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协调的人机外骨骼运动源于对虚拟能量的调节。

Coordinated human-exoskeleton locomotion emerges from regulating virtual energy.

作者信息

Nasiri Rezvan, Dinovitzer Hannah, Manohara Nirosh, Arami Arash

机构信息

Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON, Canada.

Toronto Rehabilitation Institute (KITE), University Health Network, Toronto, ON, Canada.

出版信息

PLoS One. 2025 Jan 22;20(1):e0292334. doi: 10.1371/journal.pone.0292334. eCollection 2025.

DOI:10.1371/journal.pone.0292334
PMID:39841647
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11753675/
Abstract

Lower-limb exoskeletons have demonstrated great potential for gait rehabilitation in individuals with motor impairments; however, maintaining human-exoskeleton coordination remains a challenge. The coordination problem, referred to as any mismatch or asynchrony between the user's intended trajectories and exoskeleton desired trajectories, leads to sub-optimal gait performance, particularly for individuals with residual motor ability. Here, we investigate the virtual energy regulator (VER)'s ability to generate coordinated locomotion in lower limb exoskeleton. Contribution: (1) In this paper, we experimented VER on a group of nine healthy individuals at different speeds (0.6m/s - 0.85m/s) to study the resultant gait coordination and naturalness on a large group of users. (2) The resultant assisted gait is compared to the natural and passive (zero-torque exoskeleton) walking conditions in terms of muscle activities, kinematic, spatiotemporal and kinetic measures, and questionnaires. (3) Moreover, we presented the VER's convergence proof considering the user contribution to the gait and introduced a metric to measure the user's contribution to gait. (4) We also compared VER performance with the phase-based path controller in terms of muscle effort reduction and joint kinematics using three able-bodied individuals. Results: (1) The results from the VER demonstrate the emergence of natural, coordinated locomotion, resulting in an average muscle effort reduction ranging from 13.1% to 17.7% at different speeds compared to passive walking. (2) The results from VER revealed improvements in all indicators towards natural gait when compared to walking with a zero-torque exoskeleton, for instance, an enhancement in average knee extension ranging from 3.9 to 4.1 degrees. All indicators suggest that the VER preserves natural gait variability and user engagement in locomotion control. (3) Using VER also yields in 13.9%, 15.1%, and 7.0% average muscle effort reduction when compared to the phase-based path controller. (4) Finally, using our proposed metric, we demonstrated that the resultant locomotion limit cycle is a linear combination of human-intended limit cycle and the VER's limit cycle. These findings may have implications for understanding how the central nervous system controls our locomotion.

摘要

下肢外骨骼已在运动功能受损个体的步态康复中展现出巨大潜力;然而,维持人与外骨骼的协调性仍是一项挑战。这种协调问题,即用户预期轨迹与外骨骼期望轨迹之间的任何不匹配或不同步,会导致步态表现欠佳,尤其是对于仍有残余运动能力的个体。在此,我们研究虚拟能量调节器(VER)在下肢外骨骼中产生协调运动的能力。贡献:(1)在本文中,我们让一组九名健康个体以不同速度(0.6米/秒 - 0.85米/秒)对VER进行实验,以研究大量用户群体所产生的步态协调性和自然度。(2)将所产生的辅助步态在肌肉活动、运动学、时空和动力学指标以及问卷调查方面与自然和被动(零扭矩外骨骼)行走条件进行比较。(3)此外,我们给出了考虑用户对步态贡献的VER收敛证明,并引入了一种衡量用户对步态贡献的指标。(4)我们还使用三名身体健全的个体,在肌肉用力减少和关节运动学方面将VER性能与基于相位的路径控制器进行比较。结果:(1)VER的结果表明出现了自然、协调的运动,与被动行走相比,在不同速度下平均肌肉用力减少了13.1%至17.7%。(2)与零扭矩外骨骼行走相比,VER的结果显示所有指标都朝着自然步态有所改善,例如,平均膝关节伸展增加了3.9至4.1度。所有指标表明VER保留了自然步态变异性以及用户在运动控制中的参与度。(3)与基于相位的路径控制器相比,使用VER还能使平均肌肉用力分别减少13.9%、15.1%和7.0%。(4)最后,使用我们提出的指标,我们证明所产生的运动极限环是人类预期极限环和VER极限环的线性组合。这些发现可能对理解中枢神经系统如何控制我们的运动具有启示意义。

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本文引用的文献

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A Unified Gait Phase Estimation and Control of Exoskeleton using Virtual Energy Regulator (VER).使用虚拟能量调节器 (VER) 对下肢外骨骼进行统一的步态相位估计和控制。
IEEE Int Conf Rehabil Robot. 2022 Jul;2022:1-6. doi: 10.1109/ICORR55369.2022.9896572.
2
Ultra-Robust Real-Time Estimation of Gait Phase.超稳健实时步态相位估计
IEEE Trans Neural Syst Rehabil Eng. 2022;30:2793-2801. doi: 10.1109/TNSRE.2022.3207919. Epub 2022 Oct 10.
3
A neuromuscular model of human locomotion combines spinal reflex circuits with voluntary movements.
一种人类运动的神经肌肉模型将脊髓反射回路与自主运动相结合。
Sci Rep. 2022 May 17;12(1):8189. doi: 10.1038/s41598-022-11102-1.
4
Real-Time Gait Phase Estimation for Robotic Hip Exoskeleton Control During Multimodal Locomotion.多模态运动期间用于机器人髋关节外骨骼控制的实时步态阶段估计
IEEE Robot Autom Lett. 2021 Apr;6(2):3491-3497. doi: 10.1109/lra.2021.3062562. Epub 2021 Feb 26.
5
Real-time gait metric estimation for everyday gait training with wearable devices in people poststroke.使用可穿戴设备对中风后患者进行日常步态训练的实时步态指标估计
Wearable Technol. 2021;2. doi: 10.1017/wtc.2020.11. Epub 2021 Mar 25.
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Assistance magnitude versus metabolic cost reductions for a tethered multiarticular soft exosuit.多关节软体外骨骼的系绳辅助幅度与代谢成本降低。
Sci Robot. 2017 Jan 18;2(2). doi: 10.1126/scirobotics.aah4416.
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Human-in-the-loop optimization of hip assistance with a soft exosuit during walking.人在环优化软外骨骼辅助下的髋关节在行走中的作用。
Sci Robot. 2018 Feb 28;3(15). doi: 10.1126/scirobotics.aar5438.
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A Clustering-Based Approach to Identify Joint Impedance During Walking.基于聚类的方法识别行走过程中的关节阻抗。
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