Lonini L, Moon Y, Embry K, Cotton RJ, McKenzie K, Jenz S, et al. Video-Based Pose Estimation for Gait Analysis in Stroke Survivors during Clinical Assessments: A Proof-of-Concept Study. Digital Biomarkers. 2022;6:9–18. DOI 10.1159/000520732
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DOI: 10.1159/000520732
Bibliographic record from the original reports
Access labels embedded in these original reference strings are historical. Current access and exact checked components are stated separately below.
Lonini L, Moon Y, Embry K, Cotton RJ, McKenzie K, Jenz S, et al. Video-Based Pose Estimation for Gait Analysis in Stroke Survivors during Clinical Assessments: A Proof-of-Concept Study. Digital Biomarkers. 2022;6:9–18. DOI 10.1159/000520732 Source examined: Abstract and original-study details in later primary source.
Conditions: COND-STROKE Stroke
Scoped audit evidence
These are source- and component-level audit summaries as of 3 October 2026. Access and comparison scope can differ by report; none certifies every result or the underlying raw data.
Stroke gait — gait
- current access statement: Current audit access: full_body. Prior claims of licensed reading are not re-certified merely from present availability.
- source access: full_body
The complete PMC body confirms eight chronic stroke participants and a custom DeepLabCut/ResNet 50 model trained on 82 videos, followed by a separate temporal-parameter CNN. It does not validate unrelated applications.
Source locator: audit evidence record L104–105,Methods,Results and Discussion L427–431
Limitations: The current body recovery updates access. Historical prior incomplete retrieval is not contradicted or re-certified.
Linked audit findings
Reports citing this source
- Gait assessment and prognosis after stroke · reference 53 · original reference
Update record
- 2026-10-03: Created from the supplied reports and final scoped audit. New evidence should be appended with source version, access date, exact locator and affected report links.
Updating the wiki · Evidence and status guide
Linked knowledge pages
- TEST-MARKERLESS Markerless and video gait analysis