The wavelet transform has emerged over recent years as a powerful time–frequency
analysis and signal coding tool favoured for the interrogation of complex nonstationary …

Abstract Analysis of electrocardiogram (ECG) signal provides valuable information about the
heart conditions of the patient to the clinicians. The wavelet transform is an effective tool for …

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

This paper illustrates the use of combined neural network model to guide model selection for
classification of electrocardiogram (ECG) beats. The ECG signals were decomposed into …

In this paper, an electrocardiogram (ECG) beat classification system based on wavelet
transformation and probabilistic neural network (PNN) is proposed to discriminate six ECG …

This paper presents the experimental pilot study to investigate the effects of pulsed
electromagnetic field (PEMF) at extremely low frequency (ELF) in response to …

A novel method for detecting ventricular premature contraction (VPC) from the Holter system
is proposed using wavelet transform (WT) and fuzzy neural network (FNN). The basic ideal …

Among various life-threatening cardiac disorders, ventricular tachycardia (VT) and
ventricular fibrillation (VF) are shockable ventricular cardiac arrhythmias (SVCA) which …

Ventricular tachycardia (VT) and ventricular fibrillation (VF) are shockable ventricular cardiac
ailments. Detection of VT/VF is one of the important step in both automated external …

The surface electrocardiogram associated with ventricular fibrillation has been of interest to
researchers for some time. Over the last few decades, techniques have been developed to …