With smartphone videos, clinicians can analyze human movement using open source “OpenCap” platform, 25x faster and at a fraction of the cost of labs.
Credit: Ulrich et al., 2023, PLOS Computational Biology, CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)
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
DOI
10.1371/journal.pcbi.1011462
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.