Critical Scale-invariance in Healthy Human Heart Rate

Human heart rate is known to display complex fluctuations. Evidence of multifractality in heart rate fluctuations in healthy state has been reported [Ivanov et al., Nature {\bf 399}, 461 (1999)]. This multifractal character could be manifested as a dependence on scale or beat number of the probability density functions (PDFs) of the heart rate increments. On the other hand, scale invariance has been recently reported in a detrended analysis of healthy heart rate increments [K...

Recent evidence suggests that physiological signals under healthy conditions may have a fractal temporal structure. We investigate the possibility that time series generated by certain physiological control systems may be members of a special class of complex processes, termed multifractal, which require a large number of exponents to characterize their scaling properties. We report on evidence for multifractality in a biological dynamical system --- the healthy human heartbe...

We introduce a segmentation algorithm to probe temporal organization of heterogeneities in human heartbeat interval time series. We find that the lengths of segments with different local values of heart rates follow a power-law distribution. This scale-invariant structure is not a simple consequence of the long-range correlations present in the data. We also find that the differences in mean heart rates between consecutive segments display a common functional form, but with d...

Evidence of discrete scale invariance (DSI) in daytime healthy heart rate variability (HRV) is presented based on the log-periodic power law scaling of the heart beat interval increment. Our analysis suggests multiple DSI groups and a dynamic cascading process. A cascade model is presented to simulate such a property.

Human heart rate fluctuates in a complex and non-stationary manner. Elaborating efficient and adequate tools for the analysis of such signals has been a great challenge for the researchers during last decades. Here, an overview of the main research results in this field is given. The following question are addressed: (a) what are the intrinsic features of the heart rate variability signal; (b) what are the most promising non-linear measures, bearing in mind clinical diagnosti...

It is shown that the distribution of low variability periods in the activity of human heart rate typically follows a multi-scaling Zipf's law. The presence or failure of a power law, as well as the values of the scaling exponents, are personal characteristics depending on the daily habits of the subjects. Meanwhile, the distribution function of the low-variability periods as a whole discriminates efficiently between various heart pathologies. This new technique is also applic...

Normal human heart rate shows complex fluctuations in time, which is natural, since heart rate is controlled by a large number of different feedback control loops. These unpredictable fluctuations have been shown to display fractal dynamics, long-term correlations, and 1/f noise. These characterizations are statistical and they have been widely studied and used, but much less is known about the detailed time evolution (dynamics) of the heart rate control mechanism. Here we sh...

We analyze heartbeat interval recordings from two independent databases: (a) 19 healthy young (avg. age 25.7 years) and 16 healthy elderly subjects (avg. age 73.8 years) during 2h under resting conditions from the Fantasia database; and (b) 29 healthy elderly subjects (avg. age 75.9 years) during $\approx{}8$h of sleep from the SHHS database, and the same subjects recorded 5 years later. We quantify: (1) The average heart rate <RR>; (2) the SD $\sigma_{RR}$ and $\sigma_{\Delt...

Many physical and physiological signals exhibit complex scale-invariant features characterized by $1/f$ scaling and long-range power-law correlations, suggesting a possibly common control mechanism. Specifically, it has been suggested that dynamical processes influenced by inputs and feedback on multiple time scales may be sufficient to give rise to $1/f$ scaling and scale invariance. Two examples of physiologic signals that are the output of hierarchical, multi-scale physiol...

We present the first systematic evidence for the origins of 1/f-type temporal scaling in human heart rate. The heart rate is regulated by the activity of two branches of the autonomic nervous system: the parasympathetic (PNS) and the sympathetic (SNS) nervous systems. We examine alterations in the scaling property when the balance between PNS and SNS activity is modified, and find that the relative PNS suppression by congestive heart failure results in a substantial increase ...