P. Ch. Ivanov

TL;DR: It is found that periodic trends can severely affect the quantitative analysis of long-range correlations, leading to crossovers and other spurious deviations from power laws, implying both local and global detrending approaches should be applied to properly uncoverLong-range power-law auto-correlations and cross-cor Relations in the random part of the underlying stochastic process.

TL;DR: This work focuses on interbeat interval variability as an important quantity to help elucidate possibly non-homeostatic physiologic variability because (i) the heart rate is under direct neuroautonomic control, and (ii) analysis of these heart rate dynamics may provide important practical diagnostic and prognostic information not obtainable with current approaches.

TL;DR: A general approach to the question of how biological rhythms spontaneously self-regulate is proposed, based on the concept of "stochastic feedback", by considering at a coarse-grained level the neuroautonomic regulation of the heart rate.

TL;DR: Comparing scaling properties of the cardiac dynamics during sleep and wake periods for healthy individuals, cosmonauts during orbital flight, and subjects with severe heart disease finds a greater degree of anticorrelation in the heartbeat fluctuations during sleep compared to wake periods.

TL;DR: In this article, the authors study the dynamics of the awakening during the night for healthy subjects and find that the wake and the sleep periods exhibit completely different behavior: the durations of wake periods are characterized by a scale-free power law distribution, while the duration of sleep periods have an exponential distribution with a characteristic time scale.