Information scaling properties of heart rate variability.

Many chaos detection methods have proven inherently ambiguous in that they yield similar results for chaotic signals and correlated noise. The purpose of this work was to determine whether human resting heart period sequences have global properties characteristic of chaotic systems. We investigated the inherent global organization of heart period sequences by quantifying how the information content of the embedded sequences varied as a function of scale. We compared the information scaling characteristics of 60-min heart period sequences obtained from 10 healthy resting volunteers with those obtained from numerous periodic and chaotic control sequences. The information scaling properties of the heart period sequences were significantly different from those obtained for the controls, particularly at the coarsest scales (P = 0.0003 vs. low-dimensional periodic controls; P = 0.0005 vs. low-dimensional chaotic controls; P = 0.0003 vs. low-dimensional periodic and chaotic controls). We also showed that nondeterministic components, such as large tachycardic (or bradycardic) events or aperiodic fluctuations, can lead to scaling characteristics similar to those observed for the resting heart period sequences. This, in addition to previous evidence from spectral, nonlinear predictability and lexical studies, favors an events-based approach to understanding heart rate variability.