REHAB 2014

Research Article

A Low Cost Tele-Rehabilitation Device for Training of Wrist and Finger Functions After Stroke

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  • @INPROCEEDINGS{10.4108/icst.pervasivehealth.2014.255331,
        author={Patrick Weiss and Alexander Gabrecht and Thomas M\'{y}nte and Marcus Heldmann and Achim Schweikard and Erik Maehle},
        title={A Low Cost Tele-Rehabilitation Device for Training of Wrist and Finger Functions After Stroke},
        proceedings={REHAB 2014},
        publisher={ICST},
        proceedings_a={REHAB},
        year={2014},
        month={7},
        keywords={robotic rehabilitation tele-rehabilitation stroke wrist and finger functions home health care},
        doi={10.4108/icst.pervasivehealth.2014.255331}
    }
    
  • Patrick Weiss
    Alexander Gabrecht
    Thomas Münte
    Marcus Heldmann
    Achim Schweikard
    Erik Maehle
    Year: 2014
    A Low Cost Tele-Rehabilitation Device for Training of Wrist and Finger Functions After Stroke
    REHAB
    ICST
    DOI: 10.4108/icst.pervasivehealth.2014.255331
Patrick Weiss1,*, Alexander Gabrecht1, Thomas Münte2, Marcus Heldmann2, Achim Schweikard1, Erik Maehle1
  • 1: University of Luebeck
  • 2: University Medical Center Schleswig-Holstein
*Contact email: weiss@iti.uni-luebeck.de

Abstract

There is a need for robotic rehabilitation devices that improve the outcome while reducing the cost of therapy. This paper presents a device for training of supination / pronation, dorsal wrist extension, and finger manipulation after stroke. The system exhibits modularity in terms of the communication architecture and different optional components. User interfaces (UI) can be implemented on different kinds of devices including a Rasperry Pi single-board computer on which a Qt-based graphical UI was run in this instance. Tele-rehabilitation functionality is included using SSL-encrypted RESTful web services on a three-tier architecture. Expensive sensors were omitted in order to have a cost-effective system which is a requirement for home-based rehabilitation. The current-based torque sensing is evaluated by comparing current measurements to force-torque sensor values. After canceling out the static friction, the low error justified the omission of an additional sensor.