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Nondestructive Estimation of Muscle Contributions to STS Training with Different Loadings Based on Wearable Sensor System

Partial body weight support or loading sit-to-stand (STS) rehabilitation can be useful for persons with lower limb dysfunction to achieve movement again based on the internal residual muscle force and external assistance. To explicate how the muscles contribute to the kinetics and kinematics of STS...

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Autores principales: Liu, Kun, Liu, Yong, Yan, Jianchao, Sun, Zhenyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948594/
https://www.ncbi.nlm.nih.gov/pubmed/29587391
http://dx.doi.org/10.3390/s18040971
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author Liu, Kun
Liu, Yong
Yan, Jianchao
Sun, Zhenyuan
author_facet Liu, Kun
Liu, Yong
Yan, Jianchao
Sun, Zhenyuan
author_sort Liu, Kun
collection PubMed
description Partial body weight support or loading sit-to-stand (STS) rehabilitation can be useful for persons with lower limb dysfunction to achieve movement again based on the internal residual muscle force and external assistance. To explicate how the muscles contribute to the kinetics and kinematics of STS performance by non-invasive in vitro detection and to nondestructively estimate the muscle contributions to STS training with different loadings, a wearable sensor system was developed with ground reaction force (GRF) platforms, motion capture inertial sensors and electromyography (EMG) sensors. To estimate the internal moments of hip, knee and ankle joints and quantify the contributions of individual muscle and gravity to STS movement, the inverse dynamics analysis on a simplified STS biomechanical model with external loading is proposed. The functional roles of the lower limb individual muscles (rectus femoris (RF), gluteus maximus (GM), vastus lateralis (VL), tibialis anterior (TA) and gastrocnemius (GAST)) during STS motion and the mechanism of the muscles’ synergies to perform STS-specific subtasks were analyzed. The muscle contributions to the biomechanical STS subtasks of vertical propulsion, anteroposterior (AP) braking and propulsion for body balance in the sagittal plane were quantified by experimental studies with EMG, kinematic and kinetic data.
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spelling pubmed-59485942018-05-17 Nondestructive Estimation of Muscle Contributions to STS Training with Different Loadings Based on Wearable Sensor System Liu, Kun Liu, Yong Yan, Jianchao Sun, Zhenyuan Sensors (Basel) Article Partial body weight support or loading sit-to-stand (STS) rehabilitation can be useful for persons with lower limb dysfunction to achieve movement again based on the internal residual muscle force and external assistance. To explicate how the muscles contribute to the kinetics and kinematics of STS performance by non-invasive in vitro detection and to nondestructively estimate the muscle contributions to STS training with different loadings, a wearable sensor system was developed with ground reaction force (GRF) platforms, motion capture inertial sensors and electromyography (EMG) sensors. To estimate the internal moments of hip, knee and ankle joints and quantify the contributions of individual muscle and gravity to STS movement, the inverse dynamics analysis on a simplified STS biomechanical model with external loading is proposed. The functional roles of the lower limb individual muscles (rectus femoris (RF), gluteus maximus (GM), vastus lateralis (VL), tibialis anterior (TA) and gastrocnemius (GAST)) during STS motion and the mechanism of the muscles’ synergies to perform STS-specific subtasks were analyzed. The muscle contributions to the biomechanical STS subtasks of vertical propulsion, anteroposterior (AP) braking and propulsion for body balance in the sagittal plane were quantified by experimental studies with EMG, kinematic and kinetic data. MDPI 2018-03-25 /pmc/articles/PMC5948594/ /pubmed/29587391 http://dx.doi.org/10.3390/s18040971 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Kun
Liu, Yong
Yan, Jianchao
Sun, Zhenyuan
Nondestructive Estimation of Muscle Contributions to STS Training with Different Loadings Based on Wearable Sensor System
title Nondestructive Estimation of Muscle Contributions to STS Training with Different Loadings Based on Wearable Sensor System
title_full Nondestructive Estimation of Muscle Contributions to STS Training with Different Loadings Based on Wearable Sensor System
title_fullStr Nondestructive Estimation of Muscle Contributions to STS Training with Different Loadings Based on Wearable Sensor System
title_full_unstemmed Nondestructive Estimation of Muscle Contributions to STS Training with Different Loadings Based on Wearable Sensor System
title_short Nondestructive Estimation of Muscle Contributions to STS Training with Different Loadings Based on Wearable Sensor System
title_sort nondestructive estimation of muscle contributions to sts training with different loadings based on wearable sensor system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948594/
https://www.ncbi.nlm.nih.gov/pubmed/29587391
http://dx.doi.org/10.3390/s18040971
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