With smartphone videos, clinicians can analyze human movement using open source "OpenCap" platform, 25x faster and at a fraction of the cost of labs
IMAGE:
ANALYZING HUMAN MOVEMENT WITH OPENCAP
view moreCREDIT: ULRICH ET AL., 2023, PLOS COMPUTATIONAL BIOLOGY, CC-BY 4.0 (HTTPS://CREATIVECOMMONS.ORG/LICENSES/BY/4.0/)
NEWS RELEASE
With smartphone videos, clinicians can analyze human movement using open source "OpenCap" platform, 25x faster and at a fraction of the cost of labs.
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Article URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.101XXXX
Article Title: OpenCap: Human movement dynamics from smartphone videos
Author Countries: US
Funding: SDU, AF, LK, JM, ASC, JLH, and SLD were supported by the National Institutes of Health (https://www.nih.gov; grant 1P41EB027060-01A1) and the Wu Tsai Human Performance Alliance (https://humanperformancealliance.org). ASC and MK were supported by Philips Healthcare (https://www.usa.philips.com/healthcare) and the National Institutes of Health (https://www.nih.gov; grant 1R01AR077604-01). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
JOURNAL
PLoS Computational Biology
ARTICLE TITLE
OpenCap: Human movement dynamics from smartphone videos
ARTICLE PUBLICATION DATE
19-Oct-2023
COI STATEMENT
Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: SDU and AF are co-founders of Model Health, Inc., which supports the non-academic, commercial use of the open-source software described here. OpenCap, the cloud-deployed academic version of this open-source software is hosted at Stanford University and will remain freely available to the academic research community for the foreseeable future. No other authors have competing interests to declare.
New smartphone app quickly analyzes human motion to aid physical rehabilitation
NIH-funded researchers suggest app is 25 times faster than current techniques, at a small fraction of the cost
Peer-Reviewed PublicationWHAT:
A research team funded by the National Institutes of Health has developed a smart phone app that can track and analyze a person’s ability to move from one place to another, known as locomotion, and other types of movements. Human motion analysis is used to evaluate patients with movement difficulties, to help clinicians plan surgery, and to assess the results of treatment procedures. The research team believes that using the app costs about 1% of conventional motion analysis techniques and works 25 times faster. The study appears in PLOS Computational Biology.
Researchers tested their app, called OpenCap, with 100 participants. Using two or more smart phones, the app recorded sufficient quality videos to allow for web-based, artificial intelligence analysis of muscle activations, joint loads and joint movements. Data collection took less than 10 hours for the 100 participants, and computation of results took 31 hours. Traditionally, locomotion analysis requires fixed lab space and more than $150,000 worth of equipment, including eight or more specialized cameras to capture three-dimensional images. The captured data also takes several days to analyze by a trained expert.
While current technology is too expensive for routine clinical use, according to the investigators, the app could potentially be used to help screen for disease risk, inform rehabilitation decisions, and track improvements in motion following treatment.
The study was conducted by Scott L. Delp, Ph.D., of Stanford University, and colleagues. NIH funding was provided by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institute of Biomedical Imaging and Bioengineering (NIBIB) and National Institute of Neurological Disorders and Stroke (NINDS).
WHO:
Joseph Bonner, Ph.D., of the NICHD National Center for Medical Rehabilitation Research, is available for comment.
Moira Bittmann, Ph.D., director of the NIBIB program in Medical Simulators, is also available for comment.
ARTICLE:
Uhlrich, SD et al. OpenCap: human movement dynamics from smartphone videos. PLOS Computational Biology. 2023.
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About the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): NICHD leads research and training to understand human development, improve reproductive health, enhance the lives of children and adolescents, and optimize abilities for all. For more information, visit https://www.nichd.nih.gov.
About the National Institute of Biomedical Imaging and Bioengineering (NIBIB): NIBIB’s mission is to improve health by leading the development and accelerating the application of biomedical technologies. The Institute is committed to integrating the physical and engineering sciences with the life sciences to advance basic research and medical care. NIBIB supports emerging technology research and development within its internal laboratories and through grants, collaborations, and training. More information is available at the NIBIB website: https://www.nibib.nih.gov.
About the National Institutes of Health (NIH): NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit https://www.nih.gov.
JOURNAL
PLoS Computational Biology
ARTICLE TITLE
OpenCap: human movement dynamics from smartphone videos
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