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Use of the Azure Kinect to measure foot clearance during obstacle crossing: A validation study

Obstacle crossing is typical adaptive locomotion known to be related to the risk of falls. Previous conventional studies have used elaborate and costly optical motion capture systems, which not only represent a considerable expense but also require participants to visit a laboratory. To overcome the...

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Detalles Bibliográficos
Autores principales: Yoshimoto, Kohei, Shinya, Masahiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8916621/
https://www.ncbi.nlm.nih.gov/pubmed/35275979
http://dx.doi.org/10.1371/journal.pone.0265215
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author Yoshimoto, Kohei
Shinya, Masahiro
author_facet Yoshimoto, Kohei
Shinya, Masahiro
author_sort Yoshimoto, Kohei
collection PubMed
description Obstacle crossing is typical adaptive locomotion known to be related to the risk of falls. Previous conventional studies have used elaborate and costly optical motion capture systems, which not only represent a considerable expense but also require participants to visit a laboratory. To overcome these shortcomings, we aimed to develop a practical and inexpensive solution for measuring obstacle-crossing behavior by using the Microsoft Azure Kinect, one of the most promising markerless motion capture systems. We validated the Azure Kinect as a tool to measure foot clearance and compared its performance to that of an optical motion capture system (Qualisys). We also determined the effect of the Kinect sensor placement on measurement performance. Sixteen healthy young men crossed obstacles of different heights (50, 150, and 250 mm). Kinect sensors were placed in front of and beside the obstacle as well as diagonally between those positions. As indices of measurement quality, we counted the number of measurement failures and calculated the systematic and random errors between the foot clearance measured by the Kinect and Qualisys. We also calculated the Pearson correlation coefficients between the Kinect and Qualisys measurements. The number of measurement failures and the systematic and random error were minimized when the Kinect was placed diagonally in front of the obstacle on the same side as the trail limb. The high correlation coefficient (r > 0.890) observed between the Kinect and Qualisys measurements suggest that the Azure Kinect has excellent potential for measuring foot clearance during obstacle-crossing tasks.
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spelling pubmed-89166212022-03-12 Use of the Azure Kinect to measure foot clearance during obstacle crossing: A validation study Yoshimoto, Kohei Shinya, Masahiro PLoS One Research Article Obstacle crossing is typical adaptive locomotion known to be related to the risk of falls. Previous conventional studies have used elaborate and costly optical motion capture systems, which not only represent a considerable expense but also require participants to visit a laboratory. To overcome these shortcomings, we aimed to develop a practical and inexpensive solution for measuring obstacle-crossing behavior by using the Microsoft Azure Kinect, one of the most promising markerless motion capture systems. We validated the Azure Kinect as a tool to measure foot clearance and compared its performance to that of an optical motion capture system (Qualisys). We also determined the effect of the Kinect sensor placement on measurement performance. Sixteen healthy young men crossed obstacles of different heights (50, 150, and 250 mm). Kinect sensors were placed in front of and beside the obstacle as well as diagonally between those positions. As indices of measurement quality, we counted the number of measurement failures and calculated the systematic and random errors between the foot clearance measured by the Kinect and Qualisys. We also calculated the Pearson correlation coefficients between the Kinect and Qualisys measurements. The number of measurement failures and the systematic and random error were minimized when the Kinect was placed diagonally in front of the obstacle on the same side as the trail limb. The high correlation coefficient (r > 0.890) observed between the Kinect and Qualisys measurements suggest that the Azure Kinect has excellent potential for measuring foot clearance during obstacle-crossing tasks. Public Library of Science 2022-03-11 /pmc/articles/PMC8916621/ /pubmed/35275979 http://dx.doi.org/10.1371/journal.pone.0265215 Text en © 2022 Yoshimoto, Shinya 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
Yoshimoto, Kohei
Shinya, Masahiro
Use of the Azure Kinect to measure foot clearance during obstacle crossing: A validation study
title Use of the Azure Kinect to measure foot clearance during obstacle crossing: A validation study
title_full Use of the Azure Kinect to measure foot clearance during obstacle crossing: A validation study
title_fullStr Use of the Azure Kinect to measure foot clearance during obstacle crossing: A validation study
title_full_unstemmed Use of the Azure Kinect to measure foot clearance during obstacle crossing: A validation study
title_short Use of the Azure Kinect to measure foot clearance during obstacle crossing: A validation study
title_sort use of the azure kinect to measure foot clearance during obstacle crossing: a validation study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8916621/
https://www.ncbi.nlm.nih.gov/pubmed/35275979
http://dx.doi.org/10.1371/journal.pone.0265215
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