Literature DB >> 17123205

Custom-designed haptic training for restoring reaching ability to individuals with poststroke hemiparesis.

James L Patton1, Mark Kovic, Ferdinando A Mussa-Ivaldi.   

Abstract

We present an initial test of a technique for retraining reaching skills in patients with poststroke hemiparesis, in which errors are temporarily magnified to encourage learning and compensation. Individuals with poststroke hemiparesis held a horizontal plane robotic manipulandum that could exert a variety of forces while recording patients' movements. We measured how well the patients recovered movement straightness in a single visit to the laboratory (approximately 3 h). Following training, we returned forces to zero for an additional 50 movements to discern if aftereffects lasted. We found that all subjects showed immediate benefit from the training, although 3 of the 10 subjects did not retain these benefits for the remainder of the experiment. We discuss how these approaches demonstrate great potential for rehabilitation tools that augment error to facilitate functional recovery.

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Year:  2006        PMID: 17123205     DOI: 10.1682/jrrd.2005.05.0088

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


  30 in total

1.  Manual skill generalization enhanced by negative viscosity.

Authors:  Felix C Huang; James L Patton; Ferdinando A Mussa-Ivaldi
Journal:  J Neurophysiol       Date:  2010-07-21       Impact factor: 2.714

2.  Minimally assistive robot training for proprioception enhancement.

Authors:  Maura Casadio; Pietro Morasso; Vittorio Sanguineti; Psiche Giannoni
Journal:  Exp Brain Res       Date:  2009-01-13       Impact factor: 1.972

3.  Self-powered robots to reduce motor slacking during upper-extremity rehabilitation: a proof of concept study.

Authors:  Edward P Washabaugh; Emma Treadway; R Brent Gillespie; C David Remy; Chandramouli Krishnan
Journal:  Restor Neurol Neurosci       Date:  2018       Impact factor: 2.406

4.  Organic Haptics: Intersection of Materials Chemistry and Tactile Perception.

Authors:  Darren J Lipomi; Charles Dhong; Cody W Carpenter; Nicholas B Root; Vilayanur S Ramachandran
Journal:  Adv Funct Mater       Date:  2019-10-29       Impact factor: 18.808

5.  Robotic lower limb exoskeletons using proportional myoelectric control.

Authors:  Daniel P Ferris; Cara L Lewis
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

6.  Adaptive robot training for the treatment of incoordination in Multiple Sclerosis.

Authors:  Elena Vergaro; Valentina Squeri; Giampaolo Brichetto; Maura Casadio; Pietro Morasso; Claudio Solaro; Vittorio Sanguineti
Journal:  J Neuroeng Rehabil       Date:  2010-07-29       Impact factor: 4.262

Review 7.  Sensorimotor training in virtual reality: a review.

Authors:  Sergei V Adamovich; Gerard G Fluet; Eugene Tunik; Alma S Merians
Journal:  NeuroRehabilitation       Date:  2009       Impact factor: 2.138

8.  Comparison of error-amplification and haptic-guidance training techniques for learning of a timing-based motor task by healthy individuals.

Authors:  Marie-Hélène Milot; Laura Marchal-Crespo; Christopher S Green; Steven C Cramer; David J Reinkensmeyer
Journal:  Exp Brain Res       Date:  2009-09-29       Impact factor: 1.972

Review 9.  Can robots help the learning of skilled actions?

Authors:  David J Reinkensmeyer; James L Patton
Journal:  Exerc Sport Sci Rev       Date:  2009-01       Impact factor: 6.230

Review 10.  Review of control strategies for robotic movement training after neurologic injury.

Authors:  Laura Marchal-Crespo; David J Reinkensmeyer
Journal:  J Neuroeng Rehabil       Date:  2009-06-16       Impact factor: 4.262

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