J. J. Żebrowski

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An easy to implement, consistent new measure of the complexity of heart rate variability has been developed. It is well suited for nonstationary data such as that of Holter ECG recordings and allows to assess the risk of cardiac arrest.
A dynamic analysis of the Correlation Integral (C m) of the Heart Rate Variability signal (HRV) was applied to 50 patients with Hypertrophic Cardiomyopathy (HCM). A group of 55 healthy subjects was considered as a control group. The Correlation Integral is calculated within a moving time window in order to characterize the nonlinear dynamical behavior of(More)
Heart mapping systems allow approximate reconstruction of the heart chamber geometry which is used as a base for the representation of the spatial distribution of electrophysiological parameters. Main limitation lies in the difficulty of the reconstruction of the geometry of more complicated areas of the heart. Here, we propose a new method of(More)
Aortic valve stenosis is the third commonest heart disease in developed countries. When the opening of the aortic valve is narrowed, the ability of the heart to pump blood is severely limited. This inhibits the ability of the circulation system to adapt to changing external requirements. This can drastically change state of the nonlinear system and(More)
The Poincare plots-a simple graphical, nonlinear method was implemented to express 24-h QT interval changes. The group of 23 pts with hypertrophic cardiomyopathy was analyzed (11 pts. with higher and 12 with lower risk of sudden cardiac death). The control group consisted of 10 healthy subjects. 24-h Holter ECG recordings were analyzed and RR and QT(More)
Here, we present new results obtained from a 1-D model of the atrium, with both the sinoatrial (SA) and atrioventricular (AV) nodes included. This model is able to reproduce forward and backward propagation between the SA and AV node. These nodes were approximated by a 1-D chain of diffusively coupled, modified relaxation oscillators. The atrial muscle was(More)
Autonomic Information Flow (AIF) reflects the time scale dependence of autonomic communications such as vagal, sympathetic, and slower rhythms and their complex interplay. We investigated the hypothesis that pathologically disturbed short term control is associated with simplified complex long term control. This particular characteristic of altered(More)
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