A survey on ECG analysis
The electrocardiogram (ECG) signal basically corresponds to the electrical activity of the
heart. In the literature, the ECG signal has been analyzed and utilized for various purposes …
heart. In the literature, the ECG signal has been analyzed and utilized for various purposes …
Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances
Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the
cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first …
cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first …
Arrhythmia detection using deep convolutional neural network with long duration ECG signals
This article presents a new deep learning approach for cardiac arrhythmia (17 classes)
detection based on long-duration electrocardiography (ECG) signal analysis …
detection based on long-duration electrocardiography (ECG) signal analysis …
Novel methodology of cardiac health recognition based on ECG signals and evolutionary-neural system
P Pławiak - Expert Systems with Applications, 2018 - Elsevier
This article presents an innovative research methodology that enables the efficient
classification of cardiac disorders (17 classes) based on ECG signal analysis and an …
classification of cardiac disorders (17 classes) based on ECG signal analysis and an …
An intelligent learning approach for improving ECG signal classification and arrhythmia analysis
AK Sangaiah, M Arumugam, GB Bian - Artificial intelligence in medicine, 2020 - Elsevier
The recognition of cardiac arrhythmia in minimal time is important to prevent sudden and
untimely deaths. The proposed work includes a complete framework for analyzing the …
untimely deaths. The proposed work includes a complete framework for analyzing the …
Deep learning-based stacked denoising and autoencoder for ECG heartbeat classification
S Nurmaini, A Darmawahyuni, AN Sakti Mukti… - Electronics, 2020 - mdpi.com
The electrocardiogram (ECG) is a widely used, noninvasive test for analyzing arrhythmia.
However, the ECG signal is prone to contamination by different kinds of noise. Such noise …
However, the ECG signal is prone to contamination by different kinds of noise. Such noise …
Accurate deep neural network model to detect cardiac arrhythmia on more than 10,000 individual subject ECG records
Background and objective Cardiac arrhythmia, which is an abnormal heart rhythm, is a
common clinical problem in cardiology. Detection of arrhythmia on an extended duration …
common clinical problem in cardiology. Detection of arrhythmia on an extended duration …
A novel attentional deep neural network-based assessment method for ECG quality
ECG quality assessment is of great significance to reduce false alarms in automatic
arrhythmia and other cardiovascular diseases diagnoses and reduce the workload of …
arrhythmia and other cardiovascular diseases diagnoses and reduce the workload of …
A comprehensive survey on ECG signals as new biometric modality for human authentication: Recent advances and future challenges
AN Uwaechia, DA Ramli - IEEE Access, 2021 - ieeexplore.ieee.org
Electrocardiogram (ECG) has extremely discriminative characteristics in the biometric field
and has recently received significant interest as a promising biometric trait. However, ECG …
and has recently received significant interest as a promising biometric trait. However, ECG …
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 …