Centre for Sport, Exercise and Life Sciences (CSELS), Coventry University, Coventry CV1 5FB, UK; Engineering Behaviour Analytics in Sport and Exercise (EBASE) Research group, School of Sports and Exercise Sciences, Swansea University, Bay Campus, Fabian Way, Swansea SA1 8EN, UK.
Engineering Behaviour Analytics in Sport and Exercise (EBASE) Research group, School of Sports and Exercise Sciences, Swansea University, Bay Campus, Fabian Way, Swansea SA1 8EN, UK; Systems and Process Engineering Centre, College of Engineering, Swansea University, Bay Campus, Fabian Way, Swansea SA1 8EN, UK.
Hum Mov Sci. 2019 Dec;68:102523. doi: 10.1016/j.humov.2019.102523. Epub 2019 Nov 1.
While 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.
Sixty-five children (38 boys, 4.3 ± 0.7y, 1.04 ± 0.05 m, 17.8 ± 3.2 kg, BMI; 16.2 ± 1.9 kg∙m) 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.
Two 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).
The 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.
虽然已经使用新的分析方法来检查运动行为，但迄今为止，尚无研究探讨基于频率的测量（如光谱纯度）是否有助于解释人类运动的关键方面。本研究旨在使用主成分分析来研究运动和步态质量、身体活动和运动能力。
本研究纳入了 65 名儿童（38 名男孩，4.3±0.7 岁，1.04±0.05 米，17.8±3.2 千克，体重指数；16.2±1.9 千克∙米）。测量包括加速度计测量的身体活动和运动质量（光谱纯度）、运动能力（儿童运动评估第二版；MABC2）、身高、体重和腰围。对所有数据进行主成分分析，并使用 Cronbach's alpha 评估结果成分的内部一致性。
发现了两个具有优异内部一致性（Cronbach α>0.9）的主成分；第一个主成分，称为“运动成分”，包含光谱纯度、交通灯 MABC2 得分、精细运动%和大运动%（α=0.93）；第二个主成分，称为“人体测量成分”，包含体重、BMI、BMI%和体脂%（α=0.91）。
本研究的结果表明，加速度计分析可用于自动评估运动能力，并且光谱纯度是与儿童运动质量相关的有意义的、指示性的指标。
