Literature DB >> 31102474

Re-examination of accelerometer data processing and calibration for the assessment of physical activity intensity.

Daniel Arvidsson1, Jonatan Fridolfsson1, Mats Börjesson1,2,3, Lars Bo Andersen4,5, Örjan Ekblom6, Magnus Dencker7, Jan Christian Brønd8.   

Abstract

This review re-examines the use of accelerometer and oxygen uptake data for the assessment of activity intensity. Accelerometers capture mechanical work, while oxygen uptake captures the energy cost of this work. Frequency filtering needs to be considered when processing acceleration data. A too restrictive filter attenuates the acceleration signal for walking and, to a higher degree, for running. This measurement error affects shorter (children) more than taller (adults) individuals due to their higher movement frequency. Less restrictive filtering includes more movement-related signals and provides measures that better capture mechanical work, but may include more noise. An optimal filter cut-point is determined where most relevant acceleration signals are included. Further, accelerometer placement affects what part of mechanical work being captured. While the waist placement captures total mechanical work and therefore contributes to measures of activity intensity equivalent by age and stature, the thigh and wrist placements capture more internal work and do not provide equivalent measures. Value calibration of accelerometer measures is usually performed using measured oxygen uptake with the metabolic equivalent of task (MET) as reference measure of activity intensity. However, the use of MET is not stringent and is not a measure of activity intensity equivalent by age and stature. A candidate measure is the mass-specific net oxygen uptake, VO2 net (VO2 tot - VO2 stand). To improve measurement of physical activity intensity using accelerometers, research developments are suggested concerning the processing of accelerometer data, use of energy expenditure as reference for activity intensity, and calibration procedure with absolute versus relative intensity.
© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  acceleration; counts; energy expenditure; frequency filtering; mechanical work

Mesh:

Year:  2019        PMID: 31102474     DOI: 10.1111/sms.13470

Source DB:  PubMed          Journal:  Scand J Med Sci Sports        ISSN: 0905-7188            Impact factor:   4.221


  7 in total

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Journal:  J Pers Med       Date:  2022-05-05

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Authors:  Susanne Bernhardsson; Charlotte Boman; Stefan Lundqvist; Daniel Arvidsson; Mats Börjesson; Maria E H Larsson; Hannah Lundh; Karin Melin; Per Nilsen; Katarina Lauruschkus
Journal:  Pilot Feasibility Stud       Date:  2022-06-01

3.  Wearable Inertial Sensors to Assess Gait during the 6-Minute Walk Test: A Systematic Review.

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4.  Association of Basal Metabolic Rate and Nutrients Oxidation with Cardiometabolic Risk Factors and Insulin Sensitivity in Sedentary Middle-Aged Adults.

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5.  Resemblance in accelerometer-assessed physical activity in families with children: the Lolland-Falster Health Study.

Authors:  Therese Lockenwitz Petersen; Jan Christian Brønd; Peter Lund Kristensen; Eivind Aadland; Anders Grøntved; Randi Jepsen
Journal:  Int J Behav Nutr Phys Act       Date:  2020-12-04       Impact factor: 6.457

6.  A theory-based model of cumulative activity.

Authors:  Kole Phillips; Kevin Stanley; Daniel Fuller
Journal:  Sci Rep       Date:  2022-09-17       Impact factor: 4.996

7.  Absolute Accelerometer-Based Intensity Prescription Compared to Physiological Variables in Pregnant and Nonpregnant Women.

Authors:  Philipp Birnbaumer; Pavel Dietz; Estelle Dorothy Watson; Gudani Mukoma; Alexander Müller; Matteo Christian Sattler; Johannes Jaunig; Mireille Nicoline Maria van Poppel; Peter Hofmann
Journal:  Int J Environ Res Public Health       Date:  2020-08-05       Impact factor: 3.390

  7 in total

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