Introduction: Motor impairment in Parkinson’s disease (PD) significantly compromises functional independence. While continuous rehabilitation is crucial, traditional models face logistical and economic barriers that limit continuity of treatments. Methods: To address this challenge, we developed a novel exergaming platform leveraging Google MediaPipe for markerless, real-time kinematic tracking via a standard webcam, eliminating the need for specialized hardware and delivering engaging, gamified physical exercises designed for domestic settings. This study investigates the feasibility, usability, and preliminary clinical impact of a 10-session gaming protocol in 14 out-of-hospital patients. Results: The system showed high technical performance and participant engagement, with an overall trial completion rate exceeding 94% and successful progression through game levels. We observed improvements in key functional parameters, establishing a strong correlation between level progression, measured by the novel Normalized Efficiency Index, and the clinical MDSUPDRS assessments, both for total (ρ = −0.61) and mobility (ρ = −0.66) scores. Furthermore, the system detected performance incongruence related to medication timing and motor fluctuations. In addition, a session-by-session analysis revealed consistently high patient satisfaction, engagement, and system usability scores, alongside low perceived physical fatigue. Discussion: These findings underscore the clinical validity and high acceptance of the proposed solution as a training and remote monitoring tool. By providing granular, longitudinal data, this highly accessible solution offers a promising approach to personalized home-based functional training for people with PD.

Digital monitoring of motor function in Parkinson’s disease using Markerless motion analysis and exergaming

Ferraris, Claudia
Primo
;
Amprimo, Gianluca;
2026

Abstract

Introduction: Motor impairment in Parkinson’s disease (PD) significantly compromises functional independence. While continuous rehabilitation is crucial, traditional models face logistical and economic barriers that limit continuity of treatments. Methods: To address this challenge, we developed a novel exergaming platform leveraging Google MediaPipe for markerless, real-time kinematic tracking via a standard webcam, eliminating the need for specialized hardware and delivering engaging, gamified physical exercises designed for domestic settings. This study investigates the feasibility, usability, and preliminary clinical impact of a 10-session gaming protocol in 14 out-of-hospital patients. Results: The system showed high technical performance and participant engagement, with an overall trial completion rate exceeding 94% and successful progression through game levels. We observed improvements in key functional parameters, establishing a strong correlation between level progression, measured by the novel Normalized Efficiency Index, and the clinical MDSUPDRS assessments, both for total (ρ = −0.61) and mobility (ρ = −0.66) scores. Furthermore, the system detected performance incongruence related to medication timing and motor fluctuations. In addition, a session-by-session analysis revealed consistently high patient satisfaction, engagement, and system usability scores, alongside low perceived physical fatigue. Discussion: These findings underscore the clinical validity and high acceptance of the proposed solution as a training and remote monitoring tool. By providing granular, longitudinal data, this highly accessible solution offers a promising approach to personalized home-based functional training for people with PD.
2026
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
AI-assisted rehabilitation
digital medicine
exergaming
Google MediaPipe
markerless body tracking
motion analysis
Parkinson's disease
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/576622
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