Lambelet Charles, Mathis Melvin, Siegenthaler Marc, Held Jeremia P O, Woolley Daniel, Lambercy Olivier, Gassert Roger, Wenderoth Nicole
Neural Control of Movement Lab, Department of Health Sciences and Technology, Institute of Human Movement Sciences and Sport, ETH Zurich, Zürich, Switzerland.
CRPP Stroke, Department of Neurology, University of Zurich, Zürich, Switzerland.
Front Neurorobot. 2025 Sep 1;19:1562675. doi: 10.3389/fnbot.2025.1562675. eCollection 2025.
Wrist function impairment is common after stroke and heavily impacts the execution of daily tasks. Robotic therapy, and more specifically wearable exoskeletons, have the potential to boost training dose in context-relevant scenarios, promote voluntary effort through motor intent detection, and mitigate the effect of gravity. Portable exoskeletons are often non-backdrivable and it is challenging to make their control safe, reactive and stable. Admittance control is often used in this case, however, this type of control can become unstable when the supported biological joint stiffens. Variable admittance control adapts its parameters dynamically to allow free motion and stabilize the human-robot interaction.
In this study, we implemented a variable admittance control scheme on a one degree of freedom wearable wrist exoskeleton. The damping parameter of the admittance scheme is adjusted in real-time to cope with instabilities and varying wrist stiffness. In addition to the admittance control scheme, sEMG- and gravity-based controllers were implemented, characterized and optimized on ten healthy participants and tested on six stroke survivors.
The results show that (1) the variable admittance control scheme could stabilize the interaction but at the cost of a decrease in transparency, and (2) when coupled with the variable admittance controller the sEMG-based control enhanced wrist functionality of stroke survivors in the most extreme angular positions.
Our variable admittance control scheme with sEMG- and gravity-based support was most beneficial for patients with higher levels of impairment by improving range of motion and promoting voluntary effort. Future work could combine both controllers to customize and fine tune the stability of the support to a wider range of impairment levels and types.
中风后手腕功能受损很常见，严重影响日常任务的执行。机器人疗法，尤其是可穿戴外骨骼，有可能在与实际情境相关的场景中增加训练剂量，通过运动意图检测促进自主努力，并减轻重力影响。便携式外骨骼通常不可反向驱动，要使其控制安全、具有响应性和稳定性具有挑战性。在这种情况下常采用导纳控制，然而，当被支撑的生物关节变硬时，这种控制类型可能会变得不稳定。可变导纳控制会动态调整其参数，以允许自由运动并稳定人机交互。
在本研究中，我们在一个自由度的可穿戴手腕外骨骼上实现了一种可变导纳控制方案。实时调整导纳方案的阻尼参数，以应对不稳定性和手腕刚度的变化。除了导纳控制方案外，还实施了基于表面肌电图（sEMG）和重力的控制器，在10名健康参与者身上对其进行了表征和优化，并在6名中风幸存者身上进行了测试。
结果表明：（1）可变导纳控制方案能够稳定交互，但代价是透明度降低；（2）当与可变导纳控制器结合时，基于sEMG的控制增强了中风幸存者在最极端角度位置的手腕功能。
我们基于sEMG和重力支持的可变导纳控制方案通过改善运动范围和促进自主努力，对损伤程度较高的患者最为有益。未来的工作可以将两种控制器结合起来，针对更广泛的损伤水平和类型定制并微调支持的稳定性。
