Vision-Based Pose Estimation for Robot-Mediated Hand Telerehabilitation
Identifieur interne : 000573 ( Pmc/Corpus ); précédent : 000572; suivant : 000574Vision-Based Pose Estimation for Robot-Mediated Hand Telerehabilitation
Auteurs : Giuseppe Air Farulla ; Daniele Pianu ; Marco Cempini ; Mario Cortese ; Ludovico O. Russo ; Marco Indaco ; Roberto Nerino ; Antonio Chimienti ; Calogero M. Oddo ; Nicola VitielloSource :
- Sensors (Basel, Switzerland) [ 1424-8220 ] ; 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.
Url:
DOI: 10.3390/s16020208
PubMed: 26861333
PubMed Central: 4801584
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