Lam WW, Ang WT, Fong KN. Prediction for prospective falls via gait evaluation using mobile devices for stroke survivors: A markerless motion analysis study. Clinical rehabilitation. 2026;40(7):959-971. DOI 10.1177/02692155251414356
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DOI: 10.1177/02692155251414356
Bibliographic record from the original reports
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Lam WW, Ang WT, Fong KN. Prediction for prospective falls via gait evaluation using mobile devices for stroke survivors: A markerless motion analysis study. Clinical rehabilitation. 2026;40(7):959-971. DOI 10.1177/02692155251414356 Source examined: Final accepted manuscript and publisher abstract.
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: accepted_manuscript_body. Prior claims of licensed reading are not re-certified merely from present availability.
- source access: accepted_manuscript_body
Fifty enrolled and 46 analysed; mean 72.3 months; three 3 m usual-speed walks and three iPads. The abstract gives 13% fallers, while Table 1 gives 6 single and 2 recurrent fallers. Combined AUC 0.81, sensitivity 0.84, specificity 0.79.
Source locator: Primary accepted manuscript pp4–10,23–28; Table1 p23; Table3 pp25–27; publisher abstract
Limitations: The report accurately flags a source discrepancy. If categories are disjoint, 8/46=17.39%. Stepwise modelling and confidence-interval/p-value conflicts are visible. Prior cited validation is upper-limb kinematics, reference 19. Publisher final body not obtained.
Reports citing this source
- Gait assessment and prognosis after stroke · reference 29 · 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