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Activity Mapping of Children in Play Using Multivariate Analysis of Movement Events

Paul Rees Orcid Logo, Joana N. Rocha, Claire Barnes Orcid Logo, Paul Rees, Cain T. Clark, Gareth Stratton, Huw D. Summers

Medicine & Science in Sports & Exercise, Start page: 1

Swansea University Authors: Paul Rees Orcid Logo, Claire Barnes Orcid Logo

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DOI (Published version): 10.1249/MSS.0000000000002119

Abstract

The purpose of this work was to develop an automated measurement technique for the assessment of both the form and intensity of physical activity undertaken by children during play. Further to this, our aim was to profile the varying activity across a cohort of children using a multivariate analysis...

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Published in: Medicine & Science in Sports & Exercise
ISSN: 0195-9131
Published: 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa51987
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Abstract: The purpose of this work was to develop an automated measurement technique for the assessment of both the form and intensity of physical activity undertaken by children during play. Further to this, our aim was to profile the varying activity across a cohort of children using a multivariate analysis of their movement patterns. Methods: Ankle-worn accelerometers were used to record 40-minutes of activity during a school recess, for 24 children over 5 consecutive days. Epochs of 1.1 second duration were identified within the acceleration time trace and compared to a reference motif, consisting of a single walking stride acceleration trace, obtained in a controlled setting of the motion lab. Dynamic time warping (DTW) of motif and activity events provided metrics of comparative movement duration and intensity, which formed the data set for multivariate mapping of the cohort activity using a principal component analysis (PCA). Results: The 2-D PCA plot provided clear differentiation of children displaying diverse activity profiles and clustering of those with similar movement patterns. The 1 component of the PCA correlated to the integrated intensity of movement over the 40 min. period whilst the 2 component informed on the temporal phasing of activity. Conclusion: By defining movement events and then quantifying them by reference to a motion-standard, meaningful assessment of highly varied activity within free play can be obtained. This allows detailed profiling of individual children's activity and provides an insight on social aspects of play through identification of matched activity time profiles for children participating in conjoined play.
Keywords: Accelerometry, Multivariate analysis of movement, Principal Component Analysis, Cluster Analysis
College: Faculty of Science and Engineering
Start Page: 1

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