A Convolution Model for Heart Rate Prediction in Physical Exercise
A Convolution Model for Heart Rate Prediction in Physical Exercise
复制标题
体育运动中心率预测的卷积模型
DOI：
10.5220/0006030901570164
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
A. Asteroth
中科院分区：
文献类型：
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作者：
M. Ludwig;H. Grohganz;A. Asteroth
在运动过程中，心率已被证明是计划锻炼的一个很好的衡量标准。它不仅易于测量，而且易于理解，多年来一直用于锻炼计划。为了使用心率来控制体育锻炼，可以利用依赖于给定应变来预测未来心率的模型。在本文中，我们提出了一个数学模型的基础上卷积预测的心率应变与四个生理上可解释的参数。该模型基于用于性能分析的健身-疲劳模型的总体思想，但在此处进行了修改以用于心率分析。比较表明，卷积模型可以与其他已知的心率模型。此外，这个新的模型可以通过减少参数的数量来改进。其余的参数似乎是一个有希望的指标，实际的主题的健身。
During exercise, heart rate has proven to be a good measure in planning workouts. It is not only simple to measure but also well understood and has been used for many years for workout planning. To use heart rate to control physical exercise, a model which predicts future heart rate dependent on a given strain can be utilized. In this paper, we present a mathematical model based on convolution for predicting the heart rate response to strain with four physiologically explainable parameters. This model is based on the general idea of the Fitness-Fatigue model for performance analysis, but is revised here for heart rate analysis. Comparisons show that the Convolution model can compete with other known heart rate models. Furthermore, this new model can be improved by reducing the number of parameters. The remaining parameter seems to be a promising indicator of the actual subject’s fitness.