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Development, evaluation and application of a novel markerless motion analysis system to understand push-start technique in elite skeleton athletes
This study describes the development, evaluation and application of a computer vision and deep learning system capable of capturing sprinting and skeleton push start step characteristics and mass centre velocities (sled and athlete). Movement data were captured concurrently by a marker-based motion...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8592484/ https://www.ncbi.nlm.nih.gov/pubmed/34780514 http://dx.doi.org/10.1371/journal.pone.0259624 |
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author | Needham, Laurie Evans, Murray Cosker, Darren P. Colyer, Steffi L. |
author_facet | Needham, Laurie Evans, Murray Cosker, Darren P. Colyer, Steffi L. |
author_sort | Needham, Laurie |
collection | PubMed |
description | This study describes the development, evaluation and application of a computer vision and deep learning system capable of capturing sprinting and skeleton push start step characteristics and mass centre velocities (sled and athlete). Movement data were captured concurrently by a marker-based motion capture system and a custom markerless system. High levels of agreement were found between systems, particularly for spatial based variables (step length error 0.001 ± 0.012 m) while errors for temporal variables (ground contact time and flight time) were on average within ± 1.5 frames of the criterion measures. Comparisons of sprinting and pushing revealed decreased mass centre velocities as a result of pushing the sled but step characteristics were comparable to sprinting when aligned as a function of step velocity. There were large asymmetries between the inside and outside leg during pushing (e.g. 0.22 m mean step length asymmetry) which were not present during sprinting (0.01 m step length asymmetry). The observed asymmetries suggested that force production capabilities during ground contact were compromised for the outside leg. The computer vision based methods tested in this research provide a viable alternative to marker-based motion capture systems. Furthermore, they can be deployed into challenging, real world environments to non-invasively capture data where traditional approaches are infeasible. |
format | Online Article Text |
id | pubmed-8592484 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-85924842021-11-16 Development, evaluation and application of a novel markerless motion analysis system to understand push-start technique in elite skeleton athletes Needham, Laurie Evans, Murray Cosker, Darren P. Colyer, Steffi L. PLoS One Research Article This study describes the development, evaluation and application of a computer vision and deep learning system capable of capturing sprinting and skeleton push start step characteristics and mass centre velocities (sled and athlete). Movement data were captured concurrently by a marker-based motion capture system and a custom markerless system. High levels of agreement were found between systems, particularly for spatial based variables (step length error 0.001 ± 0.012 m) while errors for temporal variables (ground contact time and flight time) were on average within ± 1.5 frames of the criterion measures. Comparisons of sprinting and pushing revealed decreased mass centre velocities as a result of pushing the sled but step characteristics were comparable to sprinting when aligned as a function of step velocity. There were large asymmetries between the inside and outside leg during pushing (e.g. 0.22 m mean step length asymmetry) which were not present during sprinting (0.01 m step length asymmetry). The observed asymmetries suggested that force production capabilities during ground contact were compromised for the outside leg. The computer vision based methods tested in this research provide a viable alternative to marker-based motion capture systems. Furthermore, they can be deployed into challenging, real world environments to non-invasively capture data where traditional approaches are infeasible. Public Library of Science 2021-11-15 /pmc/articles/PMC8592484/ /pubmed/34780514 http://dx.doi.org/10.1371/journal.pone.0259624 Text en © 2021 Needham 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, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Needham, Laurie Evans, Murray Cosker, Darren P. Colyer, Steffi L. Development, evaluation and application of a novel markerless motion analysis system to understand push-start technique in elite skeleton athletes |
title | Development, evaluation and application of a novel markerless motion analysis system to understand push-start technique in elite skeleton athletes |
title_full | Development, evaluation and application of a novel markerless motion analysis system to understand push-start technique in elite skeleton athletes |
title_fullStr | Development, evaluation and application of a novel markerless motion analysis system to understand push-start technique in elite skeleton athletes |
title_full_unstemmed | Development, evaluation and application of a novel markerless motion analysis system to understand push-start technique in elite skeleton athletes |
title_short | Development, evaluation and application of a novel markerless motion analysis system to understand push-start technique in elite skeleton athletes |
title_sort | development, evaluation and application of a novel markerless motion analysis system to understand push-start technique in elite skeleton athletes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8592484/ https://www.ncbi.nlm.nih.gov/pubmed/34780514 http://dx.doi.org/10.1371/journal.pone.0259624 |
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