Literature DB >> 29224176

Validation of a method for estimating energy expenditure during walking in middle-aged adults.

Nathan Caron1, Teddy Caderby1, Nicolas Peyrot1, Chantal Verkindt1, Georges Dalleau2.   

Abstract

PURPOSE: The aim of this study was to test the validity of a method using an inertial measurement unit for estimating activity-related energy expenditure (AEE) during walking in middle-aged adults.
METHODS: Twenty healthy middle-aged participants completed different treadmill walking trials with an inertial measurement unit adhered to their lower back. Gas exchange was monitored with indirect calorimetry. Mechanical data were used to estimate AEE from an algorithm developed by Bouten et al. (Med Sci Sport Exer 26(12):1516-1523, 1994). Three methods for removing the gravitational component were proposed and tested: mean subtraction method (MSM), high-pass filter method (HPM) and free acceleration method (FAM).
RESULTS: The three methods did not differ significantly from the indirect calorimetry [bias = - 0.08 kcal min-1; p = 0.47 (MSM), bias = - 0.08 kcal min-1; p = 0.48 (HPM) and bias = - 0.15 kcal min-1; p = 0.23 (FAM)]. Mean root mean square errors were 0.43, 0.42 and 0.51 kcal min-1 for MSM, HPM and FAM, respectively.
CONCLUSION: This study proposed an accurate method for estimating AEE in middle-aged adults for a large range of walking intensities, from slow to brisk walking, based on Bouten's algorithm.

Entities:  

Keywords:  Accelerometry; Activity monitoring; Filtering process; Net metabolic rate

Mesh:

Year:  2017        PMID: 29224176     DOI: 10.1007/s00421-017-3780-0

Source DB:  PubMed          Journal:  Eur J Appl Physiol        ISSN: 1439-6319            Impact factor:   3.078


  36 in total

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Journal:  Int J Obes Relat Metab Disord       Date:  1999-04

2.  Validity of accelerometry for the assessment of moderate intensity physical activity in the field.

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Journal:  Med Sci Sports Exerc       Date:  2000-09       Impact factor: 5.411

3.  A novel method for using accelerometer data to predict energy expenditure.

Authors:  Scott E Crouter; Kurt G Clowers; David R Bassett
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Journal:  IEEE Trans Rehabil Eng       Date:  1996-12

Review 5.  Global physical activity levels: surveillance progress, pitfalls, and prospects.

Authors:  Pedro C Hallal; Lars Bo Andersen; Fiona C Bull; Regina Guthold; William Haskell; Ulf Ekelund
Journal:  Lancet       Date:  2012-07-21       Impact factor: 79.321

6.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

7.  Assessment of energy expenditure for physical activity using a triaxial accelerometer.

Authors:  C V Bouten; K R Westerterp; M Verduin; J D Janssen
Journal:  Med Sci Sports Exerc       Date:  1994-12       Impact factor: 5.411

8.  A comprehensive evaluation of commonly used accelerometer energy expenditure and MET prediction equations.

Authors:  Kate Lyden; Sarah L Kozey; John W Staudenmeyer; Patty S Freedson
Journal:  Eur J Appl Physiol       Date:  2010-09-15       Impact factor: 3.078

9.  Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity.

Authors:  Vincent T van Hees; Lukas Gorzelniak; Emmanuel Carlos Dean León; Martin Eder; Marcelo Pias; Salman Taherian; Ulf Ekelund; Frida Renström; Paul W Franks; Alexander Horsch; Søren Brage
Journal:  PLoS One       Date:  2013-04-23       Impact factor: 3.240

10.  Validation of the Fitbit One® for physical activity measurement at an upper torso attachment site.

Authors:  Keith M Diaz; David J Krupka; Melinda J Chang; Jonathan A Shaffer; Yao Ma; Jeff Goldsmith; Joseph E Schwartz; Karina W Davidson
Journal:  BMC Res Notes       Date:  2016-04-12
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  1 in total

1.  Real-Time Tracking of Human Neck Postures and Movements.

Authors:  Korupalli V Rajesh Kumar; Susan Elias
Journal:  Healthcare (Basel)       Date:  2021-12-19
  1 in total

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