In stroke rehabilitation, motor imagery based on a brain–computer interface is an extremely useful method to control an external device and utilize neurofeedback. Many studies have reported on the classification performance of motor imagery to decode individual fingers in stroke patients compared with healthy controls. However, classification performance for a given limb is still low because the differences between patients owing to brain reorganization after stroke are not considered. We used electroencephalography signals from eleven healthy controls and eleven stroke patients in this study. The subjects performed a finger tapping task during motor execution, and motor imagery was performed with the dominant and affected hands in the healthy controls and stroke patients, respectively. All fingers except for the thumb were classified using the proposed framework based on a voting module. The averaged four-class accuracies during motor execution and motor imagery were 53.16 ± 8.42% and 46.94 ± 5.99% for the healthy controls and 53.17 ± 14.09% and 66.00 ± 14.96% for the stroke patients, respectively. Importantly, the classification accuracies in the stroke patients were statistically higher than those in healthy controls during motor imagery. However, there was no significant difference between the accuracies of motor execution and motor imagery. These findings show the potential for high classification performance for a given limb during motor imagery in stroke patients. These results can also provide insights into controlling an external device on the basis of a brain–computer interface.

中文翻译：

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解码慢性中风患者在运动想象和执行过程中用受影响的手敲击手指


在中风康复中，基于脑机接口的运动想象是控制外部设备和利用神经反馈的极其有用的方法。许多研究报告了与健康对照者相比，中风患者的运动想象解码单个手指的分类性能。然而，给定肢体的分类性能仍然很低，因为没有考虑中风后大脑重组导致的患者之间的差异。在本研究中，我们使用了来自 11 名健康对照者和 11 名中风患者的脑电图信号。受试者在运动执行过程中执行手指敲击任务，并分别用健康对照组和中风患者的优势手和受影响的手进行运动想象。除拇指外的所有手指均使用基于投票模块的提议框架进行分类。健康对照组的运动执行和运动想象的平均四级准确度分别为 53.16 ± 8.42% 和 46.94 ± 5.99%，中风患者的平均四级准确度分别为 53.17 ± 14.09% 和 66.00 ± 14.96%。重要的是，在运动想象过程中，中风患者的分类准确度在统计上高于健康对照。然而，运动执行和运动想象的准确性之间没有显着差异。这些发现表明，中风患者的运动想象过程中给定肢体具有高分类性能的潜力。这些结果还可以为基于脑机接口控制外部设备提供见解。