ABSTRACT
Ventricular fibrillation (VF) is one of the most serious malignant arrhythmias, usually resulting from immediate degeneration of ventricular tachycardia (VT). The surrogate data test (SDT) has been employed in the qualitative detection and analysis of cardiac chaos. Unfortunately, the current SDT method, based on the GP (Grassberger and Procaccia) algorithm, may not be suitable for the analysis of VF rhythm, which has been shown to be a high-dimensional signal. This paper proposes a novel qualitative analysis method based on symbolic dynamics for chaotic systems: the complexity dispersity method. Compared with the GP algorithm, our qualitative complexity method demonstrates better analytical accuracy and robustness and requires less data points (5 seconds vs 20 seconds). When used in the analysis of experimental data, our method achieved 100% accuracy in the detection of cardiac pathology for VT and VF.
Subject(s)
Nonlinear Dynamics , Tachycardia, Ventricular/pathology , Ventricular Fibrillation/pathology , Algorithms , Animals , Defibrillators, Implantable , Dogs , Models, StatisticalABSTRACT
Ventricular fibrillation (VF) is one of the most serious malignant arrhythmias usually resulting from immediate degeneration of ventricular tachycardia (VT). In order to analyse the nonlinear dynamics of the cardiac micro-mechanism under VT and VT rhythm, at the cellular level, myocardial cell action potentials are investigated under different rhythm, normal sinus rhythm, VT and VT. On the basis of nonlinear chaotic theory and symbolic dynamics, we put forward new definitions, complexity rate, etc, and obtained some useful properties for cellular electrophysiological analysis. The results of the experiments and computation show that the myocardial cellular signals under VT and VF rhythm are different kinds of chaotic signals in that the cardiac chaos attractor under VF is higher than that under VT. The analytical complexity theory has been promising in the clinical application.
