Sensorimotor rhythm (SMR)-based brain–computer interface (BCI) controlled Functional Electrical Stimulation (FES) has gained importance in recent years for the rehabilitation of motor deficits. However, there still remain many research questions to be addressed, such as unstructured Motor Imagery (MI) training procedures; a lack of methods to classify different MI tasks in a single hand, such as grasping and opening; and difficulty in decoding voluntary MI-evoked SMRs compared to FES-driven passive-movement-evoked SMRs. To address these issues, a study that is composed of two phases was conducted to develop and validate an SMR-based BCI-FES system with 2-class MI tasks in a single hand (Phase 1), and investigate the feasibility of the system with stroke and traumatic brain injury (TBI) patients (Phase 2). The results of Phase 1 showed that the accuracy of classifying 2-class MIs (approximately 71.25%) was significantly higher than the true chance level, while that of distinguishing voluntary and passive SMRs was not. In Phase 2, where the patients performed goal-oriented tasks in a semi-asynchronous mode, the effects of the FES existence type and adaptive learning on task performance were evaluated. The results showed that adaptive learning significantly increased the accuracy, and the accuracy after applying adaptive learning under the No-FES condition (61.9%) was significantly higher than the true chance level. The outcomes of the present research would provide insight into SMR-based BCI-controlled FES systems that can connect those with motor disabilities (e.g., stroke and TBI patients) to other people by greatly improving their quality of life. Recommendations for future work with a larger sample size and kinesthetic MI were also presented.

中文翻译：

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由运动图像脑机接口控制的功能性电刺激康复。

近年来，基于感觉运动节律（SMR）的脑机接口（BCI）控制的功能性电刺激（FES）对于康复运动障碍已变得越来越重要。但是，仍然有许多研究问题需要解决，例如非结构化的汽车图像（MI）培训程序；缺乏一种可以一手将不同MI任务分类的方法，例如抓握和打开；与FES驱动的被动运动诱发SMR相比，解码自愿MI诱发SMR的难度更大。为了解决这些问题，进行了一个由两个阶段组成的研究，以开发和验证单手操作具有2类MI任务的基于SMR的BCI-FES系统（阶段1），并研究该系统的可行性。中风和脑外伤（TBI）患者（第2阶段）。第1阶段的结果表明，对2类MI进行分类的准确性（约71.25％）显着高于真实机会水平，而对区分自愿性和被动SMR的准确性则不高。在阶段2中，患者以半异步模式执行了目标导向的任务，评估了FES存在类型和适应性学习对任务绩效的影响。结果表明，自适应学习显着提高了准确性，并且在No-FES条件下应用自适应学习后的准确性（61.9％）明显高于真实机会水平。本研究的结果将提供对基于SMR的BCI控制的FES系统的见解，该系统可以通过极大地改善他们的生活质量，将运动障碍者（例如中风和TBI患者）与其他人联系起来。