Journal of Computer Science

Heart Rate Variability Analysis in Different Age and Pathological Conditions

M.E.S. Chelladurai and N. Kumaravel

DOI : 10.3844/jcssp.2011.1515.1524

Journal of Computer Science

Volume 7, Issue 10

Pages 1515-1524

Abstract

Problem statement: Heart Rate Variability (HRV) has been used as a measure of mortality primarily with patients who had undergone cardiac surgery. The analysis of Heart Rate Variability (HRV) demands specific capabilities which are not provided either by parametric or nonparametric conventional estimation methods. The Empirical Mode Decomposition (EMD) adaptively estimates the Intrinsic Mode Functions (IMFs) of nonlinear nonstationary signals. Approach: The intrinsic mode functions estimated from the HRV signal were based on local characteristics of the signal. The principle objective was to analyze the HRV latencies of healthy subjects in different age and pathological conditions. The method was applied to HRV signal of 17 healthy young control subjects, 17 healthy old control subjects and 20 congestive heart failure patients for half hour duration. Results: The results showed that a healthy person’s HRV rapidly rises to its maximum response much earlier than the HRV of pathological subjects. The rising slope of the time scale’s plot discriminates the healthy controls and pathological subjects with 100% sensitivity and specificity. Conclusion: This fact makes the method a promising approach to be applied in clinical practice as a screening test for specific risk-groups.

Copyright

© 2011 M.E.S. Chelladurai and N. Kumaravel. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.