Zipf's law in human heartbeat dynamics

Abstract

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 applicable to other non-linear time-series and reflects these aspects of the underlying intermittent dynamics, which are not covered by other methods of linear- and nonlinear analysis.

4 pages

Cited by in corpus (4)

• Generalized (m,k)-Zipf law for fractional Brownian motion-like time series with or without effect of an additional linear trend
• Scaling analysis of multivariate intermittent time series
• Non-linear and scale-invariant analysis of the Heart Rate Variability
• Properties of low variability periods in financial time series