Characteristics of chaotic processes in electrocardiographically identified ventricular arrhythmia

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).

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 categoriza-tion 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.

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 myo-cardial 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.

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).