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Impact of ActiGraph sampling rate on free-living physical activity measurement in youth

Kimberly A Clevenger Orcid Logo, Jan Christian Brønd Orcid Logo, Kelly Mackintosh Orcid Logo, Karin A Pfeiffer Orcid Logo, Alexander H K Montoye, Melitta McNarry Orcid Logo

Physiological Measurement, Volume: 43, Issue: 10

Swansea University Authors: Kelly Mackintosh Orcid Logo, Melitta McNarry Orcid Logo

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DOI (Published version): 10.1088/1361-6579/ac944f

Abstract

ActiGraph sampling frequencies of more than 30 Hz may result in overestimation of activity counts in both children and adults, but research on free-living individuals has not included the range of sampling frequencies used by researchers. Objective: We compared count- and raw-acceleration-based metr...

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Published in: Physiological Measurement
ISSN: 0967-3334 1361-6579
Published: IOP Publishing 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa61301
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Objective: We compared count- and raw-acceleration-based metrics from free-living children and adolescents across a range of sampling frequencies. Approach: Participants (n=445; 10-15 y) wore an ActiGraph accelerometer for at least one 10-h day. Vector Magnitude counts, Mean Amplitude Deviation, Monitor-Independent Movement Summary units, and activity intensity classified using six methods (four cut-points, two-regression model, and artificial neural network) were compared between 30 Hz and 60, 80, 90, and 100 Hz sampling frequencies using mean absolute differences, correlations, and equivalence testing. Main results: All outcomes were statistically equivalent, and correlation coefficients were ≥0.970. Absolute differences were largest for the 30 vs. 80 and 30 vs. 100 Hz count comparisons. For comparisons of 30 with 60, 80, 90, or 100 Hz, mean (and maximum) absolute differences in minutes of moderate-to-vigorous physical activity per day ranged from 0.1 to 0.3 (0.4 to 1.5), 0.3 to 1.3 (1.6 to 8.6), 0.1 to 0.3 (1.1 to 2.5), and 0.3 to 2.5 (1.6 to 14.3) across the six classification methods. Significance: Acceleration-based outcomes are comparable across the full range of sampling rates and therefore recommended for future research. 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spelling v2 61301 2022-09-22 Impact of ActiGraph sampling rate on free-living physical activity measurement in youth bdb20e3f31bcccf95c7bc116070c4214 0000-0003-0355-6357 Kelly Mackintosh Kelly Mackintosh true false 062f5697ff59f004bc8c713955988398 0000-0003-0813-7477 Melitta McNarry Melitta McNarry true false 2022-09-22 EAAS ActiGraph sampling frequencies of more than 30 Hz may result in overestimation of activity counts in both children and adults, but research on free-living individuals has not included the range of sampling frequencies used by researchers. Objective: We compared count- and raw-acceleration-based metrics from free-living children and adolescents across a range of sampling frequencies. Approach: Participants (n=445; 10-15 y) wore an ActiGraph accelerometer for at least one 10-h day. Vector Magnitude counts, Mean Amplitude Deviation, Monitor-Independent Movement Summary units, and activity intensity classified using six methods (four cut-points, two-regression model, and artificial neural network) were compared between 30 Hz and 60, 80, 90, and 100 Hz sampling frequencies using mean absolute differences, correlations, and equivalence testing. Main results: All outcomes were statistically equivalent, and correlation coefficients were ≥0.970. Absolute differences were largest for the 30 vs. 80 and 30 vs. 100 Hz count comparisons. For comparisons of 30 with 60, 80, 90, or 100 Hz, mean (and maximum) absolute differences in minutes of moderate-to-vigorous physical activity per day ranged from 0.1 to 0.3 (0.4 to 1.5), 0.3 to 1.3 (1.6 to 8.6), 0.1 to 0.3 (1.1 to 2.5), and 0.3 to 2.5 (1.6 to 14.3) across the six classification methods. Significance: Acceleration-based outcomes are comparable across the full range of sampling rates and therefore recommended for future research. If using counts, we recommend a multiple of 30 Hz because using a 100 Hz sampling rate resulted in large maximum individual differences and epoch-level differences, and increasing differences with activity level. Journal Article Physiological