Electrocardiogram (ECG) signal quality assessment (SQA) plays a vital role in significantly
improving the diagnostic accuracy and reliability of unsupervised ECG analysis systems. In …

Clinical data management systems typically provide caregiver teams with useful information,
derived from large, sometimes highly heterogeneous, data sources that are often changing …

Cardiac arrhythmia is associated with abnormal electrical activities of the heart, which can
be reflected by altered characteristics of electrocardiogram (ECG). Due to the simplicity and …

This article presents an innovative research methodology that enables the efficient
classification of cardiac disorders (17 classes) based on ECG signal analysis and an …

Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the
cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first …

Cardiovascular diseases (CVDs), including asymptomatic myocardial ischemia, angina,
myocardial infarction, and ischemic heart failure, are the leading cause of death globally …

Our human heart is classified into four sections called the left side and right side of the
atrium and ventricle accordingly. Monitoring and taking care of the heart of every human is …

Electrocardiogram (ECG) classification is an important process in identifying arrhythmia, and
neural network models have been widely used in this field. However, these models are often …

Long-term electrocardiogram (ECG) has become one of the important diagnostic assist
methods in clinical cardiovascular domain. Long-term ECG is primarily used for the …

Objective: Automatic detection and classification of noises can play a vital role in the
development of robust unsupervised electrocardiogram (ECG) analysis systems. This paper …