Computer modeling of chaoticity degree of ventricular fibrillations in humans and dogs

Abstract

For analysis of fibrillation chaos, methods of mathematical modeling and the theory of determined chaos are currently used. Earlier we have proposed a mathematical model, which allows computer modeling of ventricular fibrillation in the conditions of different number of pacemakers (ectopic foci). The model estimates the number of ectopic foci on experimental records of heart electric activity in animals and humans. The aim of this work was to use this model for studying the interrelation between degrees of ventricular fibrillation chaoticity and quantity of ectopic foci in the myocardium of humans and dogs. Methods. Theoretical dependences of fibrillation oscillation chaoticity degree on pacemaker numbers were constructed using computer modeling. Results of computer experiments were compared with those of physiological experiments on dogs and clinical records of ECG fragments from patients with episodes of ventricular fibrillation. The degree of chaoticity of heart electric activity was estimated by entropy, correlation dimension of chaos and phase portraits of fibrillary oscillation amplitudes. Further, the method of least squares was used to solve the task of finding the best model characteristics for achieving optimum correspondence between results of computed and real physiological experiments. This allowed us to calculate the number of ectopic foci and their amplitude-frequency characteristics. The results showed that the degree of chaoticity of fibrillation oscillations depended on the number of active ectopic foci in the myocardium. Calculated values for the number of ectopic foci for dogs exceeded similar values for humans. While multifocal types of models of ventricular fibrillation (4—5 foci) were characteristic of dogs, bi- and three-focal models were characteristic of humans. Characteristics of the chaoticity degree of fibrillation oscillations for dogs were also higher than similar values for humans. Conclusion. The study results showed an interrelation between the number of independent myocardial sources of high-frequency rhythmic activity and the degree of chaoticity of fibrillation chaos.