TY - GEN
T1 - Novel feature for quantifying temporal variability of Poincaré plot
T2 - 36th Annual Conference of Computers in Cardiology, CinC 2009
AU - Karmakar, Chandan K.
AU - Khandoker, A. H.
AU - Gubbi, J.
AU - Palaniswami, M.
PY - 2009
Y1 - 2009
N2 - The Poincaré 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 Poincaré 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 Poincaré plots. To compare performance of CCM with standard Poincaré 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.
AB - The Poincaré 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 Poincaré 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 Poincaré plots. To compare performance of CCM with standard Poincaré 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.
UR - http://www.scopus.com/inward/record.url?scp=77952691216&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:77952691216
SN - 9781424472819
T3 - Computers in Cardiology
SP - 53
EP - 56
BT - Computers in Cardiology 2009, CinC 2009
Y2 - 13 September 2009 through 16 September 2009
ER -