VisionMD: an open-source tool for video-based analysis of motor function in movement disorders
Abstract VisionMD, an open-source software for automated video-based analysis of MDS-UPDRS Part III motor tasks, offers precise, objective, and scalable assessments of motor symptoms in Parkinson’s disease and other movement disorders. Leveraging deep learning, VisionMD tracks body movements to comp...
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Format: | Article |
Language: | English |
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Nature Portfolio
2025-02-01
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Series: | npj Parkinson's Disease |
Online Access: | https://doi.org/10.1038/s41531-025-00876-6 |
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author | Gabriela Acevedo Florian Lange Carolina Calonge Robert Peach Joshua K. Wong Diego L. Guarin |
author_facet | Gabriela Acevedo Florian Lange Carolina Calonge Robert Peach Joshua K. Wong Diego L. Guarin |
author_sort | Gabriela Acevedo |
collection | DOAJ |
description | Abstract VisionMD, an open-source software for automated video-based analysis of MDS-UPDRS Part III motor tasks, offers precise, objective, and scalable assessments of motor symptoms in Parkinson’s disease and other movement disorders. Leveraging deep learning, VisionMD tracks body movements to compute kinematic features that quantify symptoms severity and supports longitudinal monitoring. VisionMD’s user-friendly, customizable framework empowers clinicians and researchers to objectively evaluate motor symptoms in persons with movement disorders without specialized hardware. |
format | Article |
id | doaj-art-c98cbaea1a544431bddbbb07680c4745 |
institution | Kabale University |
issn | 2373-8057 |
language | English |
publishDate | 2025-02-01 |
publisher | Nature Portfolio |
record_format | Article |
series | npj Parkinson's Disease |
spelling | doaj-art-c98cbaea1a544431bddbbb07680c47452025-02-09T12:26:27ZengNature Portfolionpj Parkinson's Disease2373-80572025-02-011111510.1038/s41531-025-00876-6VisionMD: an open-source tool for video-based analysis of motor function in movement disordersGabriela Acevedo0Florian Lange1Carolina Calonge2Robert Peach3Joshua K. Wong4Diego L. Guarin5Movement Estimation and Analysis Laboratory, Department of Applied Physiology and Kinesiology, University of FloridaDepartment of Neurology, University of WürzburgMovement Estimation and Analysis Laboratory, Department of Applied Physiology and Kinesiology, University of FloridaDepartment of Neurology, University of WürzburgFixel Institute for Neurological Disease, College of Medicine, University of FloridaMovement Estimation and Analysis Laboratory, Department of Applied Physiology and Kinesiology, University of FloridaAbstract VisionMD, an open-source software for automated video-based analysis of MDS-UPDRS Part III motor tasks, offers precise, objective, and scalable assessments of motor symptoms in Parkinson’s disease and other movement disorders. Leveraging deep learning, VisionMD tracks body movements to compute kinematic features that quantify symptoms severity and supports longitudinal monitoring. VisionMD’s user-friendly, customizable framework empowers clinicians and researchers to objectively evaluate motor symptoms in persons with movement disorders without specialized hardware.https://doi.org/10.1038/s41531-025-00876-6 |
spellingShingle | Gabriela Acevedo Florian Lange Carolina Calonge Robert Peach Joshua K. Wong Diego L. Guarin VisionMD: an open-source tool for video-based analysis of motor function in movement disorders npj Parkinson's Disease |
title | VisionMD: an open-source tool for video-based analysis of motor function in movement disorders |
title_full | VisionMD: an open-source tool for video-based analysis of motor function in movement disorders |
title_fullStr | VisionMD: an open-source tool for video-based analysis of motor function in movement disorders |
title_full_unstemmed | VisionMD: an open-source tool for video-based analysis of motor function in movement disorders |
title_short | VisionMD: an open-source tool for video-based analysis of motor function in movement disorders |
title_sort | visionmd an open source tool for video based analysis of motor function in movement disorders |
url | https://doi.org/10.1038/s41531-025-00876-6 |
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