Journal article 763 views 220 downloads
Physical activity, motor competence and movement and gait quality: A principal component analysis
,
Michael J. Duncan,
Huw Summers ,
Gareth Stratton
Human Movement Science, Volume: 68, Start page: 102523
Swansea University Authors:
Claire Barnes , Huw Summers , Gareth Stratton
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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...
| Published in: | Human Movement Science |
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| ISSN: | 0167-9457 |
| Published: |
Elsevier BV
2019
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa52054 |
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| 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, 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. |
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| Start Page: |
102523 |