Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.
Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 90089, USA.
Sensors (Basel). 2020 Jul 4;20(13):3754. doi: 10.3390/s20133754.
Severe impairment of limb movement after stroke can be challenging to address in the chronic stage of stroke (e.g., greater than 6 months post stroke). Recent evidence suggests that physical therapy can still promote meaningful recovery after this stage, but the required high amount of therapy is difficult to deliver within the scope of standard clinical practice. Digital gaming technologies are now being combined with brain-computer interfaces to motivate engaging and frequent exercise and promote neural recovery. However, the complexity and expense of acquiring brain signals has held back widespread utilization of these rehabilitation systems. Furthermore, for people that have residual muscle activity, electromyography (EMG) might be a simpler and equally effective alternative. In this pilot study, we evaluate the feasibility and efficacy of an EMG-based variant of our REINVENT virtual reality (VR) neurofeedback rehabilitation system to increase volitional muscle activity while reducing unintended co-contractions. We recruited four participants in the chronic stage of stroke recovery, all with severely restricted active wrist movement. They completed seven 1-hour training sessions during which our head-mounted VR system reinforced activation of the wrist extensor muscles without flexor activation. Before and after training, participants underwent a battery of clinical and neuromuscular assessments. We found that training improved scores on standardized clinical assessments, equivalent to those previously reported for brain-computer interfaces. Additionally, training may have induced changes in corticospinal communication, as indexed by an increase in 12-30 Hz corticomuscular coherence and by an improved ability to maintain a constant level of wrist muscle activity. Our data support the feasibility of using muscle-computer interfaces in severe chronic stroke, as well as their potential to promote functional recovery and trigger neural plasticity.
中风后肢体运动严重受损在中风慢性期（例如，中风后大于 6 个月）较难解决。最近的证据表明，物理疗法在这个阶段之后仍然可以促进有意义的恢复，但所需的大量治疗在标准临床实践范围内难以实现。数字游戏技术现在正与脑机接口相结合，以激励参与和频繁的运动，促进神经恢复。然而，获取脑信号的复杂性和费用阻碍了这些康复系统的广泛应用。此外，对于仍有肌肉活动的人来说，肌电图（EMG）可能是一种更简单且同样有效的替代方法。在这项初步研究中，我们评估了基于 EMG 的我们的 REINVENT 虚拟现实（VR）神经反馈康复系统的变体增加意愿性肌肉活动同时减少非意愿性协同收缩的可行性和效果。我们招募了四名处于中风恢复慢性期的参与者，他们的主动腕部运动都受到严重限制。他们完成了七个 1 小时的训练课程，在此期间，我们的头戴式 VR 系统强化了腕伸肌的激活，而没有激活屈肌。在训练前后，参与者接受了一系列临床和神经肌肉评估。我们发现，训练提高了标准化临床评估的分数，与之前报道的脑机接口相当。此外，训练可能诱导了皮质脊髓间通讯的变化，表现为 12-30Hz 皮质肌相干性增加，以及维持腕部肌肉活动恒定水平的能力提高。我们的数据支持在严重慢性中风中使用肌肉计算机接口的可行性，以及它们促进功能恢复和引发神经可塑性的潜力。
