Literature DB >> 27914920

Can Lowering the Guidance Force of Robot-Assisted Gait Training Induce a Sufficient Metabolic Demand in Subacute Dependent Ambulatory Patients With Stroke?

So Young Lee1, Eun Young Han2, Bo Ryun Kim1, Min Ho Chun3, Yong Ki Lee1.   

Abstract

OBJECTIVE: To assess the effects of guidance force (GF) and gait speed (GS) on cardiorespiratory responses and energy cost in subacute dependent ambulatory patients with stroke.
DESIGN: Cross-sectional study.
SETTING: University rehabilitation hospital. PARTICIPANTS: Patients with subacute stroke (N=10; mean age, 64.50±19.20y) who were dependent ambulators (functional ambulation category ≤2).
INTERVENTIONS: Patients participated in cardiorespiratory tests during robot-assisted gait training. Subjects walked at a fixed percentage (50%) of body weight support and various percentages of GF (100%, 80%, and 60%) and GS (1.4 and 1.8km/h). The therapist encouraged patients to maximize their locomotor ability. MAIN OUTCOME MEASURES: During the cardiorespiratory tests, oxygen consumption (V˙o2), heart rate, and respiratory exchange ratio were measured continuously to assess cardiometabolic demands.
RESULTS: There were no significant differences in cardiometabolic demands according to GS (1.4 vs 1.8km/h). There were no significant differences in cardiometabolic demands according to GF at a GS of 1.4km/h. However, lowering GF decreased V˙o2 when comparing GFs of 100% (6.89±2.38mL/kg/min), 80% (6.46±1.73mL/kg/min), and 60% (5.77±1.71mL/kg/min) at a GS of 1.8km/h (P=.03).
CONCLUSIONS: Lowering the GF of robot-assisted gait training at a higher GS cannot induce a sufficient cardiometabolic demand for subacute dependent ambulatory patients with stroke. This implies that it is important to take the patient's functional ability into consideration when choosing training protocols.
Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Energy metabolism; Oxygen consumption; Rehabilitation; Robotics; Stroke

Mesh:

Year:  2016        PMID: 27914920     DOI: 10.1016/j.apmr.2016.10.021

Source DB:  PubMed          Journal:  Arch Phys Med Rehabil        ISSN: 0003-9993            Impact factor:   3.966


  3 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

2.  Sports Energy Consumption Evaluation Based on Improved Adaptive Weighted Data Fusion Energy-Saving Algorithm.

Authors:  Ling Han; Yanping Jiang
Journal:  Comput Intell Neurosci       Date:  2022-04-22

3.  Implementation of a gait center training to improve walking ability and vital parameters in inpatient neurological rehabilitation- a cohort study.

Authors:  Stephanie Reichl; Franz Weilbach; Jan Mehrholz
Journal:  J Neuroeng Rehabil       Date:  2020-03-04       Impact factor: 4.262

  3 in total

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