Graduate Institute of Sports Science, National Taiwan Sport University, Taoyuan, Taiwan.
Department of Physical Medicine and Rehabilitation, Taipei City Hospital, Zhongxiao Branch, Taipei City, Taiwan.
Sci Rep. 2020 Jun 1;10(1):8816. doi: 10.1038/s41598-020-65713-7.
Due to the nature of micro-electromechanical systems, the vector magnitude (VM) activity of accelerometers varies depending on the wearing position and does not identify different levels of physical fitness. Without an appropriate energy expenditure (EE) estimation equation, bias can occur in the estimated values. We aimed to amend the EE estimation equation using heart rate reserve (HRR) parameters as the correction factor, which could be applied to athletes and non-athletes who primarily use ankle-mounted devices. Indirect calorimetry was used as the criterion measure with an accelerometer (ankle-mounted) equipped with a heart rate monitor to synchronously measure the EE of 120 healthy adults on a treadmill in four groups. Compared with ankle-mounted accelerometer outputs, when the traditional equation was modified using linear regression by combining VM with body weight and/or HRR parameters (modified models: Model A, without HRR; Model B, with HRR), both Model A (r: 0.931 to 0.972; ICC: 0.913 to 0.954) and Model B (r: 0.933 to 0.975; ICC: 0.930 to 0.959) showed the valid and reliable predictive ability for the four groups. With respect to the simplest and most reasonable mode, Model A seems to be a good choice for predicting EE when using an ankle-mounted device.
由于微机电系统的性质，加速度计的矢量幅度（VM）活动随佩戴位置而变化，无法识别不同水平的身体健康状况。如果没有适当的能量消耗（EE）估计方程，估计值可能会出现偏差。我们旨在使用心率储备（HRR）参数作为校正因子来修正 EE 估计方程，该方程可应用于主要使用脚踝安装设备的运动员和非运动员。间接量热法被用作标准测量方法，使用配备心率监测器的加速度计（脚踝安装）在跑步机上同步测量 120 名健康成年人的 EE，共分为四组。与脚踝安装的加速度计输出相比，当使用线性回归通过将 VM 与体重和/或 HRR 参数相结合（修正模型：无 HRR 的模型 A，有 HRR 的模型 B）来修正传统方程时，模型 A（r：0.931 到 0.972；ICC：0.913 到 0.954）和模型 B（r：0.933 到 0.975；ICC：0.930 到 0.959）均显示出对四组数据具有良好的预测能力。就最简单和最合理的模式而言，对于使用脚踝安装设备时预测 EE，模型 A 似乎是一个不错的选择。
