A comparison of energy expenditure estimation of several physical activity monitors.
A comparison of energy expenditure estimation of several physical activity monitors.
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DOI：
10.1249/mss.0b013e318299d2eb
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发表时间：
2013-11
影响因子：
4.1
通讯作者：
Browning RC
中科院分区：
文献类型：
--
作者：
Dannecker KL;Sazonova NA;Melanson EL;Sazonov ES;Browning RC
准确、准确地估算自由生活能量消耗(EE)对于监测能量平衡和量化体力活动具有重要意义。最近，单传感器和多传感器设备已经开发出来，可以对身体活动进行分类，潜在地改善了EE的估计。为了确定基于鞋类的体力活动监测器的EE估计的有效性，并将该有效性与各种研究和消费者体力活动监测器进行比较。19名健康的年轻人(10名男性，9名女性)在一个房间的热量计中停留了4个小时。参与者佩戴了鞋类体力活动监测器，以及Actical、Actigraph、Ideea、DirectLife和Fitbit设备。每个人都做了一系列的姿势/活动。我们开发了模型来估计基于鞋类的设备的EE，并使用制造商的软件来估计所有其他设备的EE。使用鞋基设备估计的EE与测量的EE(分别为476(20)和478(18)千卡)(平均值(SE))没有显著差异，均方根误差(RMSE)为29.6千卡(6.2%)。Ideea和DirectLlife对EE的估计与测量的EE没有显着差异，但Actigraph和Fitbit设备明显低估了EE。ACTIC、DirectLife、Ideea、Actigraph和Fitbit的均方根误差分别为93.5kcal(19%)、62.1kcal(14%)、88.2kcal(18%)、136.6 kcal(27%)、130.1 kcal(26%)和143.2 kcal(28%)。基于鞋子的体力活动监测器提供了有效的EE估计，而其他被测试的体力活动监测器在估计EE时具有广泛的有效性。我们的结果还表明，基于体力活动分类的估计EE比基于总体力活动的估计EE更准确和精确。
Accurately and precisely estimating free-living energy expenditure (EE) is important for monitoring energy balance and quantifying physical activity. Recently, single and multi-sensor devices have been developed that can classify physical activities, potentially resulting in improved estimates of EE. To determine the validity of EE estimation of a footwear-based physical activity monitor and to compare this validity against a variety of research and consumer physical activity monitors. Nineteen healthy young adults (10 male, 9 female), completed a four-hour stay in a room calorimeter. Participants wore a footwear-based physical activity monitor, as well as Actical, Actigraph, IDEEA, DirectLife and Fitbit devices. Each individual performed a series of postures/activities. We developed models to estimate EE from the footwear-based device, and we used the manufacturer's software to estimate EE for all other devices. Estimated EE using the shoe-based device was not significantly different than measured EE (476(20) vs. 478(18) kcal) (Mean (SE)), respectively, and had a root mean square error (RMSE) of (29.6 kcal (6.2%)). The IDEEA and DirectLlife estimates of EE were not significantly different than the measured EE but the Actigraph and Fitbit devices significantly underestimated EE. Root mean square errors were 93.5 (19%), 62.1 kcal (14%), 88.2 kcal (18%), 136.6 kcal (27%), 130.1 kcal (26%), and 143.2 kcal (28%) for Actical, DirectLife, IDEEA, Actigraph and Fitbit respectively. The shoe based physical activity monitor provides a valid estimate of EE while the other physical activity monitors tested have a wide range of validity when estimating EE. Our results also demonstrate that estimating EE based on classification of physical activities can be more accurate and precise than estimating EE based on total physical activity.