Automated detection of shockable ECG signals: A review
Sudden cardiac death from lethal arrhythmia is a preventable cause of death. Ventricular
fibrillation and tachycardia are shockable electrocardiographic (ECG) rhythms that can …
fibrillation and tachycardia are shockable electrocardiographic (ECG) rhythms that can …
Detection of life-threatening arrhythmias using feature selection and support vector machines
F Alonso-Atienza, E Morgado… - IEEE Transactions …, 2013 - ieeexplore.ieee.org
Early detection of ventricular fibrillation (VF) and rapid ventricular tachycardia (VT) is crucial
for the success of the defibrillation therapy. A wide variety of detection algorithms have been …
for the success of the defibrillation therapy. A wide variety of detection algorithms have been …
A review of progress and an advanced method for shock advice algorithms in automated external defibrillators
Shock advice algorithm plays a vital role in the detection of sudden cardiac arrests on
electrocardiogram signals and hence, brings about survival improvement by delivering …
electrocardiogram signals and hence, brings about survival improvement by delivering …
ECG-based classification of resuscitation cardiac rhythms for retrospective data analysis
Objective: There is a need to monitor the heart rhythm in resuscitation to improve treatment
quality. Resuscitation rhythms are categorized into: ventricular tachycardia (VT), ventricular …
quality. Resuscitation rhythms are categorized into: ventricular tachycardia (VT), ventricular …
Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia
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 …
of-hospital cardiac arrest (OHCA) patients. ECG feature extraction and machine learning …
Machine learning techniques for the detection of shockable rhythms in automated external defibrillators
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 …
of out-of-hospital cardiac arrest (OHCA) patients treated with automated external …
Intelligent and efficient detection of life-threatening ventricular arrhythmias in short segments of surface ECG signals
D Lai, X Fan, Y Zhang, W Chen - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
Ventricular fibrillation (VF) and rapid ventricular tachycardia (VT) of a heart rate over 180
beats min-1, commonly known as shockable rhythms (ShR), are life-threatening ventricular …
beats min-1, commonly known as shockable rhythms (ShR), are life-threatening ventricular …
Life-threatening ventricular arrhythmia detection with personalized features
P Cheng, X Dong - IEEE access, 2017 - ieeexplore.ieee.org
The timely detection of life-threatening ventricular arrhythmias (VAs) is critical for saving a
patient's life. General features that characterize ECG waveforms are extracted for VA …
patient's life. General features that characterize ECG waveforms are extracted for VA …
Detection of ventricular tachycardia and fibrillation using adaptive variational mode decomposition and boosted-CART classifier
Rapid ventricular tachycardia (VT) and ventricular fibrillation (VF) are serious life-threatening
ventricular arrhythmias. Correct detection of VT/VF is crucial for the rescue of cardiac arrest …
ventricular arrhythmias. Correct detection of VT/VF is crucial for the rescue of cardiac arrest …
Weighted random forests to improve arrhythmia classification
K Gajowniczek, I Grzegorczyk, T Ząbkowski, C Bajaj - Electronics, 2020 - mdpi.com
Construction of an ensemble model is a process of combining many diverse base predictive
learners. It arises questions of how to weight each model and how to tune the parameters of …
learners. It arises questions of how to weight each model and how to tune the parameters of …