Characterization of Heart Rate Variability loss with aging and heart failure using Sample Entropy

R. Goya-Esteban, J. D. de Sá, J. Rojo-Alvarez, Ó. Barquero-Pérez
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引用次数: 17

Abstract

Entropy based measures, such as Sample Entropy (SampEn), have been widely used for quantifying the Heart Rate Variability (HRV) for cardiac risk stratification purposes, with the hypothesis that decreasing entropy points to a perturbation of the complex physiological mechanisms or disease. However, in the literature, higher entropy values have been reported for some pathologies than for healthy subjects, which could be due to the use of a threshold value r tuned relative to the signal standard deviation. In the present paper we apply SampEn to assess the variability of the RR time series from healthy subjects and subjects with Congestive Heart Failure (CHF) in order to discriminate between both groups, as well as to characterize the variability loss due to aging. We conclude that the use of a fixed threshold value r in the SampEn algorithm instead of its conventional setting (as a percentage of the standard deviation of each data series), improves the discrimination capabilities between healthy and CHF subjects, and it allows to quantify the loss of HRV due to aging in healthy subjects.
使用样本熵表征心率变异性随衰老和心力衰竭的损失
基于熵的测量,如样本熵(SampEn),已被广泛用于量化心率变异性(HRV),用于心脏风险分层目的,假设熵的减少表明复杂生理机制或疾病的扰动。然而,在文献中,一些病理的熵值比健康受试者的熵值更高,这可能是由于使用了相对于信号标准差调整的阈值r。在本文中,我们应用SampEn来评估健康受试者和充血性心力衰竭(CHF)受试者RR时间序列的变异性,以便在两组之间进行区分,并表征衰老导致的变异性损失。我们得出的结论是,在SampEn算法中使用固定阈值r而不是其传统设置(作为每个数据系列标准偏差的百分比),提高了健康和CHF受试者之间的区分能力,并且可以量化健康受试者因衰老而导致的HRV损失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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