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Evaluation of functional methods of joint centre determination for quasi-planar movement

Functional methods identify joint centres as the centre of rotation (CoR) of two adjacent movements during an ad-hoc movement. The methods have been used for functionally determining hip joint centre in gait analysis and have revealed advantages compared to predictive regression techniques. However,...

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Detalles Bibliográficos
Autores principales: Meng, Lin, Childs, Craig, Buis, Arjan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6336381/
https://www.ncbi.nlm.nih.gov/pubmed/30653613
http://dx.doi.org/10.1371/journal.pone.0210807
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author Meng, Lin
Childs, Craig
Buis, Arjan
author_facet Meng, Lin
Childs, Craig
Buis, Arjan
author_sort Meng, Lin
collection PubMed
description Functional methods identify joint centres as the centre of rotation (CoR) of two adjacent movements during an ad-hoc movement. The methods have been used for functionally determining hip joint centre in gait analysis and have revealed advantages compared to predictive regression techniques. However, the current implementation of functional methods hinders its application in clinical use when subjects have difficulties performing multi-plane movements over the required range. In this study, we systematically investigated whether functional methods can be used to localise the CoR during a quasi-planar movement. The effects of the following factors were analysed: the algorithms, the range and speed of the movement, marker cluster location, marker cluster size and distance to the joint centre. A mechanical linkage was used in our study to isolate the factors of interest and give insight to variation in implementation of functional methods. Our results showed the algorithms and cluster locations significantly affected the estimate results. For all algorithms, a significantly positive relationship between CoR errors and the distance of proximal cluster coordinate location to the joint centre along the medial-lateral direction was observed while the distal marker clusters were best located as close as possible to the joint centre. By optimising the analytical and experimental factors, the transformation algorithms achieved a root mean square error (RMSE) of 5.3 mm while the sphere fitting methods yielded the best estimation with an RMSE of 2.6 mm. The transformation algorithms performed better in presence of random noise and simulated soft tissue artefacts.
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spelling pubmed-63363812019-01-30 Evaluation of functional methods of joint centre determination for quasi-planar movement Meng, Lin Childs, Craig Buis, Arjan PLoS One Research Article Functional methods identify joint centres as the centre of rotation (CoR) of two adjacent movements during an ad-hoc movement. The methods have been used for functionally determining hip joint centre in gait analysis and have revealed advantages compared to predictive regression techniques. However, the current implementation of functional methods hinders its application in clinical use when subjects have difficulties performing multi-plane movements over the required range. In this study, we systematically investigated whether functional methods can be used to localise the CoR during a quasi-planar movement. The effects of the following factors were analysed: the algorithms, the range and speed of the movement, marker cluster location, marker cluster size and distance to the joint centre. A mechanical linkage was used in our study to isolate the factors of interest and give insight to variation in implementation of functional methods. Our results showed the algorithms and cluster locations significantly affected the estimate results. For all algorithms, a significantly positive relationship between CoR errors and the distance of proximal cluster coordinate location to the joint centre along the medial-lateral direction was observed while the distal marker clusters were best located as close as possible to the joint centre. By optimising the analytical and experimental factors, the transformation algorithms achieved a root mean square error (RMSE) of 5.3 mm while the sphere fitting methods yielded the best estimation with an RMSE of 2.6 mm. The transformation algorithms performed better in presence of random noise and simulated soft tissue artefacts. Public Library of Science 2019-01-17 /pmc/articles/PMC6336381/ /pubmed/30653613 http://dx.doi.org/10.1371/journal.pone.0210807 Text en © 2019 Meng et al http://creativecommons.org/licenses/by/4.0/ 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 author and source are credited.
spellingShingle Research Article
Meng, Lin
Childs, Craig
Buis, Arjan
Evaluation of functional methods of joint centre determination for quasi-planar movement
title Evaluation of functional methods of joint centre determination for quasi-planar movement
title_full Evaluation of functional methods of joint centre determination for quasi-planar movement
title_fullStr Evaluation of functional methods of joint centre determination for quasi-planar movement
title_full_unstemmed Evaluation of functional methods of joint centre determination for quasi-planar movement
title_short Evaluation of functional methods of joint centre determination for quasi-planar movement
title_sort evaluation of functional methods of joint centre determination for quasi-planar movement
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6336381/
https://www.ncbi.nlm.nih.gov/pubmed/30653613
http://dx.doi.org/10.1371/journal.pone.0210807
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