Remote Monitoring of Rehabilitation Exercises Through Motion Assessment

Telerehabilitation is a promising solution to ensure continuity of care for people with disabilities by delivering rehabilitation services directly in their homes or other familiar environments. This paper introduces a method for assessing movement execution during telerehabilitation sessions, offering effective support to clinicians during remote monitoring. This approach uses the 3D coordinates of the body joints provided by Microsoft Kinect to evaluate movement based on joint positions and angles. The proposed method identifies key deviations from expected movement patterns and generates graphical feedback to support the clinical evaluation of patients' performance. This system has been validated using the IntelliRehabDS dataset, which includes rehabilitation exercises designed for different pathologies. Preliminary results demonstrate the system's ability to detect deviations from the reference movement pattern, highlighting its potential as a practical tool to enhance remote rehabilitation monitoring.

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Published
2025-06-18
DOI
https://doi.org/10.1109/cbms65348.2025.00121
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
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article

Remote Monitoring of Rehabilitation Exercises Through Motion Assessment

Giovanna Sannino, Ilaria Basile
Context-Aware Activity Recognition Systems
article

Remote Monitoring of Rehabilitation Exercises Through Motion Assessment

Giovanna Sannino, Ilaria Basile
article en

Abstract

Telerehabilitation is a promising solution to ensure continuity of care for people with disabilities by delivering rehabilitation services directly in their homes or other familiar environments. This paper introduces a method for assessing movement execution during telerehabilitation sessions, offering effective support to clinicians during remote monitoring. This approach uses the 3D coordinates of the body joints provided by Microsoft Kinect to evaluate movement based on joint positions and angles. The proposed method identifies key deviations from expected movement patterns and generates graphical feedback to support the clinical evaluation of patients' performance. This system has been validated using the IntelliRehabDS dataset, which includes rehabilitation exercises designed for different pathologies. Preliminary results demonstrate the system's ability to detect deviations from the reference movement pattern, highlighting its potential as a practical tool to enhance remote rehabilitation monitoring.

Institute for High Performance Computing and Networking (IT), National Research Council (IT)
Openalex Percentile: Top 86%
Context-Aware Activity Recognition Systems
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Remote Monitoring of Rehabilitation Exercises Through Motion Assessment — Giovanna Sannino, Ilaria Basile · (2025) | TGRS Research Map | TGRS