Novel feature for quantifying temporal variability of Poincaré plot: A case study

The Poincare¿ plot of RR intervals is one of the most popular techniques used in heart rate variability (HRV) analysis. The standard descriptors SD1 and SD2 of Poincare¿ plot represents the distribution of signal by quantifying spatial (shape) information. The present study proposes a novel descriptor, Complex Correlation Measure (CCM), to quantify changes in temporal structure of points of Poincare¿ plots. To compare performance of CCM with standard Poincare¿ descriptor SD1 and SD2, we have calculated ROC area for each descriptor between Normal Sinus Rhythm (NSR) and Congestive Heart Failure (CHF) subjects. The RR intervals of 54 NSR subjects and 29 CHF subjects from Physionet NSR and CHF database are used. The p value obtained from chi-square analysis between two groups was found significant only for CCM (p=9.07E-14). The largest ROC area between two groups was for CCM (0.92) which indicate that CCM can be used as a significant feature for detecting pathology.