Enhancing dynamic ECG heartbeat classification with lightweight transformer model
Arrhythmia is a common class of Cardiovascular disease which is the cause for over 31% of
all death over the world, according to WHOs' report. Automatic detection and classification of …
all death over the world, according to WHOs' report. Automatic detection and classification of …
A multi-view multi-scale neural network for multi-label ECG classification
The 12-lead electrocardiogram (ECG) is a common method used to diagnose
cardiovascular diseases. Recently, ECG classification using deep neural networks has been …
cardiovascular diseases. Recently, ECG classification using deep neural networks has been …
BeatClass: a sustainable ECG classification system in IoT-based eHealth
With the rapid development of the Internet of Things (IoT), it becomes convenient to use
mobile devices to remotely monitor the physiological signals (eg, Arrhythmia diseases) of …
mobile devices to remotely monitor the physiological signals (eg, Arrhythmia diseases) of …
A transformer model blended with CNN and denoising autoencoder for inter-patient ECG arrhythmia classification
Y Xia, Y Xiong, K Wang - Biomedical Signal Processing and Control, 2023 - Elsevier
Researchers have proposed numerous novel features and models under the intra-patient
paradigm. However, their performance suffers when considering the inter-patient paradigm …
paradigm. However, their performance suffers when considering the inter-patient paradigm …
CAB: classifying arrhythmias based on imbalanced sensor data
Intelligently detecting anomalies in health sensor data streams (eg, Electrocardiogram,
ECG) can improve the development of E-health industry. The physiological signals of …
ECG) can improve the development of E-health industry. The physiological signals of …
Automated inter-patient arrhythmia classification with dual attention neural network
Background and objectives Arrhythmia classification based on electrocardiograms (ECG)
can enhance clinical diagnostic efficiency. However, due to the significant differences in the …
can enhance clinical diagnostic efficiency. However, due to the significant differences in the …
DSCSSA: A classification framework for spatiotemporal features extraction of arrhythmia based on the Seq2Seq model with attention mechanism
X Peng, W Shu, C Pan, Z Ke, H Zhu… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
In the field of arrhythmia classification, classification accuracy has always been a research
hotspot. However, the noises of electrocardiogram (ECG) signals, the class imbalance of …
hotspot. However, the noises of electrocardiogram (ECG) signals, the class imbalance of …
Interpatient ECG arrhythmia detection by residual attention CNN
P Xu, H Liu, X Xie, S Zhou, M Shu… - … Methods in Medicine, 2022 - Wiley Online Library
The precise identification of arrhythmia is critical in electrocardiogram (ECG) research. Many
automatic classification methods have been suggested so far. However, efficient and …
automatic classification methods have been suggested so far. However, efficient and …
Automatic Classification of Cardiac Arrhythmias using Deep Learning Techniques: A Systematic Review
F Vásquez-Iturralde, M Flores-Calero… - IEEE …, 2024 - ieeexplore.ieee.org
Cardiac arrhythmias are one of the main causes of death worldwide; therefore, early
detection is essential to save the lives of patients who suffer from them and to reduce the …
detection is essential to save the lives of patients who suffer from them and to reduce the …
An analytical investigation of anomaly detection methods based on sequence to sequence model in satellite power subsystem
W Jin, S Zhang, B Sun, P Jin, Z Li - Sensors, 2022 - mdpi.com
The satellite power subsystem is responsible for all power supply in a satellite, and is an
important component of it. The system's performance has a direct impact on the operations …
important component of it. The system's performance has a direct impact on the operations …