PROPORTIONAL ELECTROMYOGRAPHIC CONTROL OF A BIONIC ARM IN A PARTICIPANT WITH CHRONIC HEMIPARESIS, MUSCLE SPASTICITY, AND IMPAIRED RANGE OF MOTION: A CASE STUDY.

Caleb J Thomson, Jacob A George
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Abstract

The long-term goal of this research is to restore intuitive and proportional motor control to stroke patients with an assistive exoskeleton. Stroke is the leading cause of disability in the United States, with 80% of stroke-related disability coming in the form of hemiparesis, presented as weakness or paresis on half of the body. Current electromyographic-(EMG)-controlled assistive exoskeletons do not allow for fine force regulation. That is, current control strategies provide only binary, all-or-nothing, control based on a linear threshold of EMG activity. In this case study with one hemiparetic stroke patient, we show that state-of-the-art EMG control algorithms can provide proportional control of a bionic arm despite weak and spastic muscle activity. The participant completed a virtual target-touching exercise with an EMG-controlled bionic arm by attempting to grasp (close) or extend (open) their hand. The participant completed the task under two conditions, with EMG from their paretic arm and with EMG from their healthy, contralateral arm. For grasping, there was no statistical difference in task performance for the paretic and healthy arms, but there was a significant decrease in the EMG signal-to-noise ratio for the paretic arm. For extension, there was a significant decrease in both task performance and EMG signal-to-noise ratio for the paretic arm. Despite these differences, the participant was still able to complete the target-touching task with the paretic arm. These preliminary results show it is possible, for at least some patients, to provide proportional control of assistive devices using weak and spastic EMG. Importantly, information regulating fine force output is still present in EMG despite a visually immobile arm due to hemiparesis. Future work will validate these findings with additional stroke patients with varying presentations of hemiparesis and move into controlling upper-limb exoskeletons.

慢性偏瘫、肌肉痉挛和活动范围受损患者的仿生手臂的比例肌电图控制:一个案例研究。
这项研究的长期目标是通过辅助外骨骼恢复中风患者的直觉和比例运动控制。在美国,中风是致残的主要原因,80%与中风相关的致残以偏瘫的形式出现,表现为身体的一半无力或麻痹。目前肌电图(EMG)控制的辅助外骨骼不允许精细的力调节。也就是说,当前的控制策略仅提供基于肌电活动线性阈值的二元、全有或全无的控制。在一个偏瘫中风患者的案例研究中,我们展示了最先进的肌电控制算法可以在肌肉虚弱和痉挛的情况下提供仿生手臂的比例控制。参与者用肌电控制的仿生手臂完成了一个虚拟的触碰目标练习,试图抓住(闭合)或伸出(张开)他们的手。参与者在两种情况下完成了任务,一种是使用双亲手臂的肌电图,另一种是使用健康的对侧手臂的肌电图。在抓握方面,亲父母组和健康组的任务表现无统计学差异,但亲父母组的肌电信号信噪比显著降低。此外,双亲臂的任务表现和肌电信号信噪比都有显著下降。尽管存在这些差异,参与者仍然能够用父母的手臂完成触碰目标的任务。这些初步结果表明,至少对一些患者来说,利用弱肌和痉挛肌电图来提供辅助装置的比例控制是可能的。重要的是,尽管由于偏瘫导致手臂视觉无法移动,但肌电图中仍然存在调节精细力输出的信息。未来的工作将在更多具有不同偏瘫表现的中风患者中验证这些发现,并进入控制上肢外骨骼的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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