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Simulation of in vivo dynamics during robot assisted joint movement

BACKGROUND: Robots are very useful tools in orthopedic research. They can provide force/torque controlled specimen motion with high repeatability and precision. A method to analyze dissipative energy outcome in an entire joint was developed in our group. In a previous study, a sheep knee was flexed...

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Autores principales: Bobrowitsch, Evgenij, Lorenz, Andrea, Wülker, Nikolaus, Walter, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4279817/
https://www.ncbi.nlm.nih.gov/pubmed/25516427
http://dx.doi.org/10.1186/1475-925X-13-167
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author Bobrowitsch, Evgenij
Lorenz, Andrea
Wülker, Nikolaus
Walter, Christian
author_facet Bobrowitsch, Evgenij
Lorenz, Andrea
Wülker, Nikolaus
Walter, Christian
author_sort Bobrowitsch, Evgenij
collection PubMed
description BACKGROUND: Robots are very useful tools in orthopedic research. They can provide force/torque controlled specimen motion with high repeatability and precision. A method to analyze dissipative energy outcome in an entire joint was developed in our group. In a previous study, a sheep knee was flexed while axial load remained constant during the measurement of dissipated energy. We intend to apply this method for the investigation of osteoarthritis. Additionally, the method should be improved by simulation of in vivo knee dynamics. Thus, a new biomechanical testing tool will be developed for analyzing in vitro joint properties after different treatments. METHODS: Discretization of passive knee flexion was used to construct a complex flexion movement by a robot and simulate altering axial load similar to in vivo sheep knee dynamics described in a previous experimental study. RESULTS: The robot applied an in vivo like axial force profile with high reproducibility during the corresponding knee flexion (total standard deviation of 0.025 body weight (BW)). A total residual error between the in vivo and simulated axial force was 0.16 BW. Posterior-anterior and medio-lateral forces were detected by the robot as a backlash of joint structures. Their curve forms were similar to curve forms of corresponding in vivo measured forces, but in contrast to the axial force, they showed higher total standard deviation of 0.118 and 0.203 BW and higher total residual error of 0.79 and 0.21 BW for posterior-anterior and medio-lateral forces respectively. CONCLUSIONS: We developed and evaluated an algorithm for the robotic simulation of complex in vivo joint dynamics using a joint specimen. This should be a new biomechanical testing tool for analyzing joint properties after different treatments.
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spelling pubmed-42798172014-12-31 Simulation of in vivo dynamics during robot assisted joint movement Bobrowitsch, Evgenij Lorenz, Andrea Wülker, Nikolaus Walter, Christian Biomed Eng Online Research BACKGROUND: Robots are very useful tools in orthopedic research. They can provide force/torque controlled specimen motion with high repeatability and precision. A method to analyze dissipative energy outcome in an entire joint was developed in our group. In a previous study, a sheep knee was flexed while axial load remained constant during the measurement of dissipated energy. We intend to apply this method for the investigation of osteoarthritis. Additionally, the method should be improved by simulation of in vivo knee dynamics. Thus, a new biomechanical testing tool will be developed for analyzing in vitro joint properties after different treatments. METHODS: Discretization of passive knee flexion was used to construct a complex flexion movement by a robot and simulate altering axial load similar to in vivo sheep knee dynamics described in a previous experimental study. RESULTS: The robot applied an in vivo like axial force profile with high reproducibility during the corresponding knee flexion (total standard deviation of 0.025 body weight (BW)). A total residual error between the in vivo and simulated axial force was 0.16 BW. Posterior-anterior and medio-lateral forces were detected by the robot as a backlash of joint structures. Their curve forms were similar to curve forms of corresponding in vivo measured forces, but in contrast to the axial force, they showed higher total standard deviation of 0.118 and 0.203 BW and higher total residual error of 0.79 and 0.21 BW for posterior-anterior and medio-lateral forces respectively. CONCLUSIONS: We developed and evaluated an algorithm for the robotic simulation of complex in vivo joint dynamics using a joint specimen. This should be a new biomechanical testing tool for analyzing joint properties after different treatments. BioMed Central 2014-12-16 /pmc/articles/PMC4279817/ /pubmed/25516427 http://dx.doi.org/10.1186/1475-925X-13-167 Text en © Bobrowitsch et al.; licensee BioMed Central. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Bobrowitsch, Evgenij
Lorenz, Andrea
Wülker, Nikolaus
Walter, Christian
Simulation of in vivo dynamics during robot assisted joint movement
title Simulation of in vivo dynamics during robot assisted joint movement
title_full Simulation of in vivo dynamics during robot assisted joint movement
title_fullStr Simulation of in vivo dynamics during robot assisted joint movement
title_full_unstemmed Simulation of in vivo dynamics during robot assisted joint movement
title_short Simulation of in vivo dynamics during robot assisted joint movement
title_sort simulation of in vivo dynamics during robot assisted joint movement
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4279817/
https://www.ncbi.nlm.nih.gov/pubmed/25516427
http://dx.doi.org/10.1186/1475-925X-13-167
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