增强型MI-BCI。一方面，FES用于在受试者想象之前刺激其下肢，使其体验肌肉收缩并提高对下肢的注意力，据此推测可以增强受试者的运动想象（MI）能力。另一方面，设计了一个从第一人称视角的踢球运动场景，为执行MI任务提供视觉指导。FES和VR的结合可用于减少执行MI任务的困难并提高分类准确率。最后，对12名健康受试者进行了对比实验，以验证增强型MI-BCI的性能。结果表明，使用所提出的MI-BCI在分类准确率（ACC）、曲线下面积（AUC）和F1分数方面，分类性能可显著提高（配对t检验， ）。
