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Determining Energy Expenditure From Treadmill Walking Using Hip-Worn Inertial Sensors: An Experimental Study

机译:使用髋关节惯性传感器确定跑步机行走的能量消耗:一项实验研究

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摘要

We describe an experimental study to estimate energy expenditure during treadmill walking using a single hip-mounted inertial sensor (triaxial accelerometer and triaxial gyroscope). Typical physical-activity characterization using commercial monitors use proprietary counts that do not have a physically interpretable meaning. This paper emphasizes the role of probabilistic techniques in conjunction with inertial data modeling to accurately predict energy expenditure for steady-state treadmill walking. We represent the cyclic nature of walking with a Fourier transform and show how to map this representation to energy expenditure ( $dot{V}hbox{O}_{2}$, mL/min) using three regression techniques. A comparative analysis of the accuracy of sensor streams in predicting energy expenditure reveals that using triaxial information leads to more accurate energy-expenditure prediction compared to only using one axis. Combining accelerometer and gyroscope information leads to improved accuracy compared to using either sensor alone. Nonlinear regression methods showed better prediction accuracy compared to linear methods but required an order of higher magnitude run time.
机译:我们描述了一项实验研究,以估计使用单个安装在臀部的惯性传感器(三轴加速度计和三轴陀螺仪)在跑步机上行走时的能量消耗。使用商用监视器进行的典型体育活动表征使用的专有计数没有物理上可解释的含义。本文强调了概率技术与惯性数据建模相结合的作用,以准确预测稳态跑步机的能量消耗。我们使用傅立叶变换表示行走的循环性质,并展示如何使用三种回归技术将此表示形式映射到能量消耗($ dot {V} hbox {O} _ {2} $,mL / min)。对传感器流预测能量消耗的准确性的比较分析表明,与仅使用一个轴相比,使用三轴信息可以更准确地预测能量消耗。与单独使用任一传感器相比,结合使用加速度计和陀螺仪信息可以提高精度。与线性方法相比,非线性回归方法显示出更好的预测精度,但需要更高数量级的运行时间。

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