Literature DB >> 28796648

Slow Versus Fast Robot-Assisted Locomotor Training After Severe Stroke: A Randomized Controlled Trial.

Thais Amanda Rodrigues1, Daniel Gustavo Goroso, Philip M Westgate, Cheryl Carrico, Linamara R Batistella, Lumy Sawaki.   

Abstract

BACKGROUND AND
PURPOSE: Robot-assisted locomotor training on a bodyweight-supported treadmill is a rehabilitation intervention that compels repetitive practice of gait movements. Standard treadmill speed may elicit rhythmic movements generated primarily by spinal circuits. Slower-than-standard treadmill speed may elicit discrete movements, which are more complex than rhythmic movements and involve cortical areas.
OBJECTIVE: Compare effects of fast (i.e., rhythmic) versus slow (i.e., discrete) robot-assisted locomotor training on a bodyweight-supported treadmill in subjects with chronic, severe gait deficit after stroke.
METHODS: Subjects (N = 18) were randomized to receive 30 sessions (5 d/wk) of either fast or slow robot-assisted locomotor training on a bodyweight-supported treadmill in an inpatient setting. Functional ambulation category, time up and go, 6-min walk test, 10-m walk test, Berg Balance Scale, and Fugl-Meyer Assessment were administered at baseline and postintervention.
RESULTS: The slow group had statistically significant improvement on functional ambulation category (first quartile-third quartile, P = 0.004), 6-min walk test (95% confidence interval [CI] = 1.8 to 49.0, P = 0.040), Berg Balance Scale (95% CI = 7.4 to 14.8, P < 0.0001), time up and go (95% CI = -79.1 to 5.0, P < 0.0030), and Fugl-Meyer Assessment (95% CI = 24.1 to 45.1, P < 0.0001). The fast group had statistically significant improvement on Berg Balance Scale (95% CI = 1.5 to 10.5, P = 0.02).
CONCLUSIONS: In initial stages of robot-assisted locomotor training on a bodyweight-supported treadmill after severe stroke, slow training targeting discrete movement may yield greater benefit than fast training.

Entities:  

Mesh:

Year:  2017        PMID: 28796648     DOI: 10.1097/PHM.0000000000000810

Source DB:  PubMed          Journal:  Am J Phys Med Rehabil        ISSN: 0894-9115            Impact factor:   2.159


  5 in total

1.  Adjustable Parameters and the Effectiveness of Adjunct Robot-Assisted Gait Training in Individuals with Chronic Stroke.

Authors:  Shih-Ching Chen; Jiunn-Horng Kang; Chih-Wei Peng; Chih-Chao Hsu; Yen-Nung Lin; Chien-Hung Lai
Journal:  Int J Environ Res Public Health       Date:  2022-07-04       Impact factor: 4.614

Review 2.  Settings matter: a scoping review on parameters in robot-assisted gait therapy identifies the importance of reporting standards.

Authors:  Florian van Dellen; Rob Labruyère
Journal:  J Neuroeng Rehabil       Date:  2022-04-22       Impact factor: 5.208

3.  Comparisons between Locomat and Walkbot robotic gait training regarding balance and lower extremity function among non-ambulatory chronic acquired brain injury survivors.

Authors:  Hoo Young Lee; Jung Hyun Park; Tae-Woo Kim
Journal:  Medicine (Baltimore)       Date:  2021-05-07       Impact factor: 1.889

4.  Gait training using a stationary, one-leg gait exercise assist robot for chronic stroke hemiplegia: a case report.

Authors:  Norihide Itoh; Daisuke Imoto; Shuichi Kubo; Kota Takahashi; Norikazu Hishikawa; Yasuo Mikami; Toshikazu Kubo
Journal:  J Phys Ther Sci       Date:  2018-07-24

5.  The effect of rehabilitation interventions on physical function and immobility-related complications in severe stroke: a systematic review.

Authors:  Mark P McGlinchey; Jimmy James; Christopher McKevitt; Abdel Douiri; Catherine Sackley
Journal:  BMJ Open       Date:  2020-02-05       Impact factor: 2.692

  5 in total

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