Deep learning-based ECG arrhythmia classification: A systematic review
Deep learning (DL) has been introduced in automatic heart-abnormality classification using
ECG signals, while its application in practical medical procedures is limited. A systematic …
ECG signals, while its application in practical medical procedures is limited. A systematic …
Heart rate variability for medical decision support systems: A review
Abstract Heart Rate Variability (HRV) is a good predictor of human health because the heart
rhythm is modulated by a wide range of physiological processes. This statement embodies …
rhythm is modulated by a wide range of physiological processes. This statement embodies …
A star-nose-like tactile-olfactory bionic sensing array for robust object recognition in non-visual environments
M Liu, Y Zhang, J Wang, N Qin, H Yang, K Sun… - Nature …, 2022 - nature.com
Object recognition is among the basic survival skills of human beings and other animals. To
date, artificial intelligence (AI) assisted high-performance object recognition is primarily …
date, artificial intelligence (AI) assisted high-performance object recognition is primarily …
[HTML][HTML] Information fusion and artificial intelligence for smart healthcare: a bibliometric study
With the fast progress in information technologies and artificial intelligence (AI), smart
healthcare has gained considerable momentum. By using advanced technologies like AI …
healthcare has gained considerable momentum. By using advanced technologies like AI …
Arrhythmia classification of LSTM autoencoder based on time series anomaly detection
P Liu, X Sun, Y Han, Z He, W Zhang, C Wu - Biomedical Signal Processing …, 2022 - Elsevier
Electrocardiogram (ECG) is widely used in the diagnosis of heart disease because of its
noninvasiveness and simplicity. The time series signals contained in the signal are usually …
noninvasiveness and simplicity. The time series signals contained in the signal are usually …
Electrocardiogram heartbeat classification based on a deep convolutional neural network and focal loss
TF Romdhane, MA Pr - Computers in Biology and Medicine, 2020 - Elsevier
The electrocardiogram (ECG) is an effective tool for cardiovascular disease diagnosis and
arrhythmia detection. Most methods proposed in the literature include the following steps: 1) …
arrhythmia detection. Most methods proposed in the literature include the following steps: 1) …
HARDC: A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN
Deep learning-based models have achieved significant success in detecting cardiac
arrhythmia by analyzing ECG signals to categorize patient heartbeats. To improve the …
arrhythmia by analyzing ECG signals to categorize patient heartbeats. To improve the …
A novel unsupervised domain adaptation framework based on graph convolutional network and multi-level feature alignment for inter-subject ECG classification
Electrocardiogram (ECG) is an effective non-invasive tool that can detect arrhythmias.
Recently, deep learning (DL) has been widely used in ECG classification algorithms …
Recently, deep learning (DL) has been widely used in ECG classification algorithms …
Heartbeats classification using hybrid time-frequency analysis and transfer learning based on ResNet
Y Zhang, J Li, S Wei, F Zhou, D Li - IEEE Journal of Biomedical …, 2021 - ieeexplore.ieee.org
The classification of heartbeats is an important method for cardiac arrhythmia analysis. This
study proposes a novel heartbeat classification method using hybrid time-frequency analysis …
study proposes a novel heartbeat classification method using hybrid time-frequency analysis …
New hybrid deep learning approach using BiGRU-BiLSTM and multilayered dilated CNN to detect arrhythmia
Deep learning methods have shown early progress in analyzing complicated ECG signals,
especially in heartbeat classification and arrhythmia detection. However, there is still a long …
especially in heartbeat classification and arrhythmia detection. However, there is still a long …