Determinism and nonlinearity of the heart rhythm

Laura Cimponeriu, Anastassios Bezerianos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


The interaction between sympathetic and parasympathetic nerve activities at the level of sinus node play a dominant role in the magnitude and time course of heart rate fluctuations. The analysis of short-term heart rate variability provides measures of the response of the sinus node to autonomic neural control in different patho-physiological states of the cardiovascular system functioning. Diminished variability, as a result of an ANS control dysfunction is often attended by profound changes in dynamics that cannot be characterized by simple linear measures of the global variability. Our interest regards the predictability and nonlinearity of the heart rhythm and their relation with the state of neural control of the heart. In the present study, we analyze the nonlinear predictability of the RR interval time series in two different states of neural regulation: normal function and pharmacological blockade, by means of atropine and propanolol.

Original languageEnglish (US)
Title of host publicationMedical Data Analysis - 1st International Symposium, ISMDA 2000, Proceedings
EditorsRudiger W. Brause, Ernst Hanisch
PublisherSpringer Verlag
Number of pages9
ISBN (Print)3540410899, 9783540410898
StatePublished - 2000
Externally publishedYes
Event1st International Symposium on Medical Data Analysis, ISMDA 2000 - Frankfurt, Germany
Duration: Sep 29 2000Sep 30 2000

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other1st International Symposium on Medical Data Analysis, ISMDA 2000

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Determinism and nonlinearity of the heart rhythm'. Together they form a unique fingerprint.

Cite this