Investigation of linear and nonlinear properties of a heartbeat time series using multiscale Rényi entropy

Herbert F. Jelinek*, David J. Cornforth, Mika P. Tarvainen, Kinda Khalaf

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
4 Downloads (Pure)


The time series of interbeat intervals of the heart reveals much information about disease and disease progression. An area of intense research has been associated with cardiac autonomic neuropathy (CAN). In this work we have investigated the value of additional information derived from the magnitude, sign and acceleration of the RR intervals. When quantified using an entropy measure, these time series show statistically significant differences between disease classes of Normal, Early CAN and Definite CAN. In addition, pathophysiological characteristics of heartbeat dynamics provide information not only on the change in the system using the first difference but also the magnitude and direction of the change measured by the second difference (acceleration) with respect to sequence length. These additional measures provide disease categories to be discriminated and could prove useful for non-invasive diagnosis and understanding changes in heart rhythm associated with CAN.

Original languageEnglish
Article number727
Pages (from-to)1-14
Number of pages14
Issue number8
Publication statusPublished - Aug 2019

Bibliographical note

Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


  • heart rate variability
  • entropy
  • nonlinear dynamics
  • cardiac autonomic neuropathy
  • diabetes

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