Literature DB >> 7551312

Nonlinear analysis of epicardial atrial electrograms of electrically induced atrial fibrillation in man.

B P Hoekstra1, C G Diks, M A Allessie, J DeGoede.   

Abstract

INTRODUCTION: We applied methods from the theory of nonlinear dynamics to characterize unipolar epicardial right atrial electrograms of electrically induced atrial fibrillation (AF) in man. METHODS AND
RESULTS: Electrograms were selected from a high-density mapping study, which confirmed the existence of at least 3 different types of induced AF (types I, II, and III) in patients undergoing open chest surgery. We analyzed sets of 5 electrograms (4 sec, sampling frequency 1 kHz, resolution 8 bits) in 9 patients (AF type I, n = 3; type II, n = 3; type III, n = 3). The Grassberger-Procaccia method was applied to estimate the correlation dimension and correlation entropy from the electrograms. In 2 patients (AF type I) some electrograms (2 of 5 and 3 of 5, respectively) showed scaling at normalized distances ranging from 0.2 to 0.5 in phase space. Correlation dimension D ranged from 1.8 to 3.2 and correlation entropy K from 2.2 to 3.8 nats/sec. The patients were ranked according to increasing coarse-grained correlation dimension Dcg (range 3.7 to 7.9) and coarse-grained correlation entropy Kcg (range 5.6 to 18.6 nats/sec). The method of surrogate data was applied to detect nonlinearity in the electrograms. Using the correlation integral as test statistic, it could be excluded that electrograms of type I AF have been generated by linear stochastic dynamics. Episodes of sinus rhythm (D ranging from 1.0 to 5.1 and K from 2.0 to 8.6 nats/sec) and induced atrial flutter (D ranging from 2.7 to 4.2 and K from 2.2 to 4.2 nats/sec) in 2 different patients showed features of low-dimensional chaos.
CONCLUSION: Nonlinear analysis discriminated between electrograms during electrically induced AF in humans. The results are consistent with a classification of AF into 3 types based on the spatiotemporal complexity of right atrial activation patterns.

Entities:  

Mesh:

Year:  1995        PMID: 7551312     DOI: 10.1111/j.1540-8167.1995.tb00416.x

Source DB:  PubMed          Journal:  J Cardiovasc Electrophysiol        ISSN: 1045-3873


  12 in total

1.  Electrophysiological heterogeneity of atrial fibrillation and local effect of propafenone in the human right atrium: analysis based on symbolic dynamics.

Authors:  A Berkowitsch; J Carlsson; A Erdogan; J Neuzner; H F Pitschner
Journal:  J Interv Card Electrophysiol       Date:  2000-06       Impact factor: 1.900

2.  Nonlinear dynamics of two-dimensional cardiac action potential duration mapping model with memory.

Authors:  M Kesmia; S Boughaba; S Jacquir
Journal:  J Math Biol       Date:  2019-01-01       Impact factor: 2.259

3.  Linear and non-linear analysis of the surface electrocardiogram during human ventricular fibrillation shows evidence of order in the underlying mechanism.

Authors:  R H Clayton; A Murray
Journal:  Med Biol Eng Comput       Date:  1999-05       Impact factor: 2.602

4.  Measure of synchronisation of right atrial depolarisation wavefronts during atrial fibrillation.

Authors:  V Barbaro; P Bartolini; G Calcagnini; F Censi; A Michelucci
Journal:  Med Biol Eng Comput       Date:  2002-01       Impact factor: 2.602

5.  Non-invasive atrial fibrillation organization follow-up under successive attempts of electrical cardioversion.

Authors:  Raúl Alcaraz; José Joaquín Rieta; Fernando Hornero
Journal:  Med Biol Eng Comput       Date:  2009-12       Impact factor: 2.602

6.  Is human atrial fibrillation stochastic or deterministic?-Insights from missing ordinal patterns and causal entropy-complexity plane analysis.

Authors:  Konstantinos N Aronis; Ronald D Berger; Hugh Calkins; Jonathan Chrispin; Joseph E Marine; David D Spragg; Susumu Tao; Harikrishna Tandri; Hiroshi Ashikaga
Journal:  Chaos       Date:  2018-06       Impact factor: 3.642

7.  Linear and non-linear analysis of atrial signals and local activation period series during atrial-fibrillation episodes.

Authors:  L T Mainardi; A Porta; G Calcagnini; P Bartolini; A Michelucci; S Cerutti
Journal:  Med Biol Eng Comput       Date:  2001-03       Impact factor: 3.079

8.  Assessment of the dynamics of atrial signals and local atrial period series during atrial fibrillation: effects of isoproterenol administration.

Authors:  Luca T Mainardi; Valentina D A Corino; Leonida Lombardi; Claudio Tondo; Massimo Mantica; Federico Lombardi; Sergio Cerutti
Journal:  Biomed Eng Online       Date:  2004-10-22       Impact factor: 2.819

9.  Computation of nonlinear parameters of heart rhythm using short time ECG segments.

Authors:  Berik Koichubekov; Ilya Korshukov; Nazgul Omarbekova; Viktor Riklefs; Marina Sorokina; Xenia Mkhitaryan
Journal:  Comput Math Methods Med       Date:  2015-01-22       Impact factor: 2.238

10.  Dynamic approximate entropy electroanatomic maps detect rotors in a simulated atrial fibrillation model.

Authors:  Juan P Ugarte; Andrés Orozco-Duque; Catalina Tobón; Vaclav Kremen; Daniel Novak; Javier Saiz; Tobias Oesterlein; Clauss Schmitt; Armin Luik; John Bustamante
Journal:  PLoS One       Date:  2014-12-09       Impact factor: 3.240

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