Chaos control applied to cardiac rhythms represented by ECG signals

Abstract

The control of irregular or chaotic heartbeats is a key issue in cardiology. In this regard, chaos control techniques represent a good alternative since they suggest treatments different from those traditionally used. This paper deals with the application of the extended time-delayed feedback control method to stabilize pathological chaotic heart rhythms. Electrocardiogram (ECG) signals are employed to represent the cardiovascular behavior. A mathematical model is employed to generate ECG signals using three modified Van der Pol oscillators connected with time delay couplings. This model provides results that qualitatively capture the general behavior of the heart. Controlled ECG signals show the ability of the strategy either to control or to suppress the chaotic heart dynamics generating less-critical behaviors.

Dynamical behavior analysis of the heart system by the bifurcation structures

“…The information that our brain sends to it allows it to know what the body needs. Once it has received this information, to adapt its frequency to meet the needs of the body, it initiates the electrical impulse which evolves with a frequency adapted to the needs of the body [ 7 , 8 ]. To model the heart system three main nodes among the six heart nodes are considered, namely the sinus node (SA node), the atrioventricular node (AV node) and the Purkinje fibres (PF node) [ 9 , 10 ].…”

Mathematical model with autoregressive process for electrocardiogram signals

“…Gois and Savi considered three modified Van der Pol oscillators connected by time delay coupling to describe heart rhythm behaviour [10]. The coupled Van der Pol oscillators was also used in studies about the control of irregular behaviour in pathological heart rhythms [11]. McSharry and collaborators [12] introduced a dynamical model to describe generating synthetic electrocardiogram signals.…”

On new chaotic and hyperchaotic systems: A literature survey

“…This variety involves the absolute necessity to know the system performances in order to know, which one will be used. Actually, certain applications are more critical than others such as the control of cardiac rhythm [16]. Thus, comes the idea to classify the recently chaotic and hyperchaotic systems according to their performances since certain system characteristics can restrict their exploitation in nontraditional applications.…”