Literature DB >> 31787581

Effectiveness of Intervention Based on End-effector Gait Trainer in Older Patients With Stroke: A Systematic Review.

Elvira Maranesi1, Giovanni Renato Riccardi1, Valentina Di Donna2, Mirko Di Rosa3, Paolo Fabbietti3, Riccardo Luzi4, Luigi Pranno5, Fabrizia Lattanzio6, Roberta Bevilacqua7.   

Abstract

OBJECTIVE: The objective of the article is to analyze the effects of the end-effector technology for gait rehabilitation on acute, subacute, and chronic stroke in order to verify the efficacy of the treatment in older people, based on evidence from randomized controlled trials, and thus increase the clinical knowledge for future applications in the hospital setting.
DESIGN: A systematic review of the literature was conducted in October 2018. The data were collected from Cochrane, Embase, Scopus, and PubMed databases, analyzing manuscripts and articles of the last 10 years.
SETTING: We included only randomized controlled trials written in English and aimed to study the effects of end-effector devices in improving walking in stroke patients. We selected 20 studies, and the results were divided into subacute stroke patients and chronic stroke patients. MEASURES: Quality evaluation was performed using the PEDro scale. Of the 10 studies considered, 9 were randomized controlled trials. The PEDro scale score ranged from 7 to 10.
RESULTS: Robotic-assisted gait trainer is more effective for subacute stroke patients with a lower function ambulation assessment, showing significant changes in independent walking ability. One possible explanation of the improvement of the gait speed and functional ambulation is the opportunity of receiving a more intensive and repetitive task-oriented training through end-effector robotic-based intervention. CONCLUSIONS AND IMPLICATIONS: The use of robotic-assisted gait trainer, together with a conventional treatment, seems to improve the walking capability of patients. Future research trials should take into account the impact of the robotic end-effector gait training on the oldest population, as this target was only partially included in the studies examined. Availability of new evidence will support the design of innovative assistive models for the clinical rehabilitation setting, which will take into account the need of personalizing the intervention to support the growing oldest old population.
Copyright © 2019 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Robotics; oldest old person; stroke rehabilitation

Mesh:

Year:  2019        PMID: 31787581     DOI: 10.1016/j.jamda.2019.10.010

Source DB:  PubMed          Journal:  J Am Med Dir Assoc        ISSN: 1525-8610            Impact factor:   4.669


  7 in total

1.  Risk factors for fear of falling in stroke patients: a systematic review and meta-analysis.

Authors:  Qi Xie; Juhong Pei; Ling Gou; Yabin Zhang; Juanping Zhong; Yujie Su; Xinglei Wang; Li Ma; Xinman Dou
Journal:  BMJ Open       Date:  2022-06-30       Impact factor: 3.006

2.  Gait Event Detection for Stroke Patients during Robot-Assisted Gait Training.

Authors:  Andreas Schicketmueller; Juliane Lamprecht; Marc Hofmann; Michael Sailer; Georg Rose
Journal:  Sensors (Basel)       Date:  2020-06-16       Impact factor: 3.576

3.  The Rehabilitation and the Robotics: Are They Going Together Well?

Authors:  Daniele Giansanti
Journal:  Healthcare (Basel)       Date:  2020-12-30

4.  How Many Hours of Device Wear Time Are Required to Accurately Measure Physical Activity Post Stroke?

Authors:  Natalie A Fini; Anne E Holland; Julie Bernhardt; Angela T Burge
Journal:  Int J Environ Res Public Health       Date:  2022-01-21       Impact factor: 3.390

Review 5.  Use of Robotic Devices for Gait Training in Patients Diagnosed with Multiple Sclerosis: Current State of the Art.

Authors:  Sagrario Pérez-de la Cruz
Journal:  Sensors (Basel)       Date:  2022-03-28       Impact factor: 3.576

6.  A systematic review on the usability of robotic and virtual reality devices in neuromotor rehabilitation: patients' and healthcare professionals' perspective.

Authors:  Francesco Zanatta; Anna Giardini; Antonia Pierobon; Marco D'Addario; Patrizia Steca
Journal:  BMC Health Serv Res       Date:  2022-04-20       Impact factor: 2.908

7.  Information Security in Medical Robotics: A Survey on the Level of Training, Awareness and Use of the Physiotherapist.

Authors:  Lisa Monoscalco; Rossella Simeoni; Giovanni Maccioni; Daniele Giansanti
Journal:  Healthcare (Basel)       Date:  2022-01-14
  7 in total

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