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Modeling and Simulation of an Unpowered Lower Extremity Exoskeleton Based on Gait Energy

机译:基于步态能量的无动力下肢外骨骼建模与仿真

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摘要

Aiming at the problem of how to store/release gait energy with high efficiency for the conventional unpowered lower extremity exoskeletons, an unpowered lower-limb exoskeleton is proposed. In the current study, the human motion model is established, and the change rule and recovery/utilization mechanism of gait energy are illustrated. The stiffness and metabolic cost of relevant muscles in lower extremity joints are obtained based on OpenSim software. The results show that stiffness of muscle is increased when muscle concentric contraction generates positive work, but it is reverse when muscle eccentric contraction generates negative work. Besides, metabolic cost of the soleus, gastrocnemius, and tibialis anterior decreased about 31.5, 34.7, and 40, respectively. Metabolic cost of the rectus femoris, tensor fascia lata, and sartorius decreased about 36.3, 7, and 5, respectively, and the total metabolic cost of body decreased about 15.5, under the exoskeleton conditions. The results of this study can provide a theoretical basis for the optimal design of unpowered lower extremity exoskeleton.
机译:针对传统无动力下肢外骨骼如何高效储存/释放步态能量的问题,该文提出一种无动力下肢外骨骼。本研究建立了人体运动模型,阐述了步态能量的变化规律和回收利用机制。基于OpenSim软件获取下肢关节相关肌肉的僵硬和代谢成本。结果表明,当肌肉向心收缩产生正功时,肌肉僵硬增加,但当肌肉离心收缩产生负功时,肌肉僵硬相反。此外,比目鱼肌、腓肠肌和胫骨前肌的代谢成本分别下降了约31.5%、34.7%和40%。在外骨骼条件下,股直肌、阔筋膜张肌和缝匠体的代谢成本分别下降了约36.3%、7%和5%,机体总代谢成本下降了约15.5%。研究结果可为无动力下肢外骨骼的优化设计提供理论依据。

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    Chinese Acad Sci, Shenzhen Inst Adv Technol SIAT, CAS Key Lab Human Machine Intelligence Synergy Sy, Shenzhen 518055, Peoples R China|Chinese Acad Sci, Res Ctr Neural Engn, SIAT, Shenzhen 518055, Peoples R China|Hubei Polytech Univ, Sch Mech & Elect Engn,;

    Beijing Inst Technol, Intelligent Robot Inst, Beijing 100081, Peoples R China;

    Handan Univ, Handan 056001, Peoples R ChinaChinese Acad Sci, Shenzhen Inst Adv Technol SIAT, CAS Key Lab Human Machine Intelligence Synergy Sy, Shenzhen 518055, Peoples R China|Chinese Acad Sci, Res Ctr Neural Engn, SIAT, Shenzhen 518055, Peoples R China;

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