Literature DB >> 22275710

Evaluation of negative viscosity as upper extremity training for stroke survivors.

Felix C Huang1, James L Patton.   

Abstract

With stroke survivors (n=30) as the test population, we investigated how upper extremity training with negative viscosity affects coordination in unassisted conditions. Using a planar force-feedback device, subjects performed exploratory movements within an environment that simulated 1) negative viscosity added to elbow and shoulder joints 2) augmented inertia to the upper and lower arm combined with negative viscosity, or 3) a null force field (control). After training, we evaluated each subject's ability to perform circular movements in the null field. Negative viscosity training resulted in greater within-day reductions in error compared with the combined field training. Negative viscosity promoted greater distributions of accelerations during free exploration, especially in the sagittal axis, while combined field training diminished overall activity. Both force field training groups exhibited next day retention, while this was not observed for the control group. The improvement in performance suggests that greater range of kinematic experiences contribute to learning, even despite novel force field environments. These findings provide support for the use of movement amplifying environments for upper extremity rehabilitation, allowing greater access to training while maintaining user engagement.
© 2011 IEEE

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Year:  2011        PMID: 22275710      PMCID: PMC4927076          DOI: 10.1109/ICORR.2011.5975514

Source DB:  PubMed          Journal:  IEEE Int Conf Rehabil Robot        ISSN: 1945-7898


  28 in total

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2.  Motor learning elicited by voluntary drive.

Authors:  Martin Lotze; Christoph Braun; Niels Birbaumer; Silke Anders; Leonardo G Cohen
Journal:  Brain       Date:  2003-04       Impact factor: 13.501

3.  Robot-assisted adaptive training: custom force fields for teaching movement patterns.

Authors:  James L Patton; Ferdinando A Mussa-Ivaldi
Journal:  IEEE Trans Biomed Eng       Date:  2004-04       Impact factor: 4.538

4.  The interference effects of non-rotated versus counter-rotated trials in visuomotor adaptation.

Authors:  Mark R Hinder; Laura Walk; Daniel G Woolley; Stephan Riek; Richard G Carson
Journal:  Exp Brain Res       Date:  2007-02-14       Impact factor: 1.972

5.  Robot-enhanced motor learning: accelerating internal model formation during locomotion by transient dynamic amplification.

Authors:  Jeremy L Emken; David J Reinkensmeyer
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2005-03       Impact factor: 3.802

6.  Modular decomposition in visuomotor learning.

Authors:  Z Ghahramani; D M Wolpert
Journal:  Nature       Date:  1997-03-27       Impact factor: 49.962

7.  Use-dependent and error-based learning of motor behaviors.

Authors:  Jörn Diedrichsen; Olivier White; Darren Newman; Níall Lally
Journal:  J Neurosci       Date:  2010-04-14       Impact factor: 6.167

Review 8.  Robot-assisted movement training for the stroke-impaired arm: Does it matter what the robot does?

Authors:  Leonard E Kahn; Peter S Lum; W Zev Rymer; David J Reinkensmeyer
Journal:  J Rehabil Res Dev       Date:  2006 Aug-Sep

9.  Effects of cognitive processes and task complexity on acquisition, retention, and transfer of motor skills.

Authors:  T Jarus; T Gutman
Journal:  Can J Occup Ther       Date:  2001-12       Impact factor: 1.614

10.  The transition to reaching: mapping intention and intrinsic dynamics.

Authors:  E Thelen; D Corbetta; K Kamm; J P Spencer; K Schneider; R F Zernicke
Journal:  Child Dev       Date:  1993-08
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  9 in total

1.  Individual patterns of motor deficits evident in movement distribution analysis.

Authors:  Felix C Huang; James L Patton
Journal:  IEEE Int Conf Rehabil Robot       Date:  2013-06

2.  Robot Training With Vector Fields Based on Stroke Survivors' Individual Movement Statistics.

Authors:  Zachary A Wright; Emily Lazzaro; Kelly O Thielbar; James L Patton; Felix C Huang
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2017-10-16       Impact factor: 3.802

3.  Effects of the Alternate Combination of "Error-Enhancing" and "Active Assistive" Robot-Mediated Treatments on Stroke Patients.

Authors:  Peppino Tropea; Benedetta Cesqui; Vito Monaco; Sara Aliboni; Federico Posteraro; Silvestro Micera
Journal:  IEEE J Transl Eng Health Med       Date:  2013-07-24       Impact factor: 3.316

4.  A Portable Passive Rehabilitation Robot for Upper-Extremity Functional Resistance Training.

Authors:  Edward Washabaugh; Jane Guo; Chih-Kang Chang; David Remy; Chandramouli Krishnan
Journal:  IEEE Trans Biomed Eng       Date:  2018-06-21       Impact factor: 4.538

5.  Simulation of variable impedance as an intervention for upper extremity motor exploration.

Authors:  Felix C Huang
Journal:  IEEE Int Conf Rehabil Robot       Date:  2017-07

6.  Movement distributions of stroke survivors exhibit distinct patterns that evolve with training.

Authors:  Felix C Huang; James L Patton
Journal:  J Neuroeng Rehabil       Date:  2016-03-09       Impact factor: 4.262

7.  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

Review 8.  Human-machine-human interaction in motor control and rehabilitation: a review.

Authors:  Emek Barış Küçüktabak; Sangjoon J Kim; Yue Wen; Kevin Lynch; Jose L Pons
Journal:  J Neuroeng Rehabil       Date:  2021-12-27       Impact factor: 4.262

9.  Effect of Position- and Velocity-Dependent Forces on Reaching Movements at Different Speeds.

Authors:  Susanna Summa; Maura Casadio; Vittorio Sanguineti
Journal:  Front Hum Neurosci       Date:  2016-11-29       Impact factor: 3.169

  9 in total

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