Title :
Poincare mapping for detecting abnormal dynamics of cardiac repolarization
Author :
Strumillo, Pawel ; Ruta, Jan
Author_Institution :
Inst. of Electron., Tech. Univ. Lodz, Poland
Abstract :
This article concentrates on analysis of subtle ECG signal features associated with characteristic temporal variations in the repolarization phase of cardiac electrical activation (i.e., variations that are embedded within the T-wave). These variations are termed T-wave alternans (TWA) to connote larger similarity between T-wave shapes in every other beat than that in the adjacent beats that occur during regular heart rhythm of an increased rate. In an early work the concept of associating TWA with period-doubling bifurcation of the cardiac oscillator has been put forward and demonstrated on canine ECG traces. In this article we extend this idea and use it for quantification of TWA in human ECGs recorded from postinfarction patients. The purpose of this work is to show that: a statistically significant correlation exists for the analyzed ECGs between the TWA level computed by means of an inter-cycle synchronized sampling technique known as Poincare mapping (PM) and a widely used Fourier spectrum (FS) method, and that the PM method outperforms the widely used FS method for TWA analysis in a number of ways.
Keywords :
Poincare mapping; bifurcation; electrocardiography; medical signal processing; nonlinear dynamical systems; signal sampling; spectral analysis; time series; ECG signal features; Fourier spectrum method; Poincare mapping; T-wave alternans; T-wave power spectra; abnormal cardiac repolarization dynamics; cardiac electrical activation; period-doubling bifurcation; scatter-graph; statistically significant correlation; temporal variations; time series; Bifurcation; Cardiology; Electrocardiography; Frequency synchronization; Humans; Inspection; Myocardium; Oscillators; Sampling methods; Scattering; Arrhythmias, Cardiac; Body Surface Potential Mapping; Cluster Analysis; Fourier Analysis; Humans; Models, Cardiovascular; Models, Statistical; Myocardial Infarction; Periodicity; Statistics as Topic;
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE