Multiscale analysis of heart rate dynamics: entropy and time irreversibility measures.

Madalena D Costa, Chung-Kang Peng, Ary L Goldberger
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引用次数: 285

Abstract

Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and non-equilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools--multiscale entropy and multiscale time irreversibility--are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs.

心率动力学的多尺度分析:熵和时间不可逆性测量。
心血管信号的分析主要采用传统的时域和频域方法。然而,这些措施不能解释与多尺度组织和非平衡动力学有关的重要性质。因此,传统的信号分析方法和新兴的多尺度技术的互补作用是一个重要的前沿研究领域。本报告的关键发现是,最近开发的两种多尺度计算工具——多尺度熵和多尺度时间不可逆性——能够从基于均值、方差或傅立叶谱(2点相关)技术的传统方法中提取心脏搏动间隔时间序列中不包含的信息。这些新方法在谨慎注意其局限性的情况下,可能在心脏药物的诊断、风险分层和毒性检测方面有用。
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