Computer-aided arrhythmia diagnosis with bio-signal processing: A survey of trends and techniques

SMP Dinakarrao, A Jantsch, M Shafique - ACM Computing Surveys …, 2019 - dl.acm.org
Signals obtained from a patient, ie, bio-signals, are utilized to analyze the health of patient.
One such bio-signal of paramount importance is the electrocardiogram (ECG), which …

Ventricular fibrillation and tachycardia classification using a machine learning approach

Q Li, C Rajagopalan, GD Clifford - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
Correct detection and classification of ventricular fibrillation (VF) and rapid ventricular
tachycardia (VT) is of pivotal importance for an automatic external defibrillator and patient …

Detecting ventricular tachycardia and fibrillation by complexity measure

XS Zhang, YS Zhu, NV Thakor… - IEEE Transactions on …, 1999 - ieeexplore.ieee.org
Sinus rhythm (SR), ventricular tachycardia (VT) and ventricular fibrillation (VF) belong to
different nonlinear physiological processes with different complexity. In this study, the …

Detection of shockable ventricular cardiac arrhythmias from ECG signals using FFREWT filter-bank and deep convolutional neural network

R Panda, S Jain, RK Tripathy, UR Acharya - Computers in Biology and …, 2020 - Elsevier
Among various life-threatening cardiac disorders, ventricular tachycardia (VT) and
ventricular fibrillation (VF) are shockable ventricular cardiac arrhythmias (SVCA) which …

Ventricular tachycardia and fibrillation detection by a sequential hypothesis testing algorithm

NV Thakor, YS Zhu, KY Pan - IEEE Transactions on Biomedical …, 1990 - ieeexplore.ieee.org
An algorithm for detecting ventricular fibrillation (VF) and ventricular tachycardia (VT) by the
method of sequential hypothesis testing is presented. The algorithm first generates a binary …

Reliability of old and new ventricular fibrillation detection algorithms for automated external defibrillators

A Amann, R Tratnig, K Unterkofler - Biomedical engineering online, 2005 - Springer
Background A pivotal component in automated external defibrillators (AEDs) is the detection
of ventricular fibrillation by means of appropriate detection algorithms. In scientific literature …

Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia

A Picon, U Irusta, A Álvarez-Gila, E Aramendi… - PloS one, 2019 - journals.plos.org
Early defibrillation by an automated external defibrillator (AED) is key for the survival of out-
of-hospital cardiac arrest (OHCA) patients. ECG feature extraction and machine learning …

ECG biometric analysis in cardiac irregularity conditions

F Agrafioti, D Hatzinakos - Signal, Image and Video Processing, 2009 - Springer
Biometric traits offer direct solutions to the critical security concerns involved in identity
authentication systems. In this paper, a systematic analysis of the electrocardiogram (ECG) …

Machine learning techniques for the detection of shockable rhythms in automated external defibrillators

C Figuera, U Irusta, E Morgado, E Aramendi, U Ayala… - PloS one, 2016 - journals.plos.org
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 …

Method and apparatus for separation of ventricular tachycardia from ventricular fibrillation for implantable cardioverter defibrillators

SA Caswell, JM Jenkins, LA DiCarlo - US Patent 5,857,977, 1999 - Google Patents
US5857977A - Method and apparatus for separation of ventricular tachycardia from
ventricular fibrillation for implantable cardioverter defibrillators - Google Patents …