In general, Electrocardiogram (ECG) signal gets corrupted by variety of noise at the time of
its acquisition. Unfortunately, these noise tend to mask the crucial information …

Heart is responsible for circulation of the blood throughout the human body. The conduction
of the heart is nonlinear in nature and hence needs appropriate utilisation of technological …

These days signal processing has the great importance in extracting important pathological
attributes of the subject (patient). This paper covers important aspects of Electrocardiogram …

Background Accurate arrhythmia (atrial fibrillation (AF) and congestive heart failure (CHF))
detection is still a challenge in the biomedical signal‐processing field. Different linear and …

The cardiac rate variability analysis is a tool used to diagnose pathological and
physiological variations in subjects in the premature stages. The cross-sample entropy …

Traditional techniques to evaluate the complexity of biological signals forgo the numerous
time scales present in such data. When these algorithms were applied to real-world datasets …

In this paper, based upon the appearance of patterns derived from a time series, we have
investigated the suitability of multiscale entropy (MSE) technique for complexity …

This paper proposes a method that maps the coupling strength of an arbitrary number of
signals D, D≥ 2, into a single time series. It is motivated by the inability of multiscale entropy …

Muscle activation interval (MAI) is an important clinical indicator for muscular disorders
diagnosis. In this study, the S-transform technique was proposed to detect the muscle …

The goal of this paper is to investigate the changes of entropy estimates when the amplitude
distribution of the time series is equalized using the probability integral transformation. The …