In the aging society, the number of people suffering from vascular disorders is rapidly increasing and has become a social problem. The death rate due to stroke, which is the second leading cause of global mortality, has increased by 40% in the last two decades. Stroke can also cause paralysis. Of late, brain-computer interfaces (BCIs) have been garnering attention in the rehabilitation field as assistive technology. A BCI for the motor rehabilitation of patients with paralysis promotes neural plasticity, when subjects perform motor imagery (MI). Feedback, such as visual and proprioceptive, influences brain rhythm modulation to contribute to MI learning and motor function restoration. Also, virtual reality (VR) can provide powerful graphical options to enhance feedback visualization. This work aimed to improve immersive VR-BCI based on hand MI, using visual-electrotactile stimulation feedback instead of visual feedback. The MI tasks include grasping, flexion/extension, and their random combination. Moreover, the subjects answered a system perception questionnaire after the experiments. The proposed system was evaluated with twenty able-bodied subjects. Visual-electrotactile feedback improved the mean classification accuracy for the grasping (93.00%  3.50%) and flexion/extension (95.00%  5.27%) MI tasks. Additionally, the subjects achieved an acceptable mean classification accuracy (maximum of 86.5%  5.80%) for the random MI task, which required more concentration. The proprioceptive feedback maintained lower mean power spectral density in all channels and higher attention levels than those of visual feedback during the test trials for the grasping and flexion/extension MI tasks. Also, this feedback generated greater relative power in the -band for the premotor cortex, which indicated better MI preparation. Thus, electrotactile stimulation along with visual feedback enhanced the immersive VR-BCI classification accuracy by 5.5% and 4.5% for the grasping and flexion/extension MI tasks, respectively, retained the subject’s attention, and eased MI better than visual feedback alone.

中文翻译：

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视觉电动刺激反馈，基于手部运动图像改善沉浸式脑机接口

在老龄化社会中，患有血管疾病的人数正在迅速增加，并且已经成为社会问题。在过去的二十年中，中风所致的死亡率是全球死亡率的第二大原因，而卒中是全球死亡率的第二大原因。中风也会引起瘫痪。最近，脑机接口（BCI）作为辅助技术在康复领域受到了关注。当受试者执行运动成像（MI）时，用于瘫痪患者运动康复的BCI可以促进神经可塑性。视觉和本体感受等反馈会影响脑节律的调节，从而有助于MI学习和运动功能的恢复。此外，虚拟现实（VR）可以提供强大的图形选项，以增强反馈的可视化效果。这项工作旨在改善基于手部MI的沉浸式VR-BCI，使用视觉触觉刺激反馈而不是视觉反馈。MI的任务包括抓握，屈曲/伸展及其随机组合。此外，受试者在实验后回答了系统感知问卷。拟议的系统与二十个健全的主体进行了评估。视觉触觉反馈提高了抓取的平均分类精度（93.00％  3.50％）和屈伸（95.00％   5.27％）心梗任务。另外，受试者 对于随机MI任务达到了可接受的平均分类准确度（最高86.5％，  5.80％），这需要更多的注意力。在抓握和屈曲/伸展MI任务的测试试验中，本体感觉反馈在所有通道中均保持较低的平均功率谱密度，并比视觉反馈的注意力水平更高。同样，此反馈在以下方面产生了更大的相对功率：运动前皮层的条带，表明MI的准备更好。因此，触觉刺激和视觉反馈将沉浸式VR-BCI分类准确度分别提高到了抓握和屈伸MI任务的5.5％和4.5％，比单独的视觉反馈更能吸引受试者的注意力，并更好地缓解了MI。