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Energy Expenditure Estimation During Crutch-Orthosis-Assisted Gait of a Spinal-Cord-Injured Subject.
Michaud, Florian; Mouzo, Francisco; Lugrís, Urbano; Cuadrado, Javier.
Afiliação
  • Michaud F; Laboratory of Mechanical Engineering, University of La Coruña, Ferrol, Spain.
  • Mouzo F; Laboratory of Mechanical Engineering, University of La Coruña, Ferrol, Spain.
  • Lugrís U; Laboratory of Mechanical Engineering, University of La Coruña, Ferrol, Spain.
  • Cuadrado J; Laboratory of Mechanical Engineering, University of La Coruña, Ferrol, Spain.
Front Neurorobot ; 13: 55, 2019.
Article em En | MEDLINE | ID: mdl-31379551
ABSTRACT
Determination of muscle energy expenditure by computer modeling and analysis is of great interest to estimate the whole body energy consumption, while avoiding the complex character of in vivo experimental measurements for some subjects or activities. In previous papers, the authors presented optimization methods for estimating muscle forces in spinal-cord-injured (SCI) subjects performing crutch-assisted gait. Starting from those results, this work addresses the estimation of the whole body energy consumption of a SCI subject during crutch-assisted gait using the models of human muscle energy expenditure proposed by Umberger and Bhargava. First, the two methods were applied to the gait of a healthy subject, and experimentally validated by means of a portable gas analyzer in several 5-min tests. Then, both methods were used for a SCI subject during crutch-assisted gait wearing either a passive or an active knee-ankle foot orthosis (KAFO), in order to compare the energetic efficiency of both gait-assistive devices. Improved gait pattern and reduced energy consumption were the results of using the actuated gait device. Computer modeling and analysis can provide valuable indicators, as energy consumption, to assess the impact of assistive devices in patients without the need for long and uncomfortable experimental tests.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article