Multiscale Poincaré plots for visualizing the structure of heartbeat time series.

Teresa S Henriques,Anton Burykin,Tiago F Silva,Sara Mariani,Filipa Rodrigues,Sara Mariani,Sara Mariani,Ary L Goldberger

doi:10.1186/s12911-016-0252-0

Abstract

BackgroundPoincaré delay maps are widely used in the analysis of cardiac interbeat interval (RR) dynamics. To facilitate visualization of the structure of these time series, we introduce multiscale Poincaré (MSP) plots.MethodsStarting with the original RR time series, the method employs a coarse-graining procedure to create a family of time series, each of which represents the system’s dynamics in a different time scale. Next, the Poincaré plots are constructed for the original and the coarse-grained time series. Finally, as an optional adjunct, color can be added to each point to represent its normalized frequency.ResultsWe illustrate the MSP method on simulated Gaussian white and 1/f noise time series. The MSP plots of 1/f noise time series reveal relative conservation of the phase space area over multiple time scales, while those of white noise show a marked reduction in area. We also show how MSP plots can be used to illustrate the loss of complexity when heartbeat time series from healthy subjects are compared with those from patients with chronic (congestive) heart failure syndrome or with atrial fibrillation.ConclusionsThis generalized multiscale approach to Poincaré plots may be useful in visualizing other types of time series.

Highlights

Poincaré delay maps are widely used in the analysis of cardiac interbeat interval (RR) dynamics
The multiscale Poincaré (MSP) technique consists of three steps: i) construction of the coarse-grained time series; ii) construction of a Poincaré plot for the original and each of the coarsegrained time series, and iii) colorization of the Poincaré plots based on an estimated normalized probability density function
We introduce a novel delay map implementation termed multiscale Poincaré (MSP) plots, to facilitate visualization of multiscale structure of cardiac interbeat interval time series

Summary

Introduction

Poincaré delay maps are widely used in the analysis of cardiac interbeat interval (RR) dynamics. The phase space realization with dimension of two and delay of one is referred to as a Poincaré plot [1,2,3] This graphical method is widely used to visualize and quantify short- and longer-term properties of heart rate variability (HRV) [3,4,5,6,7,8,9,10,11]. We propose a multiscale generalization of the Poincaré plot method, prompted by the observation that physiologic systems generate fluctuations over a broad range of scales. These fluctuations are a marker of the complexity of biologic dynamics, especially in healthy organisms under “free-running” conditions [12,13,14,15]. A variety of computational tools, including fractal and multifractal methods [16,17,18], multiscale entropy [19,20,21,22], and multiscale time irreversibility [23, 24] have been proposed to probe the temporal richness of physiologic signals and of their dynamical alterations with senescence and pathology

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Conclusion