Correct detection and classification of ventricular fibrillation (VF) and rapid ventricular
tachycardia (VT) is of pivotal importance for an automatic external defibrillator and patient …

Robustness of estimating cardiorespiratory parameters from photoplethysmography (PPG)
signal is highly dependent on the quality of the signal, which is heavily affected by motion …

Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival
of out-of-hospital cardiac arrest (OHCA) patients treated with automated external …

Clinically significant oversensing during tachycardia is rare when the ratio of the amplitude
of atrial electrogram to that of the ventricular electrogram is≥ 4: 1. 14 Oversensing becomes …

The occurrence of sudden cardiac arrest (SCA) leads to a massive death across the world.
Hence the early prediction of ventricular tachycardia (VT) and ventricular fibrillation (VF) …

Deep neural networks (DNN) are state-of-the-art machine learning algorithms that can be
learned to self-extract significant features of the electrocardiogram (ECG) and can generally …

Ventricular Arrhythmia (VA) such as Ventricular Tachycardia (VT) and Ventricular Fibrillation
(VF) are the common type of arrhythmia in infants and children. Electrocardiogram (ECG) …

An electrocardiogram (ECG) is an essential medical tool for analyzing the functioning of the
heart. An arrhythmia is a deviation in the shape of the ECG signal from the normal sinus …

The aim of the present work was to study the possibility of a parameter set to assure both
reliable detection of shockable rhythms and adequate shock success prediction. A set of 10 …

Sudden cardiac arrests are mainly caused by ventricular fibrillation and ventricular
tachycardia, which are known as shockable (SH) rhythms and properly curable by electronic …