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

Arvidsson, Daniel; Fridolfsson, Jonatan; Börjesson, Mats; Andersen, Lars Bo; Ekblom, Örjan; Dencker, Magnus LU and Brønd, Jan Christian (2019) In Scandinavian Journal of Medicine and Science in Sports
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... (More)

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, VO2net (VO2tot − VO2stand). 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.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
epub
subject
keywords
acceleration, counts, energy expenditure, frequency filtering, mechanical work
in
Scandinavian Journal of Medicine and Science in Sports
publisher
Wiley-Blackwell
external identifiers
  • scopus:85067003259
ISSN
0905-7188
DOI
10.1111/sms.13470
language
English
LU publication?
yes
id
4266813d-713c-4886-83d2-58881133eca7
date added to LUP
2019-07-03 16:25:46
date last changed
2019-07-16 04:14:03
@article{4266813d-713c-4886-83d2-58881133eca7,
  abstract     = {<p>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, VO<sub>2</sub>net (VO<sub>2</sub>tot − VO<sub>2</sub>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.</p>},
  author       = {Arvidsson, Daniel and Fridolfsson, Jonatan and Börjesson, Mats and Andersen, Lars Bo and Ekblom, Örjan and Dencker, Magnus and Brønd, Jan Christian},
  issn         = {0905-7188},
  keyword      = {acceleration,counts,energy expenditure,frequency filtering,mechanical work},
  language     = {eng},
  publisher    = {Wiley-Blackwell},
  series       = {Scandinavian Journal of Medicine and Science in Sports},
  title        = {Re-examination of accelerometer data processing and calibration for the assessment of physical activity intensity},
  url          = {http://dx.doi.org/10.1111/sms.13470},
  year         = {2019},
}