Literature DB >> 21674386

Variable structure pantograph mechanism with spring suspension system for comprehensive upper-limb haptic movement training.

Joel C Perry1, Jakob Oblak, Je H Jung, Imre Cikajlo, Jan F Veneman, Nika Goljar, Nataša Bizovičar, Zlatko Matjačić, Thierry Keller.   

Abstract

Numerous haptic devices have been developed for upper-limb neurorehabilitation, but their widespread use has been largely impeded because of complexity and cost. Here, we describe a variable structure pantograph mechanism combined with a spring suspension system that produces a versatile rehabilitation robot, called Universal Haptic Pantograph, for movement training of the shoulder, elbow, and wrist. The variable structure is a 5-degree-of-freedom (DOF) mechanism composed of 7 joints, 11 joint axes, and 3 configurable joint locks that reduce the number of system DOFs to between 0 and 3. The resulting device has eight operational modes: Arm, Wrist, ISO (isometric) 1, ISO 2, Reach, Lift 1, Lift 2, and Steer. The combination of available work spaces (reachable areas) shows a high suitability for movement training of most upper-limb activities of daily living. The mechanism, driven by series elastic actuators, performs similarly in all operational modes, with a single control scheme and set of gains. Thus, a single device with minimal setup changes can be used to treat a variety of upper-limb impairments that commonly afflict veterans with stroke, traumatic brain injury, or other direct trauma to the arm. With appropriately selected design parameters, the developed multimode haptic device significantly reduces the costs of robotic hardware for full-arm rehabilitation while performing similarly to that of single-mode haptic devices. We conducted case studies with three patients with stroke who underwent clinical training using the developed mechanism in Arm, Wrist, and/or Reach operational modes. We assessed outcomes using Fugl-Meyer Motor Assessment and Wolf Motor Function Test scores showing that upper-limb ability improved significantly following training sessions.

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Year:  2011        PMID: 21674386     DOI: 10.1682/jrrd.2010.03.0043

Source DB:  PubMed          Journal:  J Rehabil Res Dev        ISSN: 0748-7711


  2 in total

1.  Virtual Sensors for Advanced Controllers in Rehabilitation Robotics.

Authors:  Aitziber Mancisidor; Asier Zubizarreta; Itziar Cabanes; Eva Portillo; Je Hyung Jung
Journal:  Sensors (Basel)       Date:  2018-03-05       Impact factor: 3.576

2.  The effects of error-augmentation versus error-reduction paradigms in robotic therapy to enhance upper extremity performance and recovery post-stroke: a systematic review.

Authors:  Le Yu Liu; Youlin Li; Anouk Lamontagne
Journal:  J Neuroeng Rehabil       Date:  2018-07-04       Impact factor: 4.262

  2 in total

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