'Assessments' NEVER GET YOU RECOVERED! You need EXACT PROTOCOLS for that, and this doesn't do that; SO FUCKING USELESS!
Advancements in markerless motion capture systems for upper limb functional assessment in stroke rehabilitation: A comprehensive review
sPadmavathi Shenoy1 ,S.Meenatchi Sundaram1
DIGITAL HEALTH
Volume 12: 1–27
© The Author(s) 2026
Article reuse guidelines:
sagepub.com/journals-permissions
DOI: 10.1177/20552076251412636
journals.sagepub.com/home/dhj
,Senthil Kumaran D2
Manikandan Natarajan2 andSucheta Kolekar3 ,
Abstract
Stroke frequently leads to upper limb impairment, requiring precise evaluation to guide effective rehabilitation.
Markerless motion-capture technologies have emerged as promising, noninvasive tools for objective and quantitative
movement assessment. This comprehensive review summarizes advancements in markerless motion-capture systems
for upper limb functional assessment in stroke rehabilitation and identifies current limitations and future opportunities.
Relevant studies published between 2012 and 2025 were identified through PubMed, Scopus, IEEE Xplore, and Web of
Science databases using search terms related to stroke, upper-limb motion, and markerless motion capture. Recent systems such as OpenPose, MediaPipe, and Theia3D demonstrate reliable kinematic accuracy (mean error <6°) and feasibility for remote rehabilitation monitoring. However, variations in study protocols, small sample sizes, and limited
clinical validation continue to hinder widespread clinical adoption. Markerless motion capture provides an accessible
and objective approach for assessing upper-limb function after stroke. Future work should focus on standardizing validation procedures, improving real-time performance, and integrating these systems into routine clinical and telerehabilitation workflows.
Keywords
Markerless motion capture, stroke rehabilitation, machine learning, kinematic analysis, telerehabilitation
Received: 28 August 2025; accepted: 18 November 2025
No comments:
Post a Comment