Symbolic dynamics and complexity in a physiological time series

J.J. Żebrowski , W. Popl̶awska , R. Baranowski , Teodor Buchner


A general approach to non-stationary data from a non-linear dynamical time series is presented. As an application, the RR intervals extracted from the 24 h electrocardiograms of 60 healthy individuals 16–64 yr of age are analyzed with the use of a sliding time window of 100 intervals. This procedure maps the original time series into a time series of the given complexity measure. The state of the system is then given by the properties of the distribution of the complexity measure. The relation of the complexity measures to the level of the catecholamine hormones in the plasma, their dependence on the age of the subject, their mutual correlation and the results of surrogate data tests are discussed. Two different approaches to analyzing complexity are used: pattern entropy as a measure of statistical order and algorithmic complexity as a measure sequential order in heart rate variability. These two complexity measures are found to reflect different aspects of the neuroregulation of the heart. Finally, in some subjects (usually younger persons) the two complexity measures depend on their age while in others (mostly older subjects) they do not – in which case the correlation between is lost.
Author J.J. Żebrowski - [Warsaw University of Technology (PW)]
J.J. Żebrowski,,
- Politechnika Warszawska
, W. Popl̶awska - [Instytut Kardiologii im. Prymasa Tysiaclecia Stefana Kardynala Wyszynskiego]
W. Popl̶awska,,
, R. Baranowski - [Instytut Kardiologii im. Prymasa Tysiaclecia Stefana Kardynala Wyszynskiego]
R. Baranowski,,
, Teodor Buchner (FP / PCSD)
Teodor Buchner,,
- Physics of Complex Systems Divison
Journal seriesChaos Solitons & Fractals, ISSN 0960-0779
Issue year2000
ASJC Classification2600 General Mathematics
Score (nominal)30
Score sourcejournalList
Publication indicators Scopus Citations = 30; WoS Citations = 24; Scopus SNIP (Source Normalised Impact per Paper): 2000 = 0.728; WoS Impact Factor: 2006 = 2.042 (2) - 2007=2.574 (5)
Citation count*33 (2015-04-09)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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