Advancements in markerless motion capture systems for upper limb functional assessment in stroke rehabilitation: A comprehensive review

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.