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Sensors 2016, 16(2), 208; doi:10.3390/s16020208

Vision-Based Pose Estimation for Robot-Mediated Hand Telerehabilitation

1
Department of Control and Computer Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin 10129, Italy
2
Institute of Electronics, Computer and Telecommunication Engineering, National Research Council, Corso Duca degli Abruzzi 24, Turin 10129, Italy
3
The BioRobotics Institute, Scuola Superiore Sant’Anna, viale Rinaldo Piaggio 34, Pontedera 56025, Italy
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Yajing Shen
Received: 16 December 2015 / Revised: 27 January 2016 / Accepted: 29 January 2016 / Published: 5 February 2016
(This article belongs to the Special Issue Sensors for Robots)
View Full-Text   |   Download PDF [5164 KB, uploaded 5 February 2016]   |  

Abstract

Vision-based Pose Estimation (VPE) represents a non-invasive solution to allow a smooth and natural interaction between a human user and a robotic system, without requiring complex calibration procedures. Moreover, VPE interfaces are gaining momentum as they are highly intuitive, such that they can be used from untrained personnel (e.g., a generic caregiver) even in delicate tasks as rehabilitation exercises. In this paper, we present a novel master–slave setup for hand telerehabilitation with an intuitive and simple interface for remote control of a wearable hand exoskeleton, named HX. While performing rehabilitative exercises, the master unit evaluates the 3D position of a human operator’s hand joints in real-time using only a RGB-D camera, and commands remotely the slave exoskeleton. Within the slave unit, the exoskeleton replicates hand movements and an external grip sensor records interaction forces, that are fed back to the operator-therapist, allowing a direct real-time assessment of the rehabilitative task. Experimental data collected with an operator and six volunteers are provided to show the feasibility of the proposed system and its performances. The results demonstrate that, leveraging on our system, the operator was able to directly control volunteers’ hands movements. View Full-Text
Keywords: hand telerehabilitation; hand exoskeleton; motion tracking; upper limb rehabilitation hand telerehabilitation; hand exoskeleton; motion tracking; upper limb rehabilitation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Airò Farulla, G.; Pianu, D.; Cempini, M.; Cortese, M.; Russo, L.O.; Indaco, M.; Nerino, R.; Chimienti, A.; Oddo, C.M.; Vitiello, N. Vision-Based Pose Estimation for Robot-Mediated Hand Telerehabilitation. Sensors 2016, 16, 208.

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