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Effect of sampling rate on acceleration and counts of hip- and wrist-worn ActiGraph accelerometers in children

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

Physiological Measurement, Volume: 40, Issue: 9, Start page: 095008

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

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DOI (Published version): 10.1088/1361-6579/ab444b

Abstract

Sampling rate (Hz) of ActiGraph accelerometers may affect processing of acceleration to activity counts when using a hip-worn monitor, but research is needed to quantify if sampling rate affects actual acceleration (mg's), when using wrist-worn accelerometers and during non-locomotive activitie...

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Published in: Physiological Measurement
ISSN: 1361-6579
Published: 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa52104
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Objective: To assess the effect of ActiGraph sampling rate on total counts/15-sec and mean acceleration and to compare differences due to sampling rate between accelerometer wear locations and across different types of activities. Approach: Children (n=29) wore a hip- and wrist-worn accelerometer (sampled at 100 Hz, downsampled in MATLAB to 30 Hz) during rest/transition periods, active video games, and a treadmill test to volitional exhaustion. Mean acceleration and counts/15-sec were computed for each axis and as vector magnitude. Main Results: There were mostly no significant differences in mean acceleration. However, 100 Hz data resulted in significantly more total counts/15-sec (mean bias 4-43 counts/15-sec across axes) for both the hip- and wrist-worn monitor when compared to 30 Hz data. Absolute differences increased with activity intensity (hip: r=0.46-0.63; wrist: r=0.26-0.55) and were greater for hip- versus wrist-worn monitors. Percent agreement between 100 and 30 Hz data was high (97.4-99.7%) when cut-points or machine learning algorithms were used to classify activity intensity. Significance: Our findings support that sampling rate affects the generation of counts but adds that differences increase with intensity and when using hip-worn monitors. 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spelling 2023-02-21T16:49:29.9082102 v2 52104 2019-09-26 Effect of sampling rate on acceleration and counts of hip- and wrist-worn ActiGraph accelerometers in children bdb20e3f31bcccf95c7bc116070c4214 0000-0003-0355-6357 Kelly Mackintosh Kelly Mackintosh true false 062f5697ff59f004bc8c713955988398 0000-0003-0813-7477 Melitta McNarry Melitta McNarry true false 2019-09-26 STSC Sampling rate (Hz) of ActiGraph accelerometers may affect processing of acceleration to activity counts when using a hip-worn monitor, but research is needed to quantify if sampling rate affects actual acceleration (mg's), when using wrist-worn accelerometers and during non-locomotive activities. Objective: To assess the effect of ActiGraph sampling rate on total counts/15-sec and mean acceleration and to compare differences due to sampling rate between accelerometer wear locations and across different types of activities. Approach: Children (n=29) wore a hip- and wrist-worn accelerometer (sampled at 100 Hz, downsampled in MATLAB to 30 Hz) during rest/transition periods, active video games, and a treadmill test to volitional exhaustion. Mean acceleration and counts/15-sec were computed for each axis and as vector magnitude. Main Results: There were mostly no significant differences in mean acceleration. However, 100 Hz data resulted in significantly more total counts/15-sec (mean bias 4-43 counts/15-sec across axes) for both the hip- and wrist-worn monitor when compared to 30 Hz data. Absolute differences increased with activity intensity (hip: r=0.46-0.63; wrist: r=0.26-0.55) and were greater for hip- versus wrist-worn monitors. Percent agreement between 100 and 30 Hz data was high (97.4-99.7%) when cut-points or machine learning algorithms were used to classify activity intensity. Significance: Our findings support that sampling rate affects the generation of counts but adds that differences increase with intensity and when using hip-worn monitors. We recommend researchers be consistent and vigilantly report the sampling rate used, but note that classifying data into activity intensities resulted in agreement despite differences in sampling rate. Journal Article Physiological Measurement 40 9 095008 1361-6579 30 9 2019 2019-09-30 10.1088/1361-6579/ab444b COLLEGE NANME Sport and Exercise Sciences COLLEGE CODE STSC Swansea University 2023-02-21T16:49:29.9082102 2019-09-26T09:17:31.5441337 Faculty of Science and Engineering School of Engineering and Applied Sciences - Sport and Exercise Sciences Kimberly A Clevenger 1 Karin A Pfeiffer 2 Kelly Mackintosh 0000-0003-0355-6357 3 Melitta McNarry 0000-0003-0813-7477 4 Jan Brønd 5 Daniel Arvidsson 6 Alexander H K Montoye 7 0052104-26092019092038.pdf clevenger2019.pdf 2019-09-26T09:20:38.4600000 Output 482389 application/pdf Accepted Manuscript true 2020-09-13T00:00:00.0000000 Released under the terms of a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND). true eng
title Effect of sampling rate on acceleration and counts of hip- and wrist-worn ActiGraph accelerometers in children
spellingShingle Effect of sampling rate on acceleration and counts of hip- and wrist-worn ActiGraph accelerometers in children
Kelly Mackintosh
Melitta McNarry
title_short Effect of sampling rate on acceleration and counts of hip- and wrist-worn ActiGraph accelerometers in children
title_full Effect of sampling rate on acceleration and counts of hip- and wrist-worn ActiGraph accelerometers in children
title_fullStr Effect of sampling rate on acceleration and counts of hip- and wrist-worn ActiGraph accelerometers in children
title_full_unstemmed Effect of sampling rate on acceleration and counts of hip- and wrist-worn ActiGraph accelerometers in children
title_sort Effect of sampling rate on acceleration and counts of hip- and wrist-worn ActiGraph accelerometers in children
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
Karin A Pfeiffer
Kelly Mackintosh
Melitta McNarry
Jan Brønd
Daniel Arvidsson
Alexander H K Montoye
format Journal article
container_title Physiological Measurement
container_volume 40
container_issue 9
container_start_page 095008
publishDate 2019
institution Swansea University
issn 1361-6579
doi_str_mv 10.1088/1361-6579/ab444b
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
document_store_str 1
active_str 0
description Sampling rate (Hz) of ActiGraph accelerometers may affect processing of acceleration to activity counts when using a hip-worn monitor, but research is needed to quantify if sampling rate affects actual acceleration (mg's), when using wrist-worn accelerometers and during non-locomotive activities. Objective: To assess the effect of ActiGraph sampling rate on total counts/15-sec and mean acceleration and to compare differences due to sampling rate between accelerometer wear locations and across different types of activities. Approach: Children (n=29) wore a hip- and wrist-worn accelerometer (sampled at 100 Hz, downsampled in MATLAB to 30 Hz) during rest/transition periods, active video games, and a treadmill test to volitional exhaustion. Mean acceleration and counts/15-sec were computed for each axis and as vector magnitude. Main Results: There were mostly no significant differences in mean acceleration. However, 100 Hz data resulted in significantly more total counts/15-sec (mean bias 4-43 counts/15-sec across axes) for both the hip- and wrist-worn monitor when compared to 30 Hz data. Absolute differences increased with activity intensity (hip: r=0.46-0.63; wrist: r=0.26-0.55) and were greater for hip- versus wrist-worn monitors. Percent agreement between 100 and 30 Hz data was high (97.4-99.7%) when cut-points or machine learning algorithms were used to classify activity intensity. Significance: Our findings support that sampling rate affects the generation of counts but adds that differences increase with intensity and when using hip-worn monitors. We recommend researchers be consistent and vigilantly report the sampling rate used, but note that classifying data into activity intensities resulted in agreement despite differences in sampling rate.
published_date 2019-09-30T04:04:18Z
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score 11.016235

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