Heart Rate Fragmentation: A New Approach to the Analysis of Cardiac Interbeat Interval Dynamics

Abstract

Background: Short-term heart rate variability (HRV) is most commonly attributed to physiologic vagal tone modulation. However, with aging and cardiovascular disease, the emergence of high short-term HRV, consistent with the breakdown of the neuroautonomic-electrophysiologic control system, may confound traditional HRV analysis. An apparent dynamical signature of such anomalous short-term HRV is frequent changes in heart rate acceleration sign, defined here as heart rate fragmentation.Objective: The aims were to: (1) introduce a set of metrics designed to probe the degree of sinus rhythm fragmentation; (2) test the hypothesis that the degree of fragmentation of heartbeat time series increases with the participants' age in a group of healthy subjects; (3) test the hypothesis that the heartbeat time series from patients with advanced coronary artery disease (CAD) are more fragmented than those from healthy subjects; and (4) compare the performance of the new fragmentation metrics with standard time and frequency domain measures of short-term HRV.Methods: We analyzed annotated, open-access Holter recordings (University of Rochester Holter Warehouse) from healthy subjects and patients with CAD using these newly introduced metrics of heart rate fragmentation, as well as standard time and frequency domain indices of short-term HRV, detrended fluctuation analysis and sample entropy.Results: The degree of fragmentation of cardiac interbeat interval time series increased significantly as a function of age in the healthy population as well as in patients with CAD. Fragmentation was higher for the patients with CAD than the healthy subjects. Heart rate fragmentation metrics outperformed traditional short-term HRV indices, as well as two widely used nonlinear measures, sample entropy and detrended fluctuation analysis short-term exponent, in distinguishing healthy subjects and patients with CAD. The same level of discrimination was obtained from the analysis of normal-to-normal sinus (NN) and cardiac interbeat interval (RR) time series.Conclusion: The fragmentation framework and accompanying metrics introduced here constitute a new way of assessing short-term HRV under free-running conditions, one which appears to overcome salient limitations of traditional HRV analysis. Fragmentation of sinus rhythm cadence may provide new dynamical biomarkers for probing the integrity of the neuroautonomic-electrophysiologic network controlling the heartbeat in health and disease.

Beat-to-Beat Patterning of Sinus Rhythm Reveals Non-linear Rhythm in the Dog Compared to the Human

“…Heart rate variability is influenced by multiple inputs of central and peripheral parasympathetic and sympathetic modulation (Evans et al, 1990;Goldberger et al, 1994;Cerutti et al, 1995;Roossien et al, 1997;Stein et al, 2005;Billman, 2011Billman, , 2013Billman et al, 2015b;Shaffer and Ginsberg, 2017;Behar et al, 2018a,b). The variability results from complex interactions and cannot be simplified to say that high variability universally indicates high parasympathetic modulation (Goldberger et al, 1994;Costa et al, 2017;Shaffer and Ginsberg, 2017;Hayano and Yuda, 2019). Both groups of dogs in this study had greater variability using traditional time domain indices than in humans.…”

“…These include the area of the ellipse (width/length), which represents total heart rate variability, the standard deviation perpendicular to the line of identity and the standard deviation along the line of identity. Newly developed methods to better understand the variability in the sinus rhythm have been developed and deserve further evaluation in different species (Costa et al, 2017).…”

Heart Rate Variability in Children and Adolescents with Cerebral Palsy—A Systematic Literature Review

“…Developing a better understanding of ANS activity in patients with CP is required to better understand cardiovascular diseases in this group of patients. Moreover, studies highlight the importance of non-autonomic influences in HRV [129][130][131], which are also a potential source of important information to understand the impairments in patients with CP and should be taken into account in future studies.…”

Implementing a Web-based Application for Analysis and Evaluation of Heart Rate Variability Using Serverless Architecture

“…These methods determine the degree of irregularity of the RR time series. The low entropy values are characteristic of regular time series, while higher values are inherent in stochastic data [1].…”

“…Increasingly, the attention of specialists is attracted by non-invasive methods for the examination of patients based on the principle of tracking different body system indicators [1]. The heart rate of the body is one of the most accessible physiological parameters, and it reflects the processes of vegetative regulation in the cardiovascular system.…”