Outlier-resilient complexity analysis of heartbeat dynamics.
Complexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice. Here we propose a new approach to estimate the complexity in a signal by analyzing the irregularity of the sign time series of its coarse-grained time series at different time scales. Using surrogate data, we show that the method can reliably assess the complexity in noisy data while being highly resilient to outliers. We further apply this method to the analysis of human heartbeat recordings. Without removing any outliers due to ectopic beats, the method is able to detect a degradation of cardiac control in patients with congestive heart failure and a more degradation in critically ill patients whose life continuation relies on extracorporeal membrane oxygenator (ECMO). Moreover, the derived complexity measures can predict the mortality of ECMO patients. These results indicate that the proposed method may serve as a promising tool for monitoring cardiac function of patients in clinical settings.
1] Research Center for Adaptive Data Analysis &Center for Dynamical Biomarkers and Translational Medicicne, National Central University, Taoyuan, Taiwan [2] Medical Biodynamics Program, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, 221 Longwood Avenue, Boston, MA 02115, USA.
Men-Tzung
MT
Lo
1] Research Center for Adaptive Data Analysis &Center for Dynamical Biomarkers and Translational Medicicne, National Central University, Taoyuan, Taiwan [2] Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan.
Yi-Chung
YC
Chang
Research Center for Adaptive Data Analysis &Center for Dynamical Biomarkers and Translational Medicicne, National Central University, Taoyuan, Taiwan.
Chen
C
Lin
Research Center for Adaptive Data Analysis &Center for Dynamical Biomarkers and Translational Medicicne, National Central University, Taoyuan, Taiwan.
Hsu-Wen Vincent
HW
Young
Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
Yen-Hung
YH
Lin
Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
Yi-Lwun
YL
Ho
Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, Massachusetts, USA.
Chung-Kang
CK
Peng
1] Medical Biodynamics Program, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, 221 Longwood Avenue, Boston, MA 02115, USA [2] Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.
Kun
K
Hu
D004562:Electrocardiography; D006321:Heart / Q000502:physiology*; D006331:Heart Diseases / Q000503:physiopathology; D006339:Heart Rate; D006801:Humans; D008954:Models, Biological