[HTML][HTML] Analysis of various techniques for ECG signal in healthcare, past, present, and future
Cardiovascular diseases are the primary reason for mortality worldwide. As per WHO survey
report in 2019, 17.9 million people died due to CVDs, accounting for 32% of all global …
report in 2019, 17.9 million people died due to CVDs, accounting for 32% of all global …
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 …
Automated atrial fibrillation detection using a hybrid CNN-LSTM network on imbalanced ECG datasets
Atrial fibrillation is a heart arrhythmia strongly associated with other heart-related
complications that can increase the risk of strokes and heart failure. Manual …
complications that can increase the risk of strokes and heart failure. Manual …
Accurate detection of atrial fibrillation from 12-lead ECG using deep neural network
W Cai, Y Chen, J Guo, B Han, Y Shi, L Ji… - Computers in biology …, 2020 - Elsevier
Atrial fibrillation (AF) is the most common heart arrhythmia, and 12-lead electrocardiogram
(ECG) is regarded as the gold standard for AF diagnosis. Highly accurate diagnosis of AF …
(ECG) is regarded as the gold standard for AF diagnosis. Highly accurate diagnosis of AF …
Atrial fibrillation classification and detection from ECG recordings
Objective Atrial fibrillation (AF) heart rhythm disorder is investigated under two topics:
Persistent AF (PeAF) and Paroxysmal AF (PAF). Diagnosis and detection of PeAF is …
Persistent AF (PeAF) and Paroxysmal AF (PAF). Diagnosis and detection of PeAF is …
An automated detection of atrial fibrillation from single‑lead ECG using HRV features and machine learning
Background Atrial fibrillation (AF) is a disorder of the heart rhythm where irregular and rapid
heartbeats are observed. This supraventricular arrhythmia may increase the risk of blood …
heartbeats are observed. This supraventricular arrhythmia may increase the risk of blood …
Novel density poincaré plot based machine learning method to detect atrial fibrillation from premature atrial/ventricular contractions
Objective: Detection of Atrial fibrillation (AF) from premature atrial contraction (PAC) and
premature ventricular contraction (PVC) is difficult as frequent occurrences of these ectopic …
premature ventricular contraction (PVC) is difficult as frequent occurrences of these ectopic …
Atrial fibrillation detection using heart rate variability and atrial activity: A hybrid approach
G Hirsch, SH Jensen, ES Poulsen… - Expert Systems with …, 2021 - Elsevier
Goal: Develop a real-time hybrid scheme for the automatic detection of atrial fibrillation (AF),
based on the RR interval (RRI) time series and the atrial activity (AA) derived from the …
based on the RR interval (RRI) time series and the atrial activity (AA) derived from the …
[HTML][HTML] Detection of atrial fibrillation episodes in long-term heart rhythm signals using a support vector machine
Atrial fibrillation (AF) is a serious heart arrhythmia leading to a significant increase of the risk
for occurrence of ischemic stroke. Clinically, the AF episode is recognized in an …
for occurrence of ischemic stroke. Clinically, the AF episode is recognized in an …
Non-standardized patch-based ECG lead together with deep learning based algorithm for automatic screening of atrial fibrillation
D Lai, Y Bu, Y Su, X Zhang… - IEEE journal of biomedical …, 2020 - ieeexplore.ieee.org
This study was to assess the feasibility of using non-standardized single-lead
electrocardiogram (ECG) monitoring to automatically detect atrial fibrillation (AF) with special …
electrocardiogram (ECG) monitoring to automatically detect atrial fibrillation (AF) with special …