Automated heartbeat classification using 3-D inputs based on convolutional neural network with multi-fields of view
F Li, Y Xu, Z Chen, Z Liu - IEEE Access, 2019 - ieeexplore.ieee.org
A high-performance method of automated heartbeat classification based on Convolutional
Neural Network (CNN) is proposed in this paper. To make full use of the electrocardiogram …
Neural Network (CNN) is proposed in this paper. To make full use of the electrocardiogram …
Automated heartbeat classification exploiting convolutional neural network with channel-wise attention
F Li, J Wu, M Jia, Z Chen, Y Pu - IEEE Access, 2019 - ieeexplore.ieee.org
Long-term Electrocardiogram (ECG) analysis has become a common means of diagnosing
cardiovascular diseases. In order to reduce the workload of cardiologists and accelerate …
cardiovascular diseases. In order to reduce the workload of cardiologists and accelerate …
Arrhythmic heartbeat classification using 2d convolutional neural networks
Background Electrocardiogram (ECG) is a method of recording the electrical activity of the
heart and it provides a diagnostic means for heart-related diseases. Arrhythmia is any …
heart and it provides a diagnostic means for heart-related diseases. Arrhythmia is any …
Inter-patient ECG classification with symbolic representations and multi-perspective convolutional neural networks
This paper presents a novel deep learning framework for the inter-patient electrocardiogram
(ECG) heartbeat classification. A symbolization approach especially designed for ECG is …
(ECG) heartbeat classification. A symbolization approach especially designed for ECG is …
ECG-based heartbeat classification using two-level convolutional neural network and RR interval difference
Y Xiang, J Luo, T Zhu, S Wang, X Xiang… - … on Information and …, 2018 - search.ieice.org
Arrhythmia classification based on electrocardiogram (ECG) is crucial in automatic
cardiovascular disease diagnosis. The classification methods used in the current practice …
cardiovascular disease diagnosis. The classification methods used in the current practice …
Inter-patient ECG arrhythmia heartbeat classification network based on multiscale convolution and FCBA
F Zhou, Y Sun, Y Wang - Biomedical Signal Processing and Control, 2024 - Elsevier
Cardiac arrhythmias that can lead to sudden cardiac death are common. Electrocardiograms
(ECGs) offer valuable information about cardiac status and play a crucial role in evaluating …
(ECGs) offer valuable information about cardiac status and play a crucial role in evaluating …
[PDF][PDF] A hybrid method for heartbeat classification via convolutional neural networks, multilayer perceptrons and focal loss
Background Heart arrhythmia, as one of the most important cardiovascular diseases (CVDs),
has gained wide attention in the past two decades. The article proposes a hybrid method for …
has gained wide attention in the past two decades. The article proposes a hybrid method for …
Automated ECG classification using dual heartbeat coupling based on convolutional neural network
A high performance electrocardiogram (ECG)-based arrhythmic beats classification system
is presented in this paper. The classifier was designed based on convolutional neural …
is presented in this paper. The classifier was designed based on convolutional neural …
Feature enrichment based convolutional neural network for heartbeat classification from electrocardiogram
Correct heartbeat classification from electrocardiogram (ECG) signals is fundamental to the
diagnosis of arrhythmia. The recent advancement in deep convolutional neural network …
diagnosis of arrhythmia. The recent advancement in deep convolutional neural network …
Automated heartbeat classification based on deep neural network with multiple input layers
H Shi, C Qin, D Xiao, L Zhao, C Liu - Knowledge-Based Systems, 2020 - Elsevier
The arrhythmia is an important group of cardiovascular disease. Electrocardiogram (ECG) is
commonly used for detecting arrhythmias. Computer-aided diagnosis system can diagnose …
commonly used for detecting arrhythmias. Computer-aided diagnosis system can diagnose …