Literature DB >> 31078010

Spatiotemporal gait characteristic changes with gait training using the hybrid assistive limb for chronic stroke patients.

Hiroki Tanaka1, Manabu Nankaku2, Toru Nishikawa2, Takuya Hosoe2, Honami Yonezawa2, Hiroki Mori2, Takayuki Kikuchi3, Hidehisa Nishi3, Yasushi Takagi4, Susumu Miyamoto3, Ryosuke Ikeguchi5, Shuichi Matsuda5.   

Abstract

BACKGROUND: Robotic rehabilitation has been attracting attention as a means to carry out "intensive", "repetitive", "task-specific", gait training. The newly developed robotic device, the Hybrid Assistive Limb (HAL), is thought to have the possibility of having an excellent effect on gait speed improvement over the conventional automatic programed assist robot. The purpose of this study was to investigate the spatiotemporal characteristics related to gait speed improvement using the HAL in chronic stroke patients. RESEARCH QUESTION: To investigate the effects of robotic gait training on gait speed and gait parameters.
METHODS: An observational study with an intervention for single group was used. Intervention was conducted in University Hospital. Eleven chronic stroke patients were enrolled in this study. The patients performed 8 gait training sessions using the HAL, 2-5 sessions/week for 3 weeks. Gait speed, stride length, cadence, time of gait cycle (double-limb stance phases and single-limb stance phases) and time asymmetry index were measured before and after intervention.
RESULTS: After intervention, gait speed, stride length, and cadence were significantly improved (Effect size = 0.39, 0.29, and 0.29), the affected initial double-limb stance phase was significantly shortened (from 15.8 ± 3.46%-13.3 ± 4.20%, p =  .01), and the affected single-limb stance phase was significantly lengthened (from 21.8±7.02%-24.5±7.95%, p <  .01). The time asymmetry index showed a tendency to improve after intervention (from 22.9±11.8-17.6±9.62, p =  .06). There was a significant correlation between gait speed and the stride length increase rate (r = .72, p =  .01). SIGNIFICANCE: This study showed that increasing stride length with lengthening of the affected single-stance phase by gait training using the HAL improved gait speed in chronic stroke patients. However, the actual contributions on HAL cannot be separated from gait training because this study is an observational research without a control group.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Chronic stroke; Gait cycle; Gait speed; Robotics rehabilitation; The hybrid assistive limb

Mesh:

Year:  2019        PMID: 31078010     DOI: 10.1016/j.gaitpost.2019.05.003

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  5 in total

1.  Effects of control strategies on gait in robot-assisted post-stroke lower limb rehabilitation: a systematic review.

Authors:  Robert Riener; Maria Chiara Carrozza; Silvia Campagnini; Piergiuseppe Liuzzi; Andrea Mannini
Journal:  J Neuroeng Rehabil       Date:  2022-06-03       Impact factor: 5.208

2.  Occurrence and Type of Adverse Events During the Use of Stationary Gait Robots-A Systematic Literature Review.

Authors:  Jule Bessler; Gerdienke B Prange-Lasonder; Robert V Schulte; Leendert Schaake; Erik C Prinsen; Jaap H Buurke
Journal:  Front Robot AI       Date:  2020-11-16

3.  Effect of hybrid assistive limb treatment on maximal walking speed and six-minute walking distance during stroke rehabilitation: a pilot study.

Authors:  Hiroki Watanabe; Hideo Tsurushima; Hisako Yanagi
Journal:  J Phys Ther Sci       Date:  2021-02-13

4.  Influence of hybrid assistive limb gait training on spatial muscle activation patterns in spinal muscular atrophy type III.

Authors:  Yuichi Nishikawa; Kohei Watanabe; Naoya Orita; Noriaki Maeda; Hiroaki Kimura; Shinobu Tanaka; Allison Hyngstrom
Journal:  F1000Res       Date:  2021-03-16

5.  Two-Month Individually Supervised Exercise Therapy Improves Walking Speed, Step Length, and Temporal Gait Symmetry in Chronic Stroke Patients: A before-after Trial.

Authors:  Kiyoshi Yoshioka; Tatsunori Watanabe; Norikazu Maruyama; Mizuki Yoshioka; Keita Iino; Kimikazu Honda; Koshiro Hayashida
Journal:  Healthcare (Basel)       Date:  2022-03-14
  5 in total

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