A multi-sensors wearable system for remote assessment of physiotherapy exercises during ACL rehabilitation
Tedesco, Salvatore; Belcastro, Marco; Manzano Torre, Oscar; Torchia, Pasqualino; Alfieri, Davide; Khokhlova, Liudmila; O'Flynn, Brendan
Date:
2019-11
Copyright:
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Citation:
Tedesco, S., Belcastro, M., Torre, O. M., Torchia, P., Alfieri, D., Khokhlova, L. and O'Flynn, B. (2019) 'A Multi-Sensors Wearable System for Remote Assessment of Physiotherapy Exercises during ACL Rehabilitation', 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS), Genoa, Italy, 27-29 November, pp. 237-240. doi: 10.1109/ICECS46596.2019.8965214
Abstract:
In this paper, the challenges associated with the design of a novel multi-sensor wearable system for the objective assessment of exercises during lower-limbs rehabilitation are described. The overall system architecture is defined, and finally both the implemented hardware and software platforms are illustrated in detail. Multiple sensing technologies are adopted including motion data, electromyography measurements, and muscle electro-stimulation. The software stack provides guidance to the users throughout the rehabilitation therapy sessions, and allows clinicians to access the data collected remotely in real-time thus supporting their clinical evaluation. Finally, preliminary results of the comparison between the knee joint angle estimated by the developed system against a gold-standard inertial-based system are provided showing promising results for future validation.
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