ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)


For citation:

Gurov J. V. Symbolic dynamics in application to cardiac rate study. Izvestiya VUZ. Applied Nonlinear Dynamics, 2010, vol. 18, iss. 4, pp. 54-66. DOI: 10.18500/0869-6632-2010-18-4-54-66

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
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Language: 
Russian
Article type: 
Article
UDC: 
51-76

Symbolic dynamics in application to cardiac rate study

Autors: 
Gurov Jurij Vladimirovich, Southern Federal University
Abstract: 

The analysis of heart rhythms using symbolic dynamics is perfomed. Time intervals corresponding to the predominance of sympathetic or parasym-pathetic tone of the nervous regulation are encoded. During encoding 25 symbols are used, what leads to a wide variety of words in the symbolic strings. The analysis of heart rhythms for patients of all ages, including healthy ones and patients with cardiovascular diseases are produced. These results give characteristic of age-related changes and different pathologies in cardiac rhythms. 

Reference: 
  1. Kurths J, Voss A, Witt A, Saparin P, Kleiner HJ, Wessel N. Quantitative analysis of heart rate variability. Chaos. 1995;5(1):88–94. DOI: 10.1063/1.166090.
  2. Voss A, Wessel N, Baier V, Osterziel KJ, Kurths J, Dietz R, Schirdewan A. Symbolic dynamics – a powerful tool in non-invasive biomedical signal processing. Report – Online symposium for electronics engineers; 2000.
  3. Yang AC, Hseu SS, Yien HW, Goldberger AL, Peng CK. Linguistic analysis of the human heartbeat using frequency and rank order statistics. Phys. Rev. Lett. 2003;90(10):108103. DOI: 10.1103/PhysRevLett.90.108103.
  4. Guzzetti S, Borroni E, Garbelli PE, Ceriani E, Della Bella P, Montano N, Cogliati C, Somers VK, Malliani A, Porta A. Symbolic dynamics of heart rate variability: a probe to investigate cardiac autonomic modulation. Circulation. 2005;112(4):465–470. DOI: 10.1161/CIRCULATIONAHA.104.518449.
  5. Maestri R, La Rovere MT, Porta A, Pinna GD. Sympathetic neurohormonal correlates of linear and symbolic dynamics heart rate variability indexes in chronic heart failure. Computers in Cardiology. Bologna, Italy. 2008;35:49–52. DOI: 10.1109/CIC.2008.4748974.
  6. Cysarz D, Lange S, Matthiessen PF, Leeuwen PV. Regular heartbeat dynamics are associated with cardiac health. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2007;292(1):368–372. DOI: 10.1152/ajpregu.00161.2006.
  7. Voss A, Schulz S, Schroeder R, Baumert M, Caminal P. Methods derived from nonlinear dynamics for analysing heart rate variability. Phil. Trans. R. Soc. A. 2009;367(1887):277–296. DOI: 10.1098/rsta.2008.0232.
  8. Databases are available at: http://physionet.org/
  9. Dabrowski A, Dabrowski B, Piotrowicz R. Daily ECG monitoring. Moscow: Medpraktika; 1998. 208 p. (in Russian).
  10. Berezny EA. Correlation rhythmography in the study and treatment of patients with atrial fibrillation. Cardiology. 1981;5:94–96 (in Russian).
  11. Kamen PW, Krum H, Tonkin AM. Poincare plot of heart rate variability allows  quantitative display of parasympathetic nervous activity in humans. Clin. Sci. (Lond). 1996;91(2):201–208. DOI: 10.1042/cs0910201.
  12. Huikuri HV, Makikallio TH, Peng CK, Goldberger AL, Hintze U, Muller M. Fractal correlation properties of R-R interval dynamics and mortality in patients with depressed left ventricular function after an acute myocardial infarction. Circulation. 2000;101:47–53. DOI: 10.1161/01.cir.101.1.47.
  13. Stratonovich RL. Information Theory. Moscow: Sov. Radio; 1975. (in Russian).
  14. Gubin GD. Circadian organization of biological processes in the phylogeny and ontogenesis of vertebrates. Chronobiology and chronomedicine. Moscow: Medicine. 1989:70–82 (in Russian).
Received: 
19.04.2010
Accepted: 
16.06.2010
Published: 
29.10.2010
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