Literature DB >> 16249912

Evaluation of robotic training forces that either enhance or reduce error in chronic hemiparetic stroke survivors.

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

Abstract

This investigation is one in a series of studies that address the possibility of stroke rehabilitation using robotic devices to facilitate "adaptive training." Healthy subjects, after training in the presence of systematically applied forces, typically exhibit a predictable "after-effect." A critical question is whether this adaptive characteristic is preserved following stroke so that it might be exploited for restoring function. Another important question is whether subjects benefit more from training forces that enhance their errors than from forces that reduce their errors. We exposed hemiparetic stroke survivors and healthy age-matched controls to a pattern of disturbing forces that have been found by previous studies to induce a dramatic adaptation in healthy individuals. Eighteen stroke survivors made 834 movements in the presence of a robot-generated force field that pushed their hands proportional to its speed and perpendicular to its direction of motion--either clockwise or counterclockwise. We found that subjects could adapt, as evidenced by significant after-effects. After-effects were not correlated with the clinical scores that we used for measuring motor impairment. Further examination revealed that significant improvements occurred only when the training forces magnified the original errors, and not when the training forces reduced the errors or were zero. Within this constrained experimental task we found that error-enhancing therapy (as opposed to guiding the limb closer to the correct path) to be more effective than therapy that assisted the subject.

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Year:  2005        PMID: 16249912     DOI: 10.1007/s00221-005-0097-8

Source DB:  PubMed          Journal:  Exp Brain Res        ISSN: 0014-4819            Impact factor:   1.972


  67 in total

1.  Independent learning of internal models for kinematic and dynamic control of reaching.

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Authors:  Konrad P Körding; Daniel M Wolpert
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Authors:  James L Patton; Ferdinando A Mussa-Ivaldi
Journal:  IEEE Trans Biomed Eng       Date:  2004-04       Impact factor: 4.538

4.  Increasing productivity and quality of care: robot-aided neuro-rehabilitation.

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Journal:  J Rehabil Res Dev       Date:  2000 Nov-Dec

5.  Robot-aided functional imaging: application to a motor learning study.

Authors:  H I Krebs; T Brashers-Krug; S L Rauch; C R Savage; N Hogan; R H Rubin; A J Fischman; N M Alpert
Journal:  Hum Brain Mapp       Date:  1998       Impact factor: 5.038

6.  Quantization of continuous arm movements in humans with brain injury.

Authors:  H I Krebs; M L Aisen; B T Volpe; N Hogan
Journal:  Proc Natl Acad Sci U S A       Date:  1999-04-13       Impact factor: 11.205

7.  Hemiparetic stroke impairs anticipatory control of arm movement.

Authors:  Craig D Takahashi; David J Reinkensmeyer
Journal:  Exp Brain Res       Date:  2003-01-30       Impact factor: 1.972

8.  Providing explicit information disrupts implicit motor learning after basal ganglia stroke.

Authors:  Lara A Boyd; Carolee J Winstein
Journal:  Learn Mem       Date:  2004 Jul-Aug       Impact factor: 2.460

9.  Motor learning in patients with cerebellar dysfunction.

Authors:  J N Sanes; B Dimitrov; M Hallett
Journal:  Brain       Date:  1990-02       Impact factor: 13.501

10.  Cerebellum activation associated with performance change but not motor learning.

Authors:  R D Seidler; A Purushotham; S-G Kim; K Uğurbil; D Willingham; J Ashe
Journal:  Science       Date:  2002-06-14       Impact factor: 47.728

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  135 in total

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

Authors:  Felix C Huang; James L Patton
Journal:  IEEE Int Conf Rehabil Robot       Date:  2011

2.  Augmented dynamics and motor exploration as training for stroke.

Authors:  Felix C Huang; James L Patton
Journal:  IEEE Trans Biomed Eng       Date:  2012-04-03       Impact factor: 4.538

3.  Multijoint arm stiffness during movements following stroke: implications for robot therapy.

Authors:  D Piovesan; M Casadio; F A Mussa-Ivaldi; P G Morasso
Journal:  IEEE Int Conf Rehabil Robot       Date:  2011

4.  Implications of assist-as-needed robotic step training after a complete spinal cord injury on intrinsic strategies of motor learning.

Authors:  Lance L Cai; Andy J Fong; Chad K Otoshi; Yongqiang Liang; Joel W Burdick; Roland R Roy; V Reggie Edgerton
Journal:  J Neurosci       Date:  2006-10-11       Impact factor: 6.167

5.  Toward Restoration of Normal Mechanics of Functional Hand Tasks Post-Stroke: Subject-Specific Approach to Reinforce Impaired Muscle Function.

Authors:  Billy C Vermillion; Alexander W Dromerick; Sang Wook Lee
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2019-06-20       Impact factor: 3.802

6.  Negative viscosity can enhance learning of inertial dynamics.

Authors:  Felix C Huang; James L Patton; Ferdinando A Mussa-Ivaldi
Journal:  IEEE Int Conf Rehabil Robot       Date:  2009-06

7.  Walking flexibility after hemispherectomy: split-belt treadmill adaptation and feedback control.

Authors:  Julia T Choi; Eileen P G Vining; Darcy S Reisman; Amy J Bastian
Journal:  Brain       Date:  2008-12-11       Impact factor: 13.501

Review 8.  Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review.

Authors:  Gert Kwakkel; Boudewijn J Kollen; Hermano I Krebs
Journal:  Neurorehabil Neural Repair       Date:  2007-09-17       Impact factor: 3.919

9.  Robot-Aided Neurorehabilitation: A Pediatric Robot for Ankle Rehabilitation.

Authors:  Konstantinos P Michmizos; Stefano Rossi; Enrico Castelli; Paolo Cappa; Hermano Igo Krebs
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2015-03-06       Impact factor: 3.802

10.  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
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