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Physical activity, motor competence and movement and gait quality: A principal component analysis

Cain C.T. Clark, Claire Barnes Orcid Logo, Michael J. Duncan, Huw Summers Orcid Logo, Gareth Stratton Orcid Logo

Human Movement Science, Volume: 68, Start page: 102523

Swansea University Authors: Claire Barnes Orcid Logo, Huw Summers Orcid Logo, Gareth Stratton Orcid Logo

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DOI (Published version): 10.1016/j.humov.2019.102523

Abstract

ObjectiveWhile novel analytical methods have been used to examine movement behaviours, to date, no studies have examined whether a frequency-based measure, such a spectral purity, is useful in explaining key facets of human movement. The aim of this study was to investigate movement and gait quality...

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Published in: Human Movement Science
ISSN: 0167-9457
Published: Elsevier BV 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa52054
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spelling 2019-10-08T18:23:48.6088373 v2 52054 2019-09-24 Physical activity, motor competence and movement and gait quality: A principal component analysis 024232879fc13d5ceac584360af8742c 0000-0003-1031-7127 Claire Barnes Claire Barnes true false a61c15e220837ebfa52648c143769427 0000-0002-0898-5612 Huw Summers Huw Summers true false 6d62b2ed126961bed81a94a2beba8a01 0000-0001-5618-0803 Gareth Stratton Gareth Stratton true false 2019-09-24 MEDE ObjectiveWhile novel analytical methods have been used to examine movement behaviours, to date, no studies have examined whether a frequency-based measure, such a spectral purity, is useful in explaining key facets of human movement. The aim of this study was to investigate movement and gait quality, physical activity and motor competence using principal component analysis.MethodsSixty-five children (38 boys, 4.3 ± 0.7y, 1.04 ± 0.05 m, 17.8 ± 3.2 kg, BMI; 16.2 ± 1.9 kg∙m2) took part in this study. Measures included accelerometer-derived physical activity and movement quality (spectral purity), motor competence (Movement Assessment Battery for Children 2nd edition; MABC2), height, weight and waist circumference. All data were subjected to a principal component analysis, and the internal consistency of resultant components were assessed using Cronbach's alpha.ResultsTwo principal components, with excellent internal consistency (Cronbach α >0.9) were found; the 1st principal component, termed “movement component”, contained spectral purity, traffic light MABC2 score, fine motor% and gross motor% (α = 0.93); the 2nd principal component, termed “anthropometric component”, contained weight, BMI, BMI% and body fat% (α = 0.91).ConclusionThe results of the present study demonstrate that accelerometric analyses can be used to assess motor competence in an automated manner, and that spectral purity is a meaningful, indicative, metric related to children's movement quality. Journal Article Human Movement Science 68 102523 Elsevier BV 0167-9457 31 12 2019 2019-12-31 10.1016/j.humov.2019.102523 http://dx.doi.org/10.1016/j.humov.2019.102523 COLLEGE NANME Biomedical Engineering COLLEGE CODE MEDE Swansea University 2019-10-08T18:23:48.6088373 2019-09-24T11:56:36.8700980 Cain C.T. Clark 1 Claire Barnes 0000-0003-1031-7127 2 Michael J. Duncan 3 Huw Summers 0000-0002-0898-5612 4 Gareth Stratton 0000-0001-5618-0803 5 52054__15492__914875f1af074ce189c8b2a340d9425a.pdf clark2019.pdf 2019-10-07T11:54:31.0870000 Output 869919 application/pdf Accepted Manuscript true 2021-05-01T00:00:00.0000000 Released under the terms of a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND). true eng
title Physical activity, motor competence and movement and gait quality: A principal component analysis
spellingShingle Physical activity, motor competence and movement and gait quality: A principal component analysis
Claire Barnes
Huw Summers
Gareth Stratton
title_short Physical activity, motor competence and movement and gait quality: A principal component analysis
title_full Physical activity, motor competence and movement and gait quality: A principal component analysis
title_fullStr Physical activity, motor competence and movement and gait quality: A principal component analysis
title_full_unstemmed Physical activity, motor competence and movement and gait quality: A principal component analysis
title_sort Physical activity, motor competence and movement and gait quality: A principal component analysis
author_id_str_mv 024232879fc13d5ceac584360af8742c
a61c15e220837ebfa52648c143769427
6d62b2ed126961bed81a94a2beba8a01
author_id_fullname_str_mv 024232879fc13d5ceac584360af8742c_***_Claire Barnes
a61c15e220837ebfa52648c143769427_***_Huw Summers
6d62b2ed126961bed81a94a2beba8a01_***_Gareth Stratton
author Claire Barnes
Huw Summers
Gareth Stratton
author2 Cain C.T. Clark
Claire Barnes
Michael J. Duncan
Huw Summers
Gareth Stratton
format Journal article
container_title Human Movement Science
container_volume 68
container_start_page 102523
publishDate 2019
institution Swansea University
issn 0167-9457
doi_str_mv 10.1016/j.humov.2019.102523
publisher Elsevier BV
url http://dx.doi.org/10.1016/j.humov.2019.102523
document_store_str 1
active_str 0
description ObjectiveWhile novel analytical methods have been used to examine movement behaviours, to date, no studies have examined whether a frequency-based measure, such a spectral purity, is useful in explaining key facets of human movement. The aim of this study was to investigate movement and gait quality, physical activity and motor competence using principal component analysis.MethodsSixty-five children (38 boys, 4.3 ± 0.7y, 1.04 ± 0.05 m, 17.8 ± 3.2 kg, BMI; 16.2 ± 1.9 kg∙m2) took part in this study. Measures included accelerometer-derived physical activity and movement quality (spectral purity), motor competence (Movement Assessment Battery for Children 2nd edition; MABC2), height, weight and waist circumference. All data were subjected to a principal component analysis, and the internal consistency of resultant components were assessed using Cronbach's alpha.ResultsTwo principal components, with excellent internal consistency (Cronbach α >0.9) were found; the 1st principal component, termed “movement component”, contained spectral purity, traffic light MABC2 score, fine motor% and gross motor% (α = 0.93); the 2nd principal component, termed “anthropometric component”, contained weight, BMI, BMI% and body fat% (α = 0.91).ConclusionThe results of the present study demonstrate that accelerometric analyses can be used to assess motor competence in an automated manner, and that spectral purity is a meaningful, indicative, metric related to children's movement quality.
published_date 2019-12-31T04:04:13Z
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score 11.037603

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