open access

Vol 24, No 2 (2017)
Original articles — Clinical cardiology
Published online: 2016-10-11
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Characteristics of chaotic processes in electrocardiographically identified ventricular arrhythmia

Andrzej Mysiak, Małgorzata Kobusiak-Prokopowicz, Konrad Kaaz, Kamila Jarczewska, Wojciech Glabisz
DOI: 10.5603/CJ.a2016.0088
·
Pubmed: 27734459
·
Cardiol J 2017;24(2):151-158.

open access

Vol 24, No 2 (2017)
Original articles — Clinical cardiology
Published online: 2016-10-11

Abstract

Background: The theory of chaos proves a deterministic mechanism of induction of multiple complex processes previously thought to be random in nature. This research explains how these complex processes develop. The aim of the study was to test the hypothesis of the chaotic nature of myocardial electrical events during ventricular tachycardia (VT) and ventricular fibrillation (VF).

Methods: Original hardware and software was developed for digitalization of on-line electrocardiography (ECG) data, with the functions of automatic and manual identification as well as categoriza­tion of specific ventricular arrhythmias. Patient ECGs were recorded by specially developed measuring equipment (M2TT). Available ECG sampling frequency was 20,000 Hz, and it was possible to analyze the signal retrospectively. Digital ECG of the sinus rhythm (SR) was analyzed with non-sustained VT, VT and VF. The signals were then subjected to mathematical analysis. Using wavelet analysis, signals carrying frequencies from various ranges were isolated from baseline and each of these isolated signals was subjected to Fourier transformation to check on differences in the Fourier power spectra of the analyzed VT and VF signals.

Results: Ventricular tachycardia identified based on ECG fulfills the criteria of a chaotic process, while no such properties were found for SR and VF. Information obtained by the ECG is used to record myo­cardial electrical signals, but they are not sufficient to differentiate between an advanced chaotic state and the process of linear expansion of electrical activation within the myocardium.

Conclusions: Electrophysiological study requires advanced methods to record the signal of myocardial electrical activity, as ECG is not sufficiently sensitive to identify the features of a chaotic process during VF. (Cardiol J 2017; 24, 2: 151–158)

Abstract

Background: The theory of chaos proves a deterministic mechanism of induction of multiple complex processes previously thought to be random in nature. This research explains how these complex processes develop. The aim of the study was to test the hypothesis of the chaotic nature of myocardial electrical events during ventricular tachycardia (VT) and ventricular fibrillation (VF).

Methods: Original hardware and software was developed for digitalization of on-line electrocardiography (ECG) data, with the functions of automatic and manual identification as well as categoriza­tion of specific ventricular arrhythmias. Patient ECGs were recorded by specially developed measuring equipment (M2TT). Available ECG sampling frequency was 20,000 Hz, and it was possible to analyze the signal retrospectively. Digital ECG of the sinus rhythm (SR) was analyzed with non-sustained VT, VT and VF. The signals were then subjected to mathematical analysis. Using wavelet analysis, signals carrying frequencies from various ranges were isolated from baseline and each of these isolated signals was subjected to Fourier transformation to check on differences in the Fourier power spectra of the analyzed VT and VF signals.

Results: Ventricular tachycardia identified based on ECG fulfills the criteria of a chaotic process, while no such properties were found for SR and VF. Information obtained by the ECG is used to record myo­cardial electrical signals, but they are not sufficient to differentiate between an advanced chaotic state and the process of linear expansion of electrical activation within the myocardium.

Conclusions: Electrophysiological study requires advanced methods to record the signal of myocardial electrical activity, as ECG is not sufficiently sensitive to identify the features of a chaotic process during VF. (Cardiol J 2017; 24, 2: 151–158)

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Keywords

theory of chaos, ventricular fibrillation, ventricular tachycardia, wavelet analysis, phase trajectories

About this article
Title

Characteristics of chaotic processes in electrocardiographically identified ventricular arrhythmia

Journal

Cardiology Journal

Issue

Vol 24, No 2 (2017)

Pages

151-158

Published online

2016-10-11

DOI

10.5603/CJ.a2016.0088

Pubmed

27734459

Bibliographic record

Cardiol J 2017;24(2):151-158.

Keywords

theory of chaos
ventricular fibrillation
ventricular tachycardia
wavelet analysis
phase trajectories

Authors

Andrzej Mysiak
Małgorzata Kobusiak-Prokopowicz
Konrad Kaaz
Kamila Jarczewska
Wojciech Glabisz

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