2001/10/26 by J. Kalda, Jaan Kalda, M. Sakki +8
Biochemistry, Genetics and Molecular Biology · Computer Science · Economics, Econometrics and Finance · Medicine · Physics and Astronomy · #Complex Systems and Time Series Analysis #Data Analysis #FOS: Biological sciences #FOS: Physical sciences #Heart Rate Variability and Autonomic Control #Medical Physics (physics.med-ph) #Quantitative Biology (q-bio) #Statistics and Probability (physics.data-an) #Time Series Analysis and Forecasting #physics.data-an #physics.med-ph #q-bio
paper · pdf · doi:10.48550/arxiv.physics/0110075
4 pages
arxiv created 2001/10/26 · openalex publication_date 2001/10/26 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.