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用于心率变异性频谱分析的心电图采样频率。

Sampling frequency of the electrocardiogram for spectral analysis of the heart rate variability.

作者信息

Merri M, Farden D C, Mottley J G, Titlebaum E L

机构信息

Department of Electrical Engineering, University of Rochester, NY 14627.

出版信息

IEEE Trans Biomed Eng. 1990 Jan;37(1):99-106. doi: 10.1109/10.43621.

Abstract

The R-R interval measurement from digitized electrocardiograms (ECG) contains an error due to the finite sampling frequency which may jeopardize the beat-to-beat analysis of the heart rate. In this paper, we develop a model to describe and quantitate this error. The "measured" R-R interval is modeled as the sum of the "true" R-R interval and of the error of measurement. The first and second order statistics of the error are computed in order to investigate its influence on the heart rate variability (HRV) power spectrum. They are found to be only functions of the ECG sampling frequency and, in particular, the power spectrum of the error contributes an additive high-pass filter-like term (colored noise) to the power spectrum of the HRV. The accuracy of the model is tested via a simulation procedure. The model indicates that the relative balance between the HRV and the error power spectra is important and should be checked before any variability analysis on the heart rate. This balance may be favorable to the error when 1) the sampling frequency of the ECG is too low, and/or 2) the variability of the heart rate is too little. In these cases, the HRV spectrum analysis may not give reliable results. Two tests are proposed in order to evaluate the error influence either in specific frequency bands or in the total frequency range.

摘要

数字化心电图(ECG)测量的R-R间期存在误差,这是由于采样频率有限所致,该误差可能会危及心率的逐搏分析。在本文中,我们开发了一个模型来描述和量化此误差。“测量的”R-R间期被建模为“真实的”R-R间期与测量误差之和。计算误差的一阶和二阶统计量,以研究其对心率变异性(HRV)功率谱的影响。发现它们仅是ECG采样频率的函数,特别是误差的功率谱为HRV的功率谱贡献了一个类似高通滤波器的附加项(有色噪声)。通过模拟程序测试模型的准确性。该模型表明,HRV与误差功率谱之间的相对平衡很重要,在对心率进行任何变异性分析之前都应进行检查。当1)ECG的采样频率过低,和/或2)心率变异性过小时,这种平衡可能有利于误差。在这些情况下,HRV频谱分析可能无法给出可靠的结果。提出了两项测试,以评估特定频段或整个频率范围内的误差影响。

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