Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review
Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …
tools in medicine and healthcare. Deep learning methods have achieved promising results …
Computer-aided diagnosis of atrial fibrillation based on ECG Signals: A review
Arrhythmia is a type of disorder that affects the pattern and rate of the heartbeat. Among the
various arrhythmia conditions, atrial fibrillation (AF) is the most prevalent. AF is associated …
various arrhythmia conditions, atrial fibrillation (AF) is the most prevalent. AF is associated …
AF classification from a short single lead ECG recording: The PhysioNet/computing in cardiology challenge 2017
The PhysioNet/Computing in Cardiology (CinC) Challenge 2017 focused on differentiating
AF from noise, normal or other rhythms in short term (from 9-61 s) ECG recordings …
AF from noise, normal or other rhythms in short term (from 9-61 s) ECG recordings …
Detecting atrial fibrillation by deep convolutional neural networks
Background Atrial fibrillation (AF) is the most common cardiac arrhythmia. The incidence of
AF increases with age, causing high risks of stroke and increased morbidity and mortality …
AF increases with age, causing high risks of stroke and increased morbidity and mortality …
Automated detection of atrial fibrillation using long short-term memory network with RR interval signals
Atrial Fibrillation (AF), either permanent or intermittent (paroxysnal AF), increases the risk of
cardioembolic stroke. Accurate diagnosis of AF is obligatory for initiation of effective …
cardioembolic stroke. Accurate diagnosis of AF is obligatory for initiation of effective …
DENS-ECG: A deep learning approach for ECG signal delineation
Objectives With the technological advancements in the field of tele-health monitoring, it is
now possible to gather huge amount of electro-physiological signals such as the …
now possible to gather huge amount of electro-physiological signals such as the …
Smart wearables for cardiac monitoring—real-world use beyond atrial fibrillation
The possibilities and implementation of wearable cardiac monitoring beyond atrial fibrillation
are increasing continuously. This review focuses on the real-world use and evolution of …
are increasing continuously. This review focuses on the real-world use and evolution of …
Fully screen-printed PI/PEG blends enabled patternable electrodes for scalable manufacturing of skin-conformal, stretchable, wearable electronics
Recent advances in soft materials and nano-microfabrication have enabled the
development of flexible wearable electronics. At the same time, printing technologies have …
development of flexible wearable electronics. At the same time, printing technologies have …
ECG signal classification for the detection of cardiac arrhythmias using a convolutional recurrent neural network
Objective: The electrocardiogram (ECG) provides an effective, non-invasive approach for
clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the …
clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the …
Automatic detection of atrial fibrillation using stationary wavelet transform and support vector machine
S Asgari, A Mehrnia, M Moussavi - Computers in biology and medicine, 2015 - Elsevier
Background Atrial fibrillation (AF) is the most common cardiac arrhythmia, and a major
public health burden associated with significant morbidity and mortality. Automatic detection …
public health burden associated with significant morbidity and mortality. Automatic detection …