Prediction of Physical Activity Intensity with Accelerometry in Young Children
Prediction of Physical Activity Intensity with Accelerometry in Young Children
复制标题
DOI：
10.3390/ijerph16060931
复制
发表时间：
2019-03-02
影响因子：
--
通讯作者：
Tanaka, Shigeho
中科院分区：
文献类型：
--
作者：
Tanaka, Chiaki;Hikihara, Yuki;Tanaka, Shigeho
背景资料：已开发出一种算法，用于使用三轴加速度计测量的未经过滤的合成加速度和预测模型的身体活动强度（MET）在成年人和小学儿童的比率进行非卧床和非卧床活动的分类。本研究的目的是推导出一个类似的算法在幼儿MET的预测方程。方法：37名健康的日本儿童（4 - 6岁）参加了这项研究。选择了五种非步行活动，包括低强度活动和五种步行活动。使用三轴加速度计的原始加速度和使用道格拉斯袋法的间接量热法的能量消耗在每个活动期间被收集。结果如下：对于非步行活动，特别是轻度非步行活动，具有预定截距（0.9）的线性回归方程或二次方程比线性回归更好。这些公式与成人和小学生的公式不同。另一方面，在非步行活动中，未过滤的合成加速度与过滤的合成加速度的比值与步行活动中的合成加速度的比值不同，如成人和小学儿童。结论：我们的幼儿校正模型可以准确地预测体力活动的强度，包括低强度的非步行活动。
Background: An algorithm for the classification of ambulatory and non-ambulatory activities using the ratio of unfiltered to filtered synthetic acceleration measured with a triaxial accelerometer and predictive models for physical activity intensity (METs) in adults and in elementary school children has been developed. The purpose of the present study was to derive predictive equations for METs with a similar algorithm in young children. Methods: Thirty-seven healthy Japanese children (four- to six-years old) participated in this study. The five non-ambulatory activities including low-intensity activities, and five ambulatory activities were selected. The raw accelerations using a triaxial accelerometer and energy expenditure by indirect calorimetry using the Douglas bag method during each activity were collected. Results: For non-ambulatory activities, especially light-intensity non-ambulatory activities, linear regression equations with a predetermined intercept (0.9) or quadratic equations were a better fit than the linear regression. The equations were different from those for adults and elementary school children. On the other hand, the ratios of unfiltered to filtered synthetic acceleration in non-ambulatory activities were different from those in ambulatory activities, as in adults and elementary school children. Conclusions: Our calibration model for young children could accurately predict intensity of physical activity including low-intensity non-ambulatory activities.