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Quantitative Time Profiling of Children's Activity and Motion

Claire Barnes Orcid Logo, Cain Clark, Mark Holton Orcid Logo, Gareth Stratton Orcid Logo, Huw Summers Orcid Logo

Medicine & Science in Sports & Exercise, Volume: 49, Issue: 1, Pages: 183 - 190

Swansea University Authors: Claire Barnes Orcid Logo, Cain Clark, Mark Holton Orcid Logo, Gareth Stratton Orcid Logo, Huw Summers Orcid Logo

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DOI (Published version): 10.1249/mss.0000000000001085

Abstract

Introduction The aim of this study was to establish children's mechanical movement patterns during a standardized assessment of fitness by using an accelerometer. Further to this, our objective was to use the information from the accelerometer to profile individual time courses of exercise, acr...

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Published in: Medicine & Science in Sports & Exercise
ISSN: 0195-9131 1530-0315
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa49765
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Further to this, our objective was to use the information from the accelerometer to profile individual time courses of exercise, across the cohort.Methods A multistage fitness test study was performed with 103 children (mean &#xB1; SD age = 10.3 &#xB1; 0.6 yr). Children wore an ankle-mounted accelerometer, and gait data were collected on radial acceleration traces obtained at a frequency of 40 Hz. Time-resolved metrics of foot impact force, maximum leg lift angle, and stride frequency were used to profile children's performance across the test duration. A whole-history metric of stride quality, based on the changing ratio of stride length to stride frequency, was used in bivariate analyses of physical performance and body metrics.Results Stride angle derived by our protocol was found to have a strong positive correlation with integrated acceleration, synonymous with counts, widely used in the sport science community (r = 0.81, 0.79, and 0.80 across different stages of the multistage fitness test). Accelerometer data show that differing performance in the test is related to the children's ability to accurately control their gait, with high performers displaying a linearly increasing speed, delivered through stride extension and well matched to the demand level of the test. A negative correlation was found between stride quality and body measures of body mass index (r = &#x2212;0.61) and body mass (r = &#x2212;0.60).Conclusion Profiles of the gait parameters provide information on the mechanics of child's motion, allowing detailed assessment of multiple parameter during increasing intensities of exercise.</abstract><type>Journal Article</type><journal>Medicine &amp; Science in Sports &amp; Exercise</journal><volume>49</volume><journalNumber>1</journalNumber><paginationStart>183</paginationStart><paginationEnd>190</paginationEnd><publisher/><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0195-9131</issnPrint><issnElectronic>1530-0315</issnElectronic><keywords/><publishedDay>31</publishedDay><publishedMonth>1</publishedMonth><publishedYear>2017</publishedYear><publishedDate>2017-01-31</publishedDate><doi>10.1249/mss.0000000000001085</doi><url/><notes/><college>COLLEGE NANME</college><department>Biomedical Engineering</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDE</DepartmentCode><institution>Swansea University</institution><apcterm/><funders/><projectreference/><lastEdited>2023-02-14T16:47:50.2929007</lastEdited><Created>2019-03-27T08:35:49.9054962</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Engineering and Applied Sciences - Sport and Exercise Sciences</level></path><authors><author><firstname>Claire</firstname><surname>Barnes</surname><orcid>0000-0003-1031-7127</orcid><order>1</order></author><author><firstname>Cain</firstname><surname>Clark</surname><orcid/><order>2</order></author><author><firstname>Mark</firstname><surname>Holton</surname><orcid>0000-0001-8834-3283</orcid><order>3</order></author><author><firstname>Gareth</firstname><surname>Stratton</surname><orcid>0000-0001-5618-0803</orcid><order>4</order></author><author><firstname>Huw</firstname><surname>Summers</surname><orcid>0000-0002-0898-5612</orcid><order>5</order></author></authors><documents><document><filename>49765__13270__363efa8515b84b1ebeb52666d7ae4b01.pdf</filename><originalFilename>barnes2017.pdf</originalFilename><uploaded>2019-03-27T08:43:57.6030000</uploaded><type>Output</type><contentLength>5935837</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><embargoDate>2019-03-27T00:00:00.0000000</embargoDate><copyrightCorrect>true</copyrightCorrect><language>eng</language></document></documents><OutputDurs/></rfc1807>
