Literature DB >> 32229177

Effects of robotic gait training after stroke: A meta-analysis.

Geoffroy Moucheboeuf1, Romain Griffier2, David Gasq3, Bertrand Glize1, Laurent Bouyer4, Patrick Dehail1, Helene Cassoudesalle5.   

Abstract

BACKGROUND: Robotic devices are often used in rehabilitation and might be efficient to improve walking capacity after stroke.
OBJECTIVE: First to investigate the effects of robot-assisted gait training after stroke and second to explain the observed heterogeneity of results in previous meta-analyses.
METHODS: All randomized controlled trials investigating exoskeletons or end-effector devices in adult patients with stroke were searched in databases (MEDLINE, EMBASE, CENTRAL, CINAHL, OPENGREY, OPENSIGLE, PEDRO, WEB OF SCIENCE, CLINICAL TRIALS, conference proceedings) from inception to November 2019, as were bibliographies of previous meta-analyses, independently by 2 reviewers. The following variables collected before and after the rehabilitation program were gait speed, gait endurance, Berg Balance Scale (BBS), Functional Ambulation Classification (FAC) and Timed Up and Go scores. We also extracted data on randomization method, blinding of outcome assessors, drop-outs, intention (or not) to treat, country, number of participants, disease duration, mean age, features of interventions, and date of outcomes assessment.
RESULTS: We included 33 studies involving 1466 participants. On analysis by subgroups of intervention, as compared with physiotherapy alone, physiotherapy combined with body-weight support training and robot-assisted gait training conferred greater improvement in gait speed (+0.09m/s, 95% confidence interval [CI] 0.03 to 0.15; p=0.002), FAC scores (+0.51, 95% CI 0.07 to 0.95; p=0.022) and BBS scores (+4.16, 95% CI 2.60 to 5.71; p=0.000). A meta-regression analysis suggested that these results were underestimated by the attrition bias of studies.
CONCLUSIONS: Robot-assisted gait training combined with physiotherapy and body-weight support training seems an efficient intervention for gait recovery after stroke.
Copyright © 2020 Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  End-effector; Exoskeleton; Gait; Rehabilitation; Robot-assisted gait training; Stroke; Walking

Mesh:

Year:  2020        PMID: 32229177     DOI: 10.1016/j.rehab.2020.02.008

Source DB:  PubMed          Journal:  Ann Phys Rehabil Med        ISSN: 1877-0657


  8 in total

Review 1.  Efficacy of Overground Robotic Gait Training on Balance in Stroke Survivors: A Systematic Review and Meta-Analysis.

Authors:  Matteo Lorusso; Marco Tramontano; Matteo Casciello; Andrea Pece; Nicola Smania; Giovanni Morone; Federica Tamburella
Journal:  Brain Sci       Date:  2022-05-31

2.  Changes in Balance, Gait and Electroencephalography Oscillations after Robot-Assisted Gait Training: An Exploratory Study in People with Chronic Stroke.

Authors:  Hoon-Ming Heng; Ming-Kuei Lu; Li-Wei Chou; Nai-Hsin Meng; Hui-Chun Huang; Masashi Hamada; Chon-Haw Tsai; Jui-Cheng Chen
Journal:  Brain Sci       Date:  2020-11-06

Review 3.  Effect of robotic-assisted gait training on objective biomechanical measures of gait in persons post-stroke: a systematic review and meta-analysis.

Authors:  Heidi Nedergård; Ashokan Arumugam; Marlene Sandlund; Anna Bråndal; Charlotte K Häger
Journal:  J Neuroeng Rehabil       Date:  2021-04-16       Impact factor: 4.262

4.  Measuring Balance Abilities of Transtibial Amputees Using Multiattribute Utility Theory.

Authors:  Xueyi Zhang; Zhicheng Liu; Guixing Qiu
Journal:  Biomed Res Int       Date:  2021-12-21       Impact factor: 3.411

5.  Effects of Training with a Brain-Computer Interface-Controlled Robot on Rehabilitation Outcome in Patients with Subacute Stroke: A Randomized Controlled Trial.

Authors:  Chen-Guang Zhao; Fen Ju; Wei Sun; Shan Jiang; Xiao Xi; Hong Wang; Xiao-Long Sun; Min Li; Jun Xie; Kai Zhang; Guang-Hua Xu; Si-Cong Zhang; Xiang Mou; Hua Yuan
Journal:  Neurol Ther       Date:  2022-02-16

6.  Relation between Cortical Activation and Effort during Robot-Mediated Walking in Healthy People: A Functional Near-Infrared Spectroscopy Neuroimaging Study (fNIRS).

Authors:  Julien Bonnal; Fanny Monnet; Ba-Thien Le; Ophélie Pila; Anne-Gaëlle Grosmaire; Canan Ozsancak; Christophe Duret; Pascal Auzou
Journal:  Sensors (Basel)       Date:  2022-07-25       Impact factor: 3.847

7.  Hybrid robot-assisted gait training for motor function in subacute stroke: a single-blind randomized controlled trial.

Authors:  Yen-Nung Lin; Shih-Wei Huang; Yi-Chun Kuan; Hung-Chou Chen; Wen-Shan Jian; Li-Fong Lin
Journal:  J Neuroeng Rehabil       Date:  2022-09-14       Impact factor: 5.208

8.  The Effect of Robotic Assisted Gait Training With Lokomat® on Balance Control After Stroke: Systematic Review and Meta-Analysis.

Authors:  Federica Baronchelli; Chiara Zucchella; Mariano Serrao; Domenico Intiso; Michelangelo Bartolo
Journal:  Front Neurol       Date:  2021-07-06       Impact factor: 4.003

  8 in total

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