Medical practitioners need to understand the critical features of ECG beats to diagnose and
identify cardiovascular conditions accurately. This would be greatly facilitated by identifying …

The new advances in multiple types of devices and machine learning models provide
opportunities for practical automatic computer-aided diagnosis (CAD) systems for ECG …

Heart disease prevention is one of the most important tasks for healthcare problems since
more than 50 million people around the world are at the risk of cardiovascular disease …

In recent years, cardiac problems have been found proportional to technology development.
As the cardiac signal (Electrocardiogram) relates to the electrical activity of the heart of a …

Over the years, researchers have studied the evolution of Electrocardiogram (ECG) and the
complex classification of cardiovascular diseases. This review focuses on the evolution of …

This paper presents an active and incremental learning system called active broad learning
system (ABLS) for ECG arrhythmia classification to reduce the time-consumption of training …

This study aims to present an efficient model for autodetection of cardiac arrhythmia by the
diagnosis of self-affinity and identification of governing processes of a number of …

The detrended fluctuation analysis (DFA) and its variants are popular methods to analyze
the self-similarity of a signal. Two steps characterize them: firstly, the trend of the centered …

Speech emotional content estimation is still a challenge for building robust human–machine
interaction systems. Accuracy of emotion estimation depends upon the corpus used for …

In this paper, we proposed a new hybrid model to predict the number of ischemia
occurrences in heart patients based on their ECG records using fractal analysis, statistical …