Analysis of the nonlinear dynamical characteristics of ventricular fibrillation

Ventricular fibrillation (VF), with apparent complexity and nonlinearity, is a fatal malignant arrhythmia. We preprocess VF signals to eliminate noises by the wavelet transform, and then analyze its nonlinear dynamical characteristics using fractals and chaos theories. The nonstationary and time-varing properties of VF are demonstrated and changes in short-term net-counting dimension with time course of evolution. On the basis of the reconstructed phase space, strange attractor of VF is manifested in 2 and 3 dimensional phase portraits, and its correlation dimension evolution exponent and Lyapunov exponent are calculated respectively and prove it a 6.27 dimensional chaotic dynamics. These supply a theoretical framework and improve insight into the management of VF rhythm