Multiscale Poincaré plots for visualizing the structure of heartbeat time series

BMC Medical Informatics and Decision Making

Technical Advance

Anton Burykin¹  Tiago F. Silva²  Filipa Rodrigues²  Sara Mariani³  Ary L. Goldberger⁴  Teresa S. Henriques⁵ 

[1] Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA;Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA;Department of Physics, Faculty of Sciences, University of Lisbon, Lisbon, Portugal;Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA;Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA;Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA;Margret and H.A. Rey Institute of Nonlinear Dynamics in Physiology and Medicine, Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Boston, MA, USA;Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA; Center for Anesthesia Research and Excellence (CARE), Beth Israel Deaconess Medical Center, Boston, MA, USA;Margret and H.A. Rey Institute of Nonlinear Dynamics in Physiology and Medicine, Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Boston, MA, USA;

关键词: Atrial fibrillation;    Complexity;    Congestive heart failure;    Fractal;    Heart rate;    Multiscale;    Nonlinear dynamics;    Poincaré plot;    Time series;    Visualization;   

DOI  :  10.1186/s12911-016-0252-0

 received in 2015-10-09, accepted in 2016-01-27,  发布年份 2016

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY   
© Henriques et al. 2016