Applications of Pose Estimation in Human Health and Performance across the Lifespan

The emergence of pose estimation algorithms represents a potential paradigm shift in the study and assessment of human movement. Human pose estimation algorithms leverage advances in computer vision to track human movement automatically from simple videos recorded using common household devices with...

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Autores principales:	Jan Stenum, Kendra M. Cherry-Allen, Connor O. Pyles, Rachel D. Reetzke, Michael F. Vignos, Ryan T. Roemmich
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	pose estimation movement tracking computer vision artificial intelligence markerless motion capture assessment Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/1645132efa314022b1165b5509c8363e
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spelling	oai:doaj.org-article:1645132efa314022b1165b5509c8363e2021-11-11T19:15:48ZApplications of Pose Estimation in Human Health and Performance across the Lifespan10.3390/s212173151424-8220https://doaj.org/article/1645132efa314022b1165b5509c8363e2021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7315https://doaj.org/toc/1424-8220The emergence of pose estimation algorithms represents a potential paradigm shift in the study and assessment of human movement. Human pose estimation algorithms leverage advances in computer vision to track human movement automatically from simple videos recorded using common household devices with relatively low-cost cameras (e.g., smartphones, tablets, laptop computers). In our view, these technologies offer clear and exciting potential to make measurement of human movement substantially more accessible; for example, a clinician could perform a quantitative motor assessment directly in a patient’s home, a researcher without access to expensive motion capture equipment could analyze movement kinematics using a smartphone video, and a coach could evaluate player performance with video recordings directly from the field. In this review, we combine expertise and perspectives from physical therapy, speech-language pathology, movement science, and engineering to provide insight into applications of pose estimation in human health and performance. We focus specifically on applications in areas of human development, performance optimization, injury prevention, and motor assessment of persons with neurologic damage or disease. We review relevant literature, share interdisciplinary viewpoints on future applications of these technologies to improve human health and performance, and discuss perceived limitations.Jan StenumKendra M. Cherry-AllenConnor O. PylesRachel D. ReetzkeMichael F. VignosRyan T. RoemmichMDPI AGarticlepose estimationmovement trackingcomputer visionartificial intelligencemarkerless motion captureassessmentChemical technologyTP1-1185ENSensors, Vol 21, Iss 7315, p 7315 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	pose estimation movement tracking computer vision artificial intelligence markerless motion capture assessment Chemical technology TP1-1185
spellingShingle	pose estimation movement tracking computer vision artificial intelligence markerless motion capture assessment Chemical technology TP1-1185 Jan Stenum Kendra M. Cherry-Allen Connor O. Pyles Rachel D. Reetzke Michael F. Vignos Ryan T. Roemmich Applications of Pose Estimation in Human Health and Performance across the Lifespan
description	The emergence of pose estimation algorithms represents a potential paradigm shift in the study and assessment of human movement. Human pose estimation algorithms leverage advances in computer vision to track human movement automatically from simple videos recorded using common household devices with relatively low-cost cameras (e.g., smartphones, tablets, laptop computers). In our view, these technologies offer clear and exciting potential to make measurement of human movement substantially more accessible; for example, a clinician could perform a quantitative motor assessment directly in a patient’s home, a researcher without access to expensive motion capture equipment could analyze movement kinematics using a smartphone video, and a coach could evaluate player performance with video recordings directly from the field. In this review, we combine expertise and perspectives from physical therapy, speech-language pathology, movement science, and engineering to provide insight into applications of pose estimation in human health and performance. We focus specifically on applications in areas of human development, performance optimization, injury prevention, and motor assessment of persons with neurologic damage or disease. We review relevant literature, share interdisciplinary viewpoints on future applications of these technologies to improve human health and performance, and discuss perceived limitations.
format	article
author	Jan Stenum Kendra M. Cherry-Allen Connor O. Pyles Rachel D. Reetzke Michael F. Vignos Ryan T. Roemmich
author_facet	Jan Stenum Kendra M. Cherry-Allen Connor O. Pyles Rachel D. Reetzke Michael F. Vignos Ryan T. Roemmich
author_sort	Jan Stenum
title	Applications of Pose Estimation in Human Health and Performance across the Lifespan
title_short	Applications of Pose Estimation in Human Health and Performance across the Lifespan
title_full	Applications of Pose Estimation in Human Health and Performance across the Lifespan
title_fullStr	Applications of Pose Estimation in Human Health and Performance across the Lifespan
title_full_unstemmed	Applications of Pose Estimation in Human Health and Performance across the Lifespan
title_sort	applications of pose estimation in human health and performance across the lifespan
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/1645132efa314022b1165b5509c8363e
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Applications of Pose Estimation in Human Health and Performance across the Lifespan

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