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 …
A novel deep-learning-based framework for the classification of cardiac arrhythmia
Cardiovascular diseases (CVDs) are the primary cause of death. Every year, many people
die due to heart attacks. The electrocardiogram (ECG) signal plays a vital role in diagnosing …
die due to heart attacks. The electrocardiogram (ECG) signal plays a vital role in diagnosing …
Res-BiANet: A Hybrid Deep Learning Model for Arrhythmia Detection Based on PPG Signal
Y Wu, Q Tang, W Zhan, S Li, Z Chen - Electronics, 2024 - mdpi.com
Arrhythmias are among the most prevalent cardiac conditions and frequently serve as a
direct cause of sudden cardiac death. Hence, the automated detection of arrhythmias holds …
direct cause of sudden cardiac death. Hence, the automated detection of arrhythmias holds …
ECG classification for detecting ECG arrhythmia empowered with deep learning approaches
According to the World Health Organization (WHO) report, heart disease is spreading
throughout the world very rapidly and the situation is becoming alarming in people aged 40 …
throughout the world very rapidly and the situation is becoming alarming in people aged 40 …
A hybrid deep CNN model for abnormal arrhythmia detection based on cardiac ECG signal
Electrocardiogram (ECG) signals play a vital role in diagnosing and monitoring patients
suffering from various cardiovascular diseases (CVDs). This research aims to develop a …
suffering from various cardiovascular diseases (CVDs). This research aims to develop a …
Arrhythmia recognition and classification through deep learning-based approach
R Zhou, X Li, B Yong, Z Shen, C Wang… - International …, 2019 - inderscienceonline.com
Arrhythmia is a cardiac condition caused by abnormal electrical activity of the heart, which
can be life-threatening. Electrocardiogram (ECG) is the principal diagnostic tool used to …
can be life-threatening. Electrocardiogram (ECG) is the principal diagnostic tool used to …
A novel wearable electrocardiogram classification system using convolutional neural networks and active learning
Arrhythmias reflect electrical abnormalities of the heart, and they can lead to severe harm to
the heart. An electrocardiogram (ECG) is a useful tool to manifest arrhythmias. In this paper …
the heart. An electrocardiogram (ECG) is a useful tool to manifest arrhythmias. In this paper …
Cardiac arrhythmia classification by multi-layer perceptron and convolution neural networks
S Savalia, V Emamian - Bioengineering, 2018 - mdpi.com
The electrocardiogram (ECG) plays an imperative role in the medical field, as it records
heart signal over time and is used to discover numerous cardiovascular diseases. If a …
heart signal over time and is used to discover numerous cardiovascular diseases. If a …
A novel deep convolutional neural network for arrhythmia classification
H Dang, M Sun, G Zhang, X Zhou… - 2019 International …, 2019 - ieeexplore.ieee.org
The electrocardiogram (ECG) is a key standard for monitoring the activity regularity of heart.
Many cardiac abnormalities will be demonstrated from ECG including arrhythmia, which may …
Many cardiac abnormalities will be demonstrated from ECG including arrhythmia, which may …
A new transfer learning approach to detect cardiac arrhythmia from ECG signals
Deep Learning (DL) has turned into a subject of study in different applications, including
medical field. Finding the irregularities in Electrocardiogram (ECG) is a critical part in …
medical field. Finding the irregularities in Electrocardiogram (ECG) is a critical part in …