Affiliation:
1. Scuola Superiore Sant’Anna
Abstract
The adoption of motor-rehabilitative therapies is highly demanded in a society where the average age of the population is constantly increasing. A recent trend to contain costs while providing high quality of healthcare services is to foster the adoption of self-care procedures, performed primarily in patients’ environments rather than in hospitals or healthcare structures, especially in the case of intensive and chronic patients’ rehabilitation.
This work presents a platform to enhance limb functional recovery through telerehabilitation sessions. It relies on a sensing system based on inertial sensors and data fusion algorithms, a module to provide bio-feedback tailored to the users, and a module dedicated to the physicians’ practices. The system design had to face several cyber-physical challenges due to the tight interaction between patient and sensors. For instance, integrating the body kinematics into the sensory processing improved the precision of measurements, simplified the calibration procedure, and made it possible to generate bio-feedback signals. The precision of the proposed system is presented through a set of experiments, showing a resolution below one degree in monitoring joint angles. A validation of the proposed solution has been performed through a medical trial on 50 patients affected by osteo-articular diseases.
The presented framework has been designed to operate in other application fields, such as neurological rehabilitation (e.g., Parkinson, Stroke, etc.), sports training, and fitness activities.
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Control and Optimization,Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction
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