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Remote physiological and GPS data processing in evaluation of physical activities

机译:远程生理和GPS数据处理可评估身体活动

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摘要

The monitoring of data from global positioning system (GPS) receivers and remote sensors of physiological and environmental data allow forming an information database for observed data processing. In this paper, we propose the use of such a database for the analysis of physical activities during cycling. The main idea of the proposed algorithm is to use cross-correlations between the heart rate and the altitude gradient to evaluate the delay between these variables and to study its time evolution. The data acquired during 22 identical cycling routes, each about 130 km long, include more than 6,700 segments of length 60 s recorded with varying sampling periods. General statistical and digital signal processing methods used include mathematical tools to reject gross errors, resampling using selected interpolation methods, digital filtering of noise signal components, and estimating cross-correlations between the position data and the physiological signals. The results of a regression between GPS and physiological data include the estimate of the time delay between the heart rate change and gradient altitude of about 7.5 s and its decrease during each training route.
机译:对来自全球定位系统(GPS)接收器以及生理和环境数据的远程传感器的数据的监视,可以形成一个用于观察数据处理的信息数据库。在本文中,我们建议使用这种数据库来分析自行车运动中的身体活动。该算法的主要思想是利用心率和海拔梯度之间的互相关来评估这些变量之间的延迟并研究其时间演变。在22条相同的自行车路线(每条路线长约130公里)中获取的数据包括超过6700个长度为60 s的路段,记录了不同的采样周期。所使用的常规统计和数字信号处理方法包括数学工具,用于拒绝严重误差,使用选定的插值方法进行重采样,对噪声信号分量进行数字滤波以及估计位置数据与生理信号之间的互相关性。 GPS和生理数据之间的回归结果包括对心率变化和梯度高度之间约7.5 s的时间延迟及其在每个训练路线中的下降的估计。

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