Illuminating of Premature Ventricular Contractions of Heart using Fractal Dimension and Poincaré plot methods

Premature ventricular contractions (PVC) are premature heartbeats originating from the ventricles of the heart. These heart beats occur before the regular heartbeat. PVC in patients with heart diseases (heart attacks, heart failure, diseases of the heart valves) may be associated with increased risks of developing ventricular tachycardia. A technique of nonlinear analysis, the fractal analysis is most mathematical models produce intractable solutions. Fractal is a mathematical analysis for characterizing complex, repeating geometrical patterns at various scale lengths. Due to the self-similarity in the heart’s electrical conduction mechanism and self-affine behaviour of heart rate (HR), fractal analysis can be used to analyze HR time serie data. Some studies tried to apply the fractal dimension to quantify of cardiac abnormality like PVC. A total number of 14 sets of ECG record, 7 with normal rhythm, 7 of premature ventricular contraction (PVC). Based on FD change, we can identify and classify different abnormalities present in ECG. Presents the uses of Poincaré plot indexes of heart rate variability (HRV) from short term ECG recordings as a screening tool for PVC. A clear reduction of standard deviation (SD) projections in Poincaré plot patterns is observed in the healthy group with a significant difference of SD between healthy and PVC subjects. The results show that Poincaré plot patterns of HRV can be used in identifying PVC. Finally a comparison is shown for FD and Poincare plot parameters.