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Video-Based Analyses of Parkinson’s Disease Severity: A Brief Review

Remote and objective assessment of the motor symptoms of Parkinson’s disease is an area of great interest particularly since the COVID-19 crisis emerged. In this paper, we focus on a) the challenges of assessing motor severity via videos and b) the use of emerging video-based Artificial Intelligence...

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Detalles Bibliográficos
Autores principales: Sibley, Krista G., Girges, Christine, Hoque, Ehsan, Foltynie, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8385513/
https://www.ncbi.nlm.nih.gov/pubmed/33682727
http://dx.doi.org/10.3233/JPD-202402
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author Sibley, Krista G.
Girges, Christine
Hoque, Ehsan
Foltynie, Thomas
author_facet Sibley, Krista G.
Girges, Christine
Hoque, Ehsan
Foltynie, Thomas
author_sort Sibley, Krista G.
collection PubMed
description Remote and objective assessment of the motor symptoms of Parkinson’s disease is an area of great interest particularly since the COVID-19 crisis emerged. In this paper, we focus on a) the challenges of assessing motor severity via videos and b) the use of emerging video-based Artificial Intelligence (AI)/Machine Learning techniques to quantitate human movement and its potential utility in assessing motor severity in patients with Parkinson’s disease. While we conclude that video-based assessment may be an accessible and useful way of monitoring motor severity of Parkinson’s disease, the potential of video-based AI to diagnose and quantify disease severity in the clinical context is dependent on research with large, diverse samples, and further validation using carefully considered performance standards.
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spelling pubmed-83855132021-09-09 Video-Based Analyses of Parkinson’s Disease Severity: A Brief Review Sibley, Krista G. Girges, Christine Hoque, Ehsan Foltynie, Thomas J Parkinsons Dis Review Remote and objective assessment of the motor symptoms of Parkinson’s disease is an area of great interest particularly since the COVID-19 crisis emerged. In this paper, we focus on a) the challenges of assessing motor severity via videos and b) the use of emerging video-based Artificial Intelligence (AI)/Machine Learning techniques to quantitate human movement and its potential utility in assessing motor severity in patients with Parkinson’s disease. While we conclude that video-based assessment may be an accessible and useful way of monitoring motor severity of Parkinson’s disease, the potential of video-based AI to diagnose and quantify disease severity in the clinical context is dependent on research with large, diverse samples, and further validation using carefully considered performance standards. IOS Press 2021-07-16 /pmc/articles/PMC8385513/ /pubmed/33682727 http://dx.doi.org/10.3233/JPD-202402 Text en © 2021 – The authors. Published by IOS Press https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) License (https://creativecommons.org/licenses/by-nc/4.0/) , which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Sibley, Krista G.
Girges, Christine
Hoque, Ehsan
Foltynie, Thomas
Video-Based Analyses of Parkinson’s Disease Severity: A Brief Review
title Video-Based Analyses of Parkinson’s Disease Severity: A Brief Review
title_full Video-Based Analyses of Parkinson’s Disease Severity: A Brief Review
title_fullStr Video-Based Analyses of Parkinson’s Disease Severity: A Brief Review
title_full_unstemmed Video-Based Analyses of Parkinson’s Disease Severity: A Brief Review
title_short Video-Based Analyses of Parkinson’s Disease Severity: A Brief Review
title_sort video-based analyses of parkinson’s disease severity: a brief review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8385513/
https://www.ncbi.nlm.nih.gov/pubmed/33682727
http://dx.doi.org/10.3233/JPD-202402
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