Measurement 43 10 IOP Publishing 0967-3334 1361-6579 Accelerometer, methodology, signal processing, sampling frequency, youth, pediatric 22 9 2022 2022-09-22 10.1088/1361-6579/ac944f COLLEGE NANME Engineering and Applied Sciences School COLLEGE CODE EAAS Swansea University 2024-07-17T12:57:10.7553360 2022-09-22T12:06:30.5720060 Faculty of Science and Engineering School of Engineering and Applied Sciences - Sport and Exercise Sciences Kimberly A Clevenger 0000-0003-2993-3587 1 Jan Christian Brønd 0000-0001-6718-3022 2 Kelly Mackintosh 0000-0003-0355-6357 3 Karin A Pfeiffer 0000-0001-6280-9495 4 Alexander H K Montoye 5 Melitta McNarry 0000-0003-0813-7477 6 61301__25190__65fff9210c474a22a8bd31c31acffe74.pdf 61301.pdf 2022-09-22T12:10:15.5784289 Output 441392 application/pdf Accepted Manuscript true 2023-09-22T00:00:00.0000000 ©2022 All rights reserved. All article content, except where otherwise noted, is licensed under a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND) true eng https://creativecommons.org/licenses/by-nc-nd/3.0/
title Impact of ActiGraph sampling rate on free-living physical activity measurement in youth
spellingShingle Impact of ActiGraph sampling rate on free-living physical activity measurement in youth
Kelly Mackintosh
Melitta McNarry
title_short Impact of ActiGraph sampling rate on free-living physical activity measurement in youth
title_full Impact of ActiGraph sampling rate on free-living physical activity measurement in youth
title_fullStr Impact of ActiGraph sampling rate on free-living physical activity measurement in youth
title_full_unstemmed Impact of ActiGraph sampling rate on free-living physical activity measurement in youth
title_sort Impact of ActiGraph sampling rate on free-living physical activity measurement in youth
author_id_str_mv bdb20e3f31bcccf95c7bc116070c4214
062f5697ff59f004bc8c713955988398
author_id_fullname_str_mv bdb20e3f31bcccf95c7bc116070c4214_***_Kelly Mackintosh
062f5697ff59f004bc8c713955988398_***_Melitta McNarry
author Kelly Mackintosh
Melitta McNarry
author2 Kimberly A Clevenger
Jan Christian Brønd
Kelly Mackintosh
Karin A Pfeiffer
Alexander H K Montoye
Melitta McNarry
format Journal article
container_title Physiological Measurement
container_volume 43
container_issue 10
publishDate 2022
institution Swansea University
issn 0967-3334
1361-6579
doi_str_mv 10.1088/1361-6579/ac944f
publisher IOP Publishing
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Sport and Exercise Sciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Sport and Exercise Sciences
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description ActiGraph sampling frequencies of more than 30 Hz may result in overestimation of activity counts in both children and adults, but research on free-living individuals has not included the range of sampling frequencies used by researchers. Objective: We compared count- and raw-acceleration-based metrics from free-living children and adolescents across a range of sampling frequencies. Approach: Participants (n=445; 10-15 y) wore an ActiGraph accelerometer for at least one 10-h day. Vector Magnitude counts, Mean Amplitude Deviation, Monitor-Independent Movement Summary units, and activity intensity classified using six methods (four cut-points, two-regression model, and artificial neural network) were compared between 30 Hz and 60, 80, 90, and 100 Hz sampling frequencies using mean absolute differences, correlations, and equivalence testing. Main results: All outcomes were statistically equivalent, and correlation coefficients were ≥0.970. Absolute differences were largest for the 30 vs. 80 and 30 vs. 100 Hz count comparisons. For comparisons of 30 with 60, 80, 90, or 100 Hz, mean (and maximum) absolute differences in minutes of moderate-to-vigorous physical activity per day ranged from 0.1 to 0.3 (0.4 to 1.5), 0.3 to 1.3 (1.6 to 8.6), 0.1 to 0.3 (1.1 to 2.5), and 0.3 to 2.5 (1.6 to 14.3) across the six classification methods. Significance: Acceleration-based outcomes are comparable across the full range of sampling rates and therefore recommended for future research. If using counts, we recommend a multiple of 30 Hz because using a 100 Hz sampling rate resulted in large maximum individual differences and epoch-level differences, and increasing differences with activity level.
published_date 2022-09-22T12:57:09Z
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score 11.037581

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