Engineering Commons^™

Multifractal Analysis Of Heart Rate Variability Using Wavelet-Transform Modulus-Maxima Method, Chirag Jani

Theses

Physiological signals are complex and carry information of human health. Recent studies reveal that under normal conditions, the heart rate time series shows multifractal behavior. In contrast, HRV in the pathological state such as congestive heart failure exhibits more monofractal-like structure. Recent advances in the assessment of heart rate variability (HRV) uses a nonlinear dynamics approach. In this study, the main objective is to use the wavelet-transform modulus-maxima method for the multifractal analysis of the heart rate time senes.

The degree of the multifractality is defined by the singularities (a point in time series where a mathematical function is not …

Quantification Of Regularity In Rr-Interval Time Series Using Approximate Entropy, Sample Entropy, And Multi-Scale Entropy, Nirvish Shah

Theses

Heart rate variability (HRV) has proven to be a useful noninvasive tool to study the neuronal control of the heart. Recently, nonlinear dynamic methods based on chaos theory and fractal dynamics have been developed to uncover the nonlinear fluctuations in heart rate. Approximate Entropy (ApEn), Sample Entropy (SampEn) and Multi-scale Entropy (MSE) are measures based on chaos theory that quantify the regularity in time series. This study has been designed to examine the ability of these measures to distinguish the RR-interval time series of normal subjects (NSR) from subjects with congestive heart failure (CHF). The study was conducted on the …