BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia that increases the risk
of thromboembolic events. Anticoagulation therapy to prevent AF-related stroke has been …

Over the past few decades, methods for classification and detection of rhythm or morphology
abnormalities in ECG signals have been widely studied. However, it lacks the …

Atrial fibrillation (AF) is an arrhythmia that can lead to several patient risks. This kind of
arrhythmia affects mostly elderly people, in particular those who suffer from heart failure (one …

Background: Atrial fibrillation (AFIB) is one of the most common types of arrhythmia, which
leads to heart failure and stroke to public. As AFIB has the high potential to cause permanent …

Electrocardiogram (ECG) signal is one of the most reliable methods to analyse the
cardiovascular system. In the literature, there are different deep learning architectures …

We present in this paper an algorithm of filtering the noisy real ECG signal. The classical
wavelet denoising process, based on the Donoho et al. algorithm, at the 4 th level, appears …

Atrial fibrillation (AF) is the most common cardiovascular disease (CVD), and most existing
algorithms are usually designed for the diagnosis (ie, feature classification) or prediction of …

Atrial flutter (AFL) and atrial fibrillation (AF) generate patterns in the electrocardiogram,
which have some similarity to a normal P-wave. Therefore their detection is an important …

Electrocardiogram (ECG) signal has been widely used for heart diagnoses, but it always
mixed with various noises. In this paper, we present a denoising algorithm that can be used …

ECG contains very important clinical information about the cardiac activities of the heart.
Often the ECG signal needs to be captured for a long period of time in order to identify …