spelling 2023-02-14T16:47:50.2929007 v2 49765 2019-03-27 Quantitative Time Profiling of Children's Activity and Motion 024232879fc13d5ceac584360af8742c 0000-0003-1031-7127 Claire Barnes Claire Barnes true false e7cb9f1de82983f71f5065419eec75ff Cain Clark Cain Clark true false 0e1d89d0cc934a740dcd0a873aed178e 0000-0001-8834-3283 Mark Holton Mark Holton true false 6d62b2ed126961bed81a94a2beba8a01 0000-0001-5618-0803 Gareth Stratton Gareth Stratton true false a61c15e220837ebfa52648c143769427 0000-0002-0898-5612 Huw Summers Huw Summers true false 2019-03-27 MEDE Introduction The aim of this study was to establish children's mechanical movement patterns during a standardized assessment of fitness by using an accelerometer. Further to this, our objective was to use the information from the accelerometer to profile individual time courses of exercise, across the cohort.Methods A multistage fitness test study was performed with 103 children (mean ± SD age = 10.3 ± 0.6 yr). Children wore an ankle-mounted accelerometer, and gait data were collected on radial acceleration traces obtained at a frequency of 40 Hz. Time-resolved metrics of foot impact force, maximum leg lift angle, and stride frequency were used to profile children's performance across the test duration. A whole-history metric of stride quality, based on the changing ratio of stride length to stride frequency, was used in bivariate analyses of physical performance and body metrics.Results Stride angle derived by our protocol was found to have a strong positive correlation with integrated acceleration, synonymous with counts, widely used in the sport science community (r = 0.81, 0.79, and 0.80 across different stages of the multistage fitness test). Accelerometer data show that differing performance in the test is related to the children's ability to accurately control their gait, with high performers displaying a linearly increasing speed, delivered through stride extension and well matched to the demand level of the test. A negative correlation was found between stride quality and body measures of body mass index (r = −0.61) and body mass (r = −0.60).Conclusion Profiles of the gait parameters provide information on the mechanics of child's motion, allowing detailed assessment of multiple parameter during increasing intensities of exercise. Journal Article Medicine & Science in Sports & Exercise 49 1 183 190 0195-9131 1530-0315 31 1 2017 2017-01-31 10.1249/mss.0000000000001085 COLLEGE NANME Biomedical Engineering COLLEGE CODE MEDE Swansea University 2023-02-14T16:47:50.2929007 2019-03-27T08:35:49.9054962 Faculty of Science and Engineering School of Engineering and Applied Sciences - Sport and Exercise Sciences Claire Barnes 0000-0003-1031-7127 1 Cain Clark 2 Mark Holton 0000-0001-8834-3283 3 Gareth Stratton 0000-0001-5618-0803 4 Huw Summers 0000-0002-0898-5612 5 49765__13270__363efa8515b84b1ebeb52666d7ae4b01.pdf barnes2017.pdf 2019-03-27T08:43:57.6030000 Output 5935837 application/pdf Version of Record true 2019-03-27T00:00:00.0000000 true eng
title Quantitative Time Profiling of Children's Activity and Motion
spellingShingle Quantitative Time Profiling of Children's Activity and Motion
Claire Barnes
Cain Clark
Mark Holton
Gareth Stratton
Huw Summers
title_short Quantitative Time Profiling of Children's Activity and Motion
title_full Quantitative Time Profiling of Children's Activity and Motion
title_fullStr Quantitative Time Profiling of Children's Activity and Motion
title_full_unstemmed Quantitative Time Profiling of Children's Activity and Motion
title_sort Quantitative Time Profiling of Children's Activity and Motion
author_id_str_mv 024232879fc13d5ceac584360af8742c
e7cb9f1de82983f71f5065419eec75ff
0e1d89d0cc934a740dcd0a873aed178e
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a61c15e220837ebfa52648c143769427
author_id_fullname_str_mv 024232879fc13d5ceac584360af8742c_***_Claire Barnes
e7cb9f1de82983f71f5065419eec75ff_***_Cain Clark
0e1d89d0cc934a740dcd0a873aed178e_***_Mark Holton
6d62b2ed126961bed81a94a2beba8a01_***_Gareth Stratton
a61c15e220837ebfa52648c143769427_***_Huw Summers
author Claire Barnes
Cain Clark
Mark Holton
Gareth Stratton
Huw Summers
author2 Claire Barnes
Cain Clark
Mark Holton
Gareth Stratton
Huw Summers
format Journal article
container_title Medicine & Science in Sports & Exercise
container_volume 49
container_issue 1
container_start_page 183
publishDate 2017
institution Swansea University
issn 0195-9131
1530-0315
doi_str_mv 10.1249/mss.0000000000001085
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 Introduction The aim of this study was to establish children's mechanical movement patterns during a standardized assessment of fitness by using an accelerometer. Further to this, our objective was to use the information from the accelerometer to profile individual time courses of exercise, across the cohort.Methods A multistage fitness test study was performed with 103 children (mean ± SD age = 10.3 ± 0.6 yr). Children wore an ankle-mounted accelerometer, and gait data were collected on radial acceleration traces obtained at a frequency of 40 Hz. Time-resolved metrics of foot impact force, maximum leg lift angle, and stride frequency were used to profile children's performance across the test duration. A whole-history metric of stride quality, based on the changing ratio of stride length to stride frequency, was used in bivariate analyses of physical performance and body metrics.Results Stride angle derived by our protocol was found to have a strong positive correlation with integrated acceleration, synonymous with counts, widely used in the sport science community (r = 0.81, 0.79, and 0.80 across different stages of the multistage fitness test). Accelerometer data show that differing performance in the test is related to the children's ability to accurately control their gait, with high performers displaying a linearly increasing speed, delivered through stride extension and well matched to the demand level of the test. A negative correlation was found between stride quality and body measures of body mass index (r = −0.61) and body mass (r = −0.60).Conclusion Profiles of the gait parameters provide information on the mechanics of child's motion, allowing detailed assessment of multiple parameter during increasing intensities of exercise.
published_date 2017-01-31T04:00:58Z
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