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Musculoskeletal modeling and humanoid control of robots based on human gait data

The emergence of exoskeleton rehabilitation training has brought good news to patients with limb dysfunction. Rehabilitation robots are used to assist patients with limb rehabilitation training and play an essential role in promoting the patient’s sports function with limb disease restoring to daily...

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Autores principales: Yu, Jun, Zhang, Shuaishuai, Wang, Aihui, Li, Wei, Song, Lulu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8372000/
https://www.ncbi.nlm.nih.gov/pubmed/34458572
http://dx.doi.org/10.7717/peerj-cs.657
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author Yu, Jun
Zhang, Shuaishuai
Wang, Aihui
Li, Wei
Song, Lulu
author_facet Yu, Jun
Zhang, Shuaishuai
Wang, Aihui
Li, Wei
Song, Lulu
author_sort Yu, Jun
collection PubMed
description The emergence of exoskeleton rehabilitation training has brought good news to patients with limb dysfunction. Rehabilitation robots are used to assist patients with limb rehabilitation training and play an essential role in promoting the patient’s sports function with limb disease restoring to daily life. In order to improve the rehabilitation treatment, various studies based on human dynamics and motion mechanisms are still being conducted to create more effective rehabilitation training. In this paper, considering the human biological musculoskeletal dynamics model, a humanoid control of robots based on human gait data collected from normal human gait movements with OpenSim is investigated. First, the establishment of the musculoskeletal model in OpenSim, inverse kinematics, and inverse dynamics are introduced. Second, accurate human-like motion analysis on the three-dimensional motion data obtained in these processes is discussed. Finally, a classic PD control method combined with the characteristics of the human motion mechanism is proposed. The method takes the angle values calculated by the inverse kinematics of the musculoskeletal model as a benchmark, then uses MATLAB to verify the simulation of the lower extremity exoskeleton robot. The simulation results show that the flexibility and followability of the method improves the safety and effectiveness of the lower limb rehabilitation exoskeleton robot for rehabilitation training. The value of this paper is also to provide theoretical and data support for the anthropomorphic control of the rehabilitation exoskeleton robot in the future.
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spelling pubmed-83720002021-08-26 Musculoskeletal modeling and humanoid control of robots based on human gait data Yu, Jun Zhang, Shuaishuai Wang, Aihui Li, Wei Song, Lulu PeerJ Comput Sci Human-Computer Interaction The emergence of exoskeleton rehabilitation training has brought good news to patients with limb dysfunction. Rehabilitation robots are used to assist patients with limb rehabilitation training and play an essential role in promoting the patient’s sports function with limb disease restoring to daily life. In order to improve the rehabilitation treatment, various studies based on human dynamics and motion mechanisms are still being conducted to create more effective rehabilitation training. In this paper, considering the human biological musculoskeletal dynamics model, a humanoid control of robots based on human gait data collected from normal human gait movements with OpenSim is investigated. First, the establishment of the musculoskeletal model in OpenSim, inverse kinematics, and inverse dynamics are introduced. Second, accurate human-like motion analysis on the three-dimensional motion data obtained in these processes is discussed. Finally, a classic PD control method combined with the characteristics of the human motion mechanism is proposed. The method takes the angle values calculated by the inverse kinematics of the musculoskeletal model as a benchmark, then uses MATLAB to verify the simulation of the lower extremity exoskeleton robot. The simulation results show that the flexibility and followability of the method improves the safety and effectiveness of the lower limb rehabilitation exoskeleton robot for rehabilitation training. The value of this paper is also to provide theoretical and data support for the anthropomorphic control of the rehabilitation exoskeleton robot in the future. PeerJ Inc. 2021-08-09 /pmc/articles/PMC8372000/ /pubmed/34458572 http://dx.doi.org/10.7717/peerj-cs.657 Text en ©2021 Yu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Human-Computer Interaction
Yu, Jun
Zhang, Shuaishuai
Wang, Aihui
Li, Wei
Song, Lulu
Musculoskeletal modeling and humanoid control of robots based on human gait data
title Musculoskeletal modeling and humanoid control of robots based on human gait data
title_full Musculoskeletal modeling and humanoid control of robots based on human gait data
title_fullStr Musculoskeletal modeling and humanoid control of robots based on human gait data
title_full_unstemmed Musculoskeletal modeling and humanoid control of robots based on human gait data
title_short Musculoskeletal modeling and humanoid control of robots based on human gait data
title_sort musculoskeletal modeling and humanoid control of robots based on human gait data
topic Human-Computer Interaction
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8372000/
https://www.ncbi.nlm.nih.gov/pubmed/34458572
http://dx.doi.org/10.7717/peerj-cs.657
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