Literature DB >> 19158061

Functional restoration for the stroke survivor: informing the efforts of engineers.

James Patton1, Steven L Small, William Zev Rymer.   

Abstract

As bioengineers begin to notice the importance of therapy in the recovery from stroke and other brain injuries, new technologies will be increasingly conceived, adapted, and designed to improve the patient's road to recovery. What is clear from engineering history, however, is that the best engineering efforts are often built on strong scientific foundations. In an effort to inform engineers with the necessary background on cutting edge research in the field of stroke and motor recovery, this article summarizes the views of several experts in the field as a result of a workshop held in 2006 on the topic. Here we elaborate on several areas relevant to this goal, including the pathophysiology of stroke and stroke recovery, the biomechanics, the secondary peripheral changes in muscle and other tissue, and the results of neuroimaging studies. One conclusion is that the current state of knowledge is now ripe for research using machines but that highly sophisticated robotic devices may not yet be needed. Instead, what may be needed is basic evidence that shows a difference in one therapeutic strategy over another.

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Mesh:

Year:  2008        PMID: 19158061      PMCID: PMC2703465          DOI: 10.1310/tsr1506-521

Source DB:  PubMed          Journal:  Top Stroke Rehabil        ISSN: 1074-9357            Impact factor:   2.119


  34 in total

1.  Robot training enhanced motor outcome in patients with stroke maintained over 3 years.

Authors:  B T Volpe; H I Krebs; N Hogan; L Edelsteinn; C M Diels; M L Aisen
Journal:  Neurology       Date:  1999-11-10       Impact factor: 9.910

2.  Learning of action through adaptive combination of motor primitives.

Authors:  K A Thoroughman; R Shadmehr
Journal:  Nature       Date:  2000-10-12       Impact factor: 49.962

3.  Learning to move amid uncertainty.

Authors:  R A Scheidt; J B Dingwell; F A Mussa-Ivaldi
Journal:  J Neurophysiol       Date:  2001-08       Impact factor: 2.714

4.  Enhancement of use-dependent plasticity by D-amphetamine.

Authors:  L Sawaki; L G Cohen; J Classen; B C Davis; C M Bütefisch
Journal:  Neurology       Date:  2002-10-22       Impact factor: 9.910

5.  Spastic muscle cells are shorter and stiffer than normal cells.

Authors:  Jan Fridén; Richard L Lieber
Journal:  Muscle Nerve       Date:  2003-02       Impact factor: 3.217

6.  Treadmill training of paraplegic patients using a robotic orthosis.

Authors:  G Colombo; M Joerg; R Schreier; V Dietz
Journal:  J Rehabil Res Dev       Date:  2000 Nov-Dec

7.  Trends in stroke prevalence between 1973 and 1991 in the US population 25 to 74 years of age.

Authors:  Paul Muntner; Elizabeth Garrett; Michael J Klag; Josef Coresh
Journal:  Stroke       Date:  2002-05       Impact factor: 7.914

8.  Measuring quality of life in a way that is meaningful to stroke patients.

Authors:  L S Williams; M Weinberger; L E Harris; J Biller
Journal:  Neurology       Date:  1999-11-10       Impact factor: 9.910

9.  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

10.  Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke.

Authors:  Peter S Lum; Charles G Burgar; Peggy C Shor; Matra Majmundar; Machiel Van der Loos
Journal:  Arch Phys Med Rehabil       Date:  2002-07       Impact factor: 3.966

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  8 in total

1.  Analysis of the Leap Motion Controller's Performance in Measuring Wrist Rehabilitation Tasks Using an Industrial Robot Arm Reference.

Authors:  Rogério S Gonçalves; Marcus R S B de Souza; Giuseppe Carbone
Journal:  Sensors (Basel)       Date:  2022-06-28       Impact factor: 3.847

2.  A portable assist-as-need upper-extremity hybrid exoskeleton for FES-induced muscle fatigue reduction in stroke rehabilitation.

Authors:  Ashley Stewart; Christopher Pretty; Xiaoqi Chen
Journal:  BMC Biomed Eng       Date:  2019-11-19

Review 3.  A survey on robotic devices for upper limb rehabilitation.

Authors:  Paweł Maciejasz; Jörg Eschweiler; Kurt Gerlach-Hahn; Arne Jansen-Troy; Steffen Leonhardt
Journal:  J Neuroeng Rehabil       Date:  2014-01-09       Impact factor: 4.262

4.  Collaborative robotic biomechanical interactions and gait adjustments in young, non-impaired individuals.

Authors:  Valdeci C Dionisio; David A Brown
Journal:  J Neuroeng Rehabil       Date:  2016-06-16       Impact factor: 4.262

5.  Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients.

Authors:  Alessandro Panarese; Elvira Pirondini; Peppino Tropea; Benedetta Cesqui; Federico Posteraro; Silvestro Micera
Journal:  J Neuroeng Rehabil       Date:  2016-09-08       Impact factor: 4.262

6.  Translation of robot-assisted rehabilitation to clinical service: a comparison of the rehabilitation effectiveness of EMG-driven robot hand assisted upper limb training in practical clinical service and in clinical trial with laboratory configuration for chronic stroke.

Authors:  Yanhuan Huang; Will Poyan Lai; Qiuyang Qian; Xiaoling Hu; Eric W C Tam; Yongping Zheng
Journal:  Biomed Eng Online       Date:  2018-06-25       Impact factor: 2.819

7.  A Case Study of Upper Limb Robotic-Assisted Therapy Using the Track-Hold Device.

Authors:  Marco Righi; Massimo Magrini; Cristina Dolciotti; Davide Moroni
Journal:  Sensors (Basel)       Date:  2022-01-28       Impact factor: 3.576

8.  Fusion of Haptic and Gesture Sensors for Rehabilitation of Bimanual Coordination and Dexterous Manipulation.

Authors:  Ningbo Yu; Chang Xu; Huanshuai Li; Kui Wang; Liancheng Wang; Jingtai Liu
Journal:  Sensors (Basel)       Date:  2016-03-18       Impact factor: 3.576

  8 in total

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