Quantifying physical activity and estimating the metabolic equivalent of tasks based on inertial measurement units has led to the emergence of multiple methods and data reduction approaches known as physical activity metrics. The present study aims to compare those metrics and reduction approaches based on descriptive and high order statistics. Data were obtained from 147 young healthy subjects wearing inertial measurement units at their wrist or ankle during standing, walking and running, labeled as light, medium or vigorous activities. The research question was, first, if those metrics allowed differentiating between light, moderate, and vigorous physical activities, and, secondly, what was the relationship with the metabolic equivalent of the task performed. The results showed that each metric differentiated the level of activity and presented a high correlation with the metabolic equivalent of the task. However, each metric and data reduction approach demonstrated its specific statistical characteristics related to the localization of the sensors. Our findings also confirm the absolute necessity to detail explicitly all calculus and post processing of metrics in order to quantify the level of activity by inertial measurement units.

基于惯性测量单位来量化体力活动和估计任务的代谢当量已导致出现了称为体力活动量度的多种方法和数据缩减方法。本研究旨在比较基于描述性和高阶统计量的那些指标和简化方法。数据来自147位年轻健康受试者，这些受试者在站立，行走和跑步过程中在手腕或脚踝处佩戴惯性测量单位，被标记为轻度，中度或剧烈活动。研究的问题是，首先，这些指标是否可以区分轻度，中度和剧烈的体育活动；其次，与所执行任务的代谢当量有什么关系。结果表明，每个指标都可以区分活动水平，并与任务的代谢当量高度相关。但是，每种度量和数据缩减方法都证明了其与传感器定位有关的特定统计特征。我们的发现还证实了绝对必要地详细列出所有演算和度量的后处理，以便通过惯性测量单位来量化活动水平。