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最常用于心率时间序列的非线性方法:综述

Nonlinear Methods Most Applied to Heart-Rate Time Series: A Review.

作者信息

Henriques Teresa, Ribeiro Maria, Teixeira Andreia, Castro Luísa, Antunes Luís, Costa-Santos Cristina

机构信息

Centre for Health Technology and Services Research (CINTESIS), Faculty of Medicine University of Porto, 4200-450 Porto, Portugal.

Health Information and Decision Sciences Department-MEDCIDS, Faculty of Medicine, University of Porto, 4200-450 Porto, Portugal.

出版信息

Entropy (Basel). 2020 Mar 9;22(3):309. doi: 10.3390/e22030309.

Abstract

The heart-rate dynamics are one of the most analyzed physiological interactions. Many mathematical methods were proposed to evaluate heart-rate variability. These methods have been successfully applied in research to expand knowledge concerning the cardiovascular dynamics in healthy as well as in pathological conditions. Notwithstanding, they are still far from clinical practice. In this paper, we aim to review the nonlinear methods most used to assess heart-rate dynamics. We focused on methods based on concepts of chaos, fractality, and complexity: Poincaré plot, recurrence plot analysis, fractal dimension (and the correlation dimension), detrended fluctuation analysis, Hurst exponent, Lyapunov exponent entropies (Shannon, conditional, approximate, sample entropy, and multiscale entropy), and symbolic dynamics. We present the description of the methods along with their most notable applications.

摘要

心率动态是研究最为深入的生理相互作用之一。人们提出了许多数学方法来评估心率变异性。这些方法已成功应用于研究中,以拓展有关健康及病理状态下心血管动力学的知识。尽管如此,它们仍与临床实践相差甚远。在本文中,我们旨在综述最常用于评估心率动态的非线性方法。我们重点关注基于混沌、分形和复杂性概念的方法:庞加莱图、递归图分析、分形维数(及关联维数)、去趋势波动分析、赫斯特指数、李雅普诺夫指数熵(香农熵、条件熵、近似熵、样本熵和多尺度熵)以及符号动力学。我们介绍了这些方法及其最显著的应用。

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