Cardiovascular systems essentially have multiscale control mechanisms. Multiscale entropy
(MSE) analysis permits the dynamic characterization of the cardiovascular time series for …

Congestive heart failure (CHF) remains to be one of the major cardiovascular disorders in
the world. Due to the prevalence of CHF related issues, it is prudent to seek out new …

Approximate entropy (ApEn) is widely accepted as a complexity measure of the heart rate
variability (HRV) signal, but selecting the criteria for the threshold value r is controversial …

This study has aimed to develop a novel pre-diagnostic tool for primary care screening of
heart disease based on multivariate short-term heart rate variability (HRV) analyzed by …

The multiscale entropy (MSE), a technique, to analyse heart rate variability at different time-
scales, requires priori determination of pattern length (m) to be compared and tolerance …

Sample entropy (SampEn) is widely used for electrocardiogram (ECG) signal analysis to
quantify the inherent complexity or regularity of RR interval time series (ie, heart rate …

Cardiovascular control acts over multiple time scales, which introduces a significant amount
of complexity to heart rate and blood pressure time series. Multiscale entropy (MSE) analysis …

As a crucial method of the feature extraction, the complexity measurement has a wide range
of applications in the field of nonlinear time series research. This paper presents an …

In the present document the multiscale entropy (MSE) methodology has been applied to
analyze the complex behavior of the heart rate variability (HRV), in patients with aortic …

Aim Congestive heart failure (CHF) is a very complex clinical syndrome that may lead to
ischemic cerebral hypoxia condition. The aim of the present study is to analyze the effects of …