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.
Highlights
Empirical Mode Decomposition (EMD) are called Intrinsic Mode Functions (IMFs)
Datasets used in the analysis: To study the intrinsic mode functions of Heart Rate Variability (HRV) in different age and pathological condition, half an hour duration HRV signal from three different groups of subjects were considered for the analysis: consecutive IMFs ck-i and ck is calculated and this value is compared to a stopping condition
Where n is the number of IMFs, ck the kth IMF and rfinal is the final residue
Summary
EMD are called Intrinsic Mode Functions (IMFs). EMD is defined by an algorithm and has got no analyticalOver the last 20 years there has been widespread formulation. Heart rate is influenced by sympathetic and parasympathetic (vagal) activities of autonomous nervous system. The sympathetic activity accelerates the heart rate while the stationary signals. Job Lindsen and Bhattacharya (2010) used EMD and Independent component analysis method to correct the blink artifacts (Lindsen and Bhattacharya, 2010). Ortiz et al (2005) applied EMD method to parasympathetic activity decelerates the heart rate. The decompose the fetal HRV series into its components influence of both branches of the autonomous nervous system is known as sympathovagal balance reflected in the HRV, which is a non invasive measure of the autonomous nervous system balance (Buccelletti et al, in order to identify, the high frequency oscillations (Ortiz et al, 20005). Neto et al (2004) applied EMD to situations where postural changes occur, provoking instantaneous changes in heart rate as a result of The decompose the fetal HRV series into its components influence of both branches of the autonomous nervous system is known as sympathovagal balance reflected in the HRV, which is a non invasive measure of the autonomous nervous system balance (Buccelletti et al, in order to identify, the high frequency oscillations (Ortiz et al, 20005). Neto et al (2004) applied EMD to situations where postural changes occur, provoking instantaneous changes in heart rate as a result of
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