By Topic

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Karmakar, C.K. ; Univ. of Melbourne, Melbourne, VIC, Australia ; Khandoker, A. ; Gubbi, J. ; Palaniswami, M.

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.

Published in:

Computers in Cardiology, 2009

Date of Conference:

13-16 Sept. 2009