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Development and Validation of a Novel In Vitro Joint Testing System for Reproduction of In Vivo Dynamic Muscle Force

In vitro biomechanical experiments utilizing cadaveric specimens are one of the most effective methods for rehearsing surgical procedures, testing implants, and guiding postoperative rehabilitation. Applying dynamic physiological muscle force to the specimens is a challenge to reconstructing the env...

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Autores principales: Yang, Yangyang, Wang, Yufan, Zheng, Nan, Cheng, Rongshan, Zou, Diyang, Zhao, Jie, Tsai, Tsung-Yuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10525521/
https://www.ncbi.nlm.nih.gov/pubmed/37760108
http://dx.doi.org/10.3390/bioengineering10091006
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author Yang, Yangyang
Wang, Yufan
Zheng, Nan
Cheng, Rongshan
Zou, Diyang
Zhao, Jie
Tsai, Tsung-Yuan
author_facet Yang, Yangyang
Wang, Yufan
Zheng, Nan
Cheng, Rongshan
Zou, Diyang
Zhao, Jie
Tsai, Tsung-Yuan
author_sort Yang, Yangyang
collection PubMed
description In vitro biomechanical experiments utilizing cadaveric specimens are one of the most effective methods for rehearsing surgical procedures, testing implants, and guiding postoperative rehabilitation. Applying dynamic physiological muscle force to the specimens is a challenge to reconstructing the environment of bionic mechanics in vivo, which is often ignored in the in vitro experiment. The current work aims to establish a hardware platform and numerical computation methods to reproduce dynamic muscle forces that can be applied to mechanical testing on in vitro specimens. Dynamic muscle loading is simulated through numerical computation, and the inputs of the platform will be derived. Then, the accuracy and robustness of the platform will be evaluated through actual muscle loading tests in vitro. The tests were run on three muscles (gastrocnemius lateralis, the rectus femoris, and the semitendinosus) around the knee joint and the results showed that the platform can accurately reproduce the magnitude of muscle strength (errors range from −6.2% to 1.81%) and changing pattern (goodness-of-fit range coefficient ranges from 0.00 to 0.06) of target muscle forces. The robustness of the platform is mainly manifested in that the platform can still accurately reproduce muscle force after changing the hardware combination. Additionally, the standard deviation of repeated test results is very small (standard ranges of hardware combination 1: 0.34 N~2.79 N vs. hardware combination 2: 0.68 N~2.93 N). Thus, the platform can stably and accurately reproduce muscle forces in vitro, and it has great potential to be applied in the future musculoskeletal loading system.
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spelling pubmed-105255212023-09-28 Development and Validation of a Novel In Vitro Joint Testing System for Reproduction of In Vivo Dynamic Muscle Force Yang, Yangyang Wang, Yufan Zheng, Nan Cheng, Rongshan Zou, Diyang Zhao, Jie Tsai, Tsung-Yuan Bioengineering (Basel) Article In vitro biomechanical experiments utilizing cadaveric specimens are one of the most effective methods for rehearsing surgical procedures, testing implants, and guiding postoperative rehabilitation. Applying dynamic physiological muscle force to the specimens is a challenge to reconstructing the environment of bionic mechanics in vivo, which is often ignored in the in vitro experiment. The current work aims to establish a hardware platform and numerical computation methods to reproduce dynamic muscle forces that can be applied to mechanical testing on in vitro specimens. Dynamic muscle loading is simulated through numerical computation, and the inputs of the platform will be derived. Then, the accuracy and robustness of the platform will be evaluated through actual muscle loading tests in vitro. The tests were run on three muscles (gastrocnemius lateralis, the rectus femoris, and the semitendinosus) around the knee joint and the results showed that the platform can accurately reproduce the magnitude of muscle strength (errors range from −6.2% to 1.81%) and changing pattern (goodness-of-fit range coefficient ranges from 0.00 to 0.06) of target muscle forces. The robustness of the platform is mainly manifested in that the platform can still accurately reproduce muscle force after changing the hardware combination. Additionally, the standard deviation of repeated test results is very small (standard ranges of hardware combination 1: 0.34 N~2.79 N vs. hardware combination 2: 0.68 N~2.93 N). Thus, the platform can stably and accurately reproduce muscle forces in vitro, and it has great potential to be applied in the future musculoskeletal loading system. MDPI 2023-08-25 /pmc/articles/PMC10525521/ /pubmed/37760108 http://dx.doi.org/10.3390/bioengineering10091006 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yang, Yangyang
Wang, Yufan
Zheng, Nan
Cheng, Rongshan
Zou, Diyang
Zhao, Jie
Tsai, Tsung-Yuan
Development and Validation of a Novel In Vitro Joint Testing System for Reproduction of In Vivo Dynamic Muscle Force
title Development and Validation of a Novel In Vitro Joint Testing System for Reproduction of In Vivo Dynamic Muscle Force
title_full Development and Validation of a Novel In Vitro Joint Testing System for Reproduction of In Vivo Dynamic Muscle Force
title_fullStr Development and Validation of a Novel In Vitro Joint Testing System for Reproduction of In Vivo Dynamic Muscle Force
title_full_unstemmed Development and Validation of a Novel In Vitro Joint Testing System for Reproduction of In Vivo Dynamic Muscle Force
title_short Development and Validation of a Novel In Vitro Joint Testing System for Reproduction of In Vivo Dynamic Muscle Force
title_sort development and validation of a novel in vitro joint testing system for reproduction of in vivo dynamic muscle force
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10525521/
https://www.ncbi.nlm.nih.gov/pubmed/37760108
http://dx.doi.org/10.3390/bioengineering10091006
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