Alessia Giussani
A Machine Learning Approach for Video-Based Movement Quality Assessment in Tele-Rehabilitation.
Rel. Danilo Demarchi, Paolo Bonato, Giulia Corniani. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2026
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Abstract
Objective: This study aims to develop a framework for the automatic assessment of Tai Chi performance in older adults using video-based analysis, with the goal of enabling scalable, objective monitoring in home-based tele-rehabilitation settings. Background: Aging is associated with a progressive decline in balance and an increased fall risk, a leading cause of injury and lost independence in older adults. While Tai Chi is proven to mitigate these risks, access is often constrained by a scarcity of structured programs. Home-based interventions could address this issue, yet their efficacy is limited by the lack of objective performance assessment, which in turn prevents the delivery of meaningful feedback.
Existing motion analysis systems typically rely on specialized equipment such as marker-based motion capture or wearable sensors, which are impractical for home use
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