Yi Weibo, Qiu Shuang, Wang Kun, Qi Hongzhi, Zhao Xin, He Feng, Zhou Peng, Yang Jiajia, Ming Dong
Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, People's Republic of China. Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin, People's Republic of China.
J Neural Eng. 2017 Apr;14(2):026002. doi: 10.1088/1741-2552/aa5559. Epub 2016 Dec 22.
We proposed a novel simultaneous hybrid brain-computer interface (BCI) by incorporating electrical stimulation into a motor imagery (MI) based BCI system. The goal of this study was to enhance the overall performance of an MI-based BCI. In addition, the brain oscillatory pattern in the hybrid task was also investigated.
64-channel electroencephalographic (EEG) data were recorded during MI, selective attention (SA) and hybrid tasks in fourteen healthy subjects. In the hybrid task, subjects performed MI with electrical stimulation which was applied to bilateral median nerve on wrists simultaneously.
The hybrid task clearly presented additional steady-state somatosensory evoked potential (SSSEP) induced by electrical stimulation with MI-induced event-related desynchronization (ERD). By combining ERD and SSSEP features, the performance in the hybrid task was significantly better than in both MI and SA tasks, achieving a ~14% improvement in total relative to the MI task alone and reaching ~89% in mean classification accuracy. On the contrary, there was no significant enhancement obtained in performance while separate ERD feature was utilized in the hybrid task. In terms of the hybrid task, the performance using combined feature was significantly better than using separate ERD or SSSEP feature.
The results in this work validate the feasibility of our proposed approach to form a novel MI-SSSEP hybrid BCI outperforming a conventional MI-based BCI through combing MI with electrical stimulation.
我们通过将电刺激纳入基于运动想象(MI)的脑机接口(BCI)系统,提出了一种新型的同步混合脑机接口。本研究的目的是提高基于MI的BCI的整体性能。此外,还研究了混合任务中的脑振荡模式。
在14名健康受试者进行运动想象、选择性注意(SA)和混合任务期间,记录64通道脑电图(EEG)数据。在混合任务中,受试者在运动想象时接受电刺激,电刺激同时施加于双侧手腕的正中神经。
混合任务清晰地呈现了由电刺激诱发的额外稳态体感诱发电位(SSSEP)以及运动想象诱发的事件相关去同步化(ERD)。通过结合ERD和SSSEP特征,混合任务的性能显著优于运动想象和选择性注意任务,相对于单独的运动想象任务,总体提升了约14%,平均分类准确率达到约89%。相反,在混合任务中单独使用ERD特征时,性能没有显著提高。就混合任务而言,使用组合特征的性能明显优于单独使用ERD或SSSEP特征。
本研究结果验证了我们所提出方法的可行性,即通过将运动想象与电刺激相结合,形成一种新型的运动想象-稳态体感诱发电位混合脑机接口,其性能优于传统的基于运动想象的脑机接口。