Literature DB >> 26736537

Multivariate outcomes in a three week bimanual self-telerehabilitation with error augmentation post-stroke.

Yazan Abdel Majeed, Farnaz Abdollahi, Saria Awadalla, James Patton.   

Abstract

We present the outcomes of a study on stroke patients in a 3-week intervention of bimanual self-telerehabilitation. This training is similar to an upper-extremity treadmill in that patients can make use of their healthy arm to provide a cue for the more impaired arm. We further inspected a cohort that covertly received error augmentation training while they practiced. Finally, we focused here on the many quantitative measures available from the robotic device, testing if these measures collectively can predict outcome on the final day. We found in a cross-validation study that predictions are possible, yielding median r-squared values over 99%. Several particular measures were found to dominate their contribution to the prediction of recoverability. These results show that interactive self-rehabilitation may be a viable method for motor restoration, and the quantitative metrics available can be used to predict the eventual state of recovery.

Entities:  

Mesh:

Year:  2015        PMID: 26736537      PMCID: PMC8682913          DOI: 10.1109/EMBC.2015.7318637

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  37 in total

1.  Forced use of the upper extremity in chronic stroke patients: results from a single-blind randomized clinical trial.

Authors:  J H van der Lee; R C Wagenaar; G J Lankhorst; T W Vogelaar; W L Devillé; L M Bouter
Journal:  Stroke       Date:  1999-11       Impact factor: 7.914

2.  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

3.  A body-powered functional upper limb orthosis.

Authors:  T Rahman; W Sample; R Seliktar; M Alexander; M Scavina
Journal:  J Rehabil Res Dev       Date:  2000 Nov-Dec

4.  Constrained and unconstrained movements involve different control strategies.

Authors:  M Desmurget; M Jordan; C Prablanc; M Jeannerod
Journal:  J Neurophysiol       Date:  1997-03       Impact factor: 2.714

5.  The Motor Activity Log-28: assessing daily use of the hemiparetic arm after stroke.

Authors:  G Uswatte; E Taub; D Morris; K Light; P A Thompson
Journal:  Neurology       Date:  2006-10-10       Impact factor: 9.910

6.  Fine motor control in adults with and without chronic hemiparesis: baseline comparison to nondisabled adults and effects of bilateral arm training.

Authors:  Sandy McCombe Waller; Jill Whitall
Journal:  Arch Phys Med Rehabil       Date:  2004-07       Impact factor: 3.966

7.  Intensive sensorimotor arm training mediated by therapist or robot improves hemiparesis in patients with chronic stroke.

Authors:  Bruce T Volpe; Daniel Lynch; Avrielle Rykman-Berland; Mark Ferraro; Michael Galgano; Neville Hogan; Hermano I Krebs
Journal:  Neurorehabil Neural Repair       Date:  2008-01-09       Impact factor: 3.919

8.  Reproducibility and minimal detectable change of three-dimensional kinematic analysis of reaching tasks in people with hemiparesis after stroke.

Authors:  Joanne M Wagner; Jennifer A Rhodes; Carolynn Patten
Journal:  Phys Ther       Date:  2008-03-06

9.  Robot-assisted arm trainer for the passive and active practice of bilateral forearm and wrist movements in hemiparetic subjects.

Authors:  Stefan Hesse; Gotthard Schulte-Tigges; Matthias Konrad; Anita Bardeleben; Cordula Werner
Journal:  Arch Phys Med Rehabil       Date:  2003-06       Impact factor: 3.966

10.  Error augmentation enhancing arm recovery in individuals with chronic stroke: a randomized crossover design.

Authors:  Farnaz Abdollahi; Emily D Case Lazarro; Molly Listenberger; Robert V Kenyon; Mark Kovic; Ross A Bogey; Donald Hedeker; Borko D Jovanovic; James L Patton
Journal:  Neurorehabil Neural Repair       Date:  2013-08-08       Impact factor: 3.919

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  3 in total

1.  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.  Key components of mechanical work predict outcomes in robotic stroke therapy.

Authors:  Zachary A Wright; Yazan A Majeed; James L Patton; Felix C Huang
Journal:  J Neuroeng Rehabil       Date:  2020-04-21       Impact factor: 4.262

3.  Regression techniques employing feature selection to predict clinical outcomes in stroke.

Authors:  Yazan Abdel Majeed; Saria S Awadalla; James L Patton
Journal:  PLoS One       Date:  2018-10-19       Impact factor: 3.240

  3 in total

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