Literature DB >> 25257873

Estimating instantaneous energetic cost during non-steady-state gait.

Jessica C Selinger1, J Maxwell Donelan2.   

Abstract

Respiratory measures of oxygen and carbon dioxide are routinely used to estimate the body's steady-state metabolic energy use. However, slow mitochondrial dynamics, long transit times, complex respiratory control mechanisms, and high breath-by-breath variability obscure the relationship between the body's instantaneous energy demands (instantaneous energetic cost) and that measured from respiratory gases (measured energetic cost). The purpose of this study was to expand on traditional methods of assessing metabolic cost by estimating instantaneous energetic cost during non-steady-state conditions. To accomplish this goal, we first imposed known changes in energy use (input), while measuring the breath-by-breath response (output). We used these input/output relationships to model the body as a dynamic system that maps instantaneous to measured energetic cost. We found that a first-order linear differential equation well approximates transient energetic cost responses during gait. Across all subjects, model fits were parameterized by an average time constant (τ) of 42 ± 12 s with an average R(2) of 0.94 ± 0.05 (mean ± SD). Armed with this input/output model, we next tested whether we could use it to reliably estimate instantaneous energetic cost from breath-by-breath measures under conditions that simulated dynamically changing gait. A comparison of the imposed energetic cost profiles and our estimated instantaneous cost demonstrated a close correspondence, supporting the use of our methodology to study the role of energetics during locomotor adaptation and learning.
Copyright © 2014 the American Physiological Society.

Entities:  

Keywords:  adaptation; energetics; gait; indirect calorimetry; metabolic cost

Mesh:

Year:  2014        PMID: 25257873     DOI: 10.1152/japplphysiol.00445.2014

Source DB:  PubMed          Journal:  J Appl Physiol (1985)        ISSN: 0161-7567


  22 in total

1.  Contribution of blood oxygen and carbon dioxide sensing to the energetic optimization of human walking.

Authors:  Jeremy D Wong; Shawn M O'Connor; Jessica C Selinger; J Maxwell Donelan
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2.  Evaluating physiological signal salience for estimating metabolic energy cost from wearable sensors.

Authors:  Kimberly A Ingraham; Daniel P Ferris; C David Remy
Journal:  J Appl Physiol (1985)       Date:  2019-01-10

3.  Foot contact forces can be used to personalize a wearable robot during human walking.

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Journal:  Sci Rep       Date:  2022-06-29       Impact factor: 4.996

4.  Metabolically efficient walking assistance using optimized timed forces at the waist.

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Journal:  Sci Robot       Date:  2022-03-16

5.  Characterizing the relationship between peak assistance torque and metabolic cost reduction during running with ankle exoskeletons.

Authors:  Delaney E Miller; Guan Rong Tan; Emily M Farina; Alison L Sheets-Singer; Steven H Collins
Journal:  J Neuroeng Rehabil       Date:  2022-05-12       Impact factor: 5.208

6.  Taking advantage of external mechanical work to reduce metabolic cost: the mechanics and energetics of split-belt treadmill walking.

Authors:  Natalia Sánchez; Surabhi N Simha; J Maxwell Donelan; James M Finley
Journal:  J Physiol       Date:  2019-07-03       Impact factor: 5.182

7.  Using asymmetry to your advantage: learning to acquire and accept external assistance during prolonged split-belt walking.

Authors:  Natalia Sánchez; Surabhi N Simha; J Maxwell Donelan; James M Finley
Journal:  J Neurophysiol       Date:  2020-12-09       Impact factor: 2.714

8.  Instantaneous Metabolic Cost of Walking: Joint-Space Dynamic Model with Subject-Specific Heat Rate.

Authors:  Dustyn Roberts; Howard Hillstrom; Joo H Kim
Journal:  PLoS One       Date:  2016-12-28       Impact factor: 3.240

9.  Sensing leg movement enhances wearable monitoring of energy expenditure.

Authors:  Patrick Slade; Mykel J Kochenderfer; Scott L Delp; Steven H Collins
Journal:  Nat Commun       Date:  2021-07-13       Impact factor: 14.919

10.  "Body-In-The-Loop": Optimizing Device Parameters Using Measures of Instantaneous Energetic Cost.

Authors:  Wyatt Felt; Jessica C Selinger; J Maxwell Donelan; C David Remy
Journal:  PLoS One       Date:  2015-08-19       Impact factor: 3.240

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