Introduction: Heart rate variability (HRV) analysis, is a common tool used in cardiovascular physiology research because it is a non-invasive tool that can be used for assessing the heart functions. To date, standard HRV analysis tools have been mainly available for analysis of human (i.e. a single mammal) electrocardiographic (i.e. whole innervated heart) signals. In this work we extend HRV research to two new dimensions: (1) the other mammalian species and (2) the level of integration (i.e. sinoatrial cell, tissue and whole heart).
Methods: We analyzed the beating rate variability (BRV) across the two new dimensions. For that purpose we used published databases of electrocardiograms from four mammal types (human (n=18), dog (n=17), rabbit (n=4) and mouse (n=7)) and computed the BRV measures for each type of mammal. We also analyzed electrophysiological data from rabbits at different level of integrations: sinoatrial node tissue (n=8) and in vivo hearts (n=9). The data was analyzed using the open source PhysioZoo program.
Results: Power spectral analysis of the heart rate of the four mammalian species revealed that the mouse is a better animal model for the study of vagal nerve stimulation. The study of sample entropy (SampEn) across the different species revealed a power-law relationship between SampEn and the body mass index. This suggests that the complexity of the beating interval time series is decreased with the mammalian size. Analysis of the rabbit data at different level of integrations showed that single sinoatrial node tissue conserved long term beating variability information but had reduced complexity in comparison to the in vivo heart.
Conclusions: Studying the BRV across two new dimensions can provide new physiological insights on cardiac function.