Stages-based ECG signal analysis from traditional signal processing to machine learning approaches: A survey
Electrocardiogram (ECG) gives essential information about different cardiac conditions of
the human heart. Its analysis has been the main objective among the research community to …
the human heart. Its analysis has been the main objective among the research community to …
A comprehensive survey on ECG signals as new biometric modality for human authentication: Recent advances and future challenges
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 …
Classification of myocardial infarction with multi-lead ECG signals and deep CNN
Myocardial infarction (MI), commonly known as heart attack, causes irreversible damage to
heart muscles and even leads to death. Rapid and accurate diagnosis of MI is critical to …
heart muscles and even leads to death. Rapid and accurate diagnosis of MI is critical to …
Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals
The electrocardiogram (ECG) is a useful diagnostic tool to diagnose various cardiovascular
diseases (CVDs) such as myocardial infarction (MI). The ECG records the heart's electrical …
diseases (CVDs) such as myocardial infarction (MI). The ECG records the heart's electrical …
Hybrid CNN-LSTM deep learning model and ensemble technique for automatic detection of myocardial infarction using big ECG data
Automatic and accurate prognosis of myocardial infarction (MI) using electrocardiogram
(ECG) signals is a challenging task for the diagnosis and treatment of heart diseases. MI is …
(ECG) signals is a challenging task for the diagnosis and treatment of heart diseases. MI is …
Comprehensive electrocardiographic diagnosis based on deep learning
Cardiovascular disease (CVD) is the leading cause of death worldwide, and coronary artery
disease (CAD) is a major contributor. Early-stage CAD can progress if undiagnosed and left …
disease (CAD) is a major contributor. Early-stage CAD can progress if undiagnosed and left …
Machine learning-based prediction of acute coronary syndrome using only the pre-hospital 12-lead electrocardiogram
Prompt identification of acute coronary syndrome is a challenge in clinical practice. The 12-
lead electrocardiogram (ECG) is readily available during initial patient evaluation, but …
lead electrocardiogram (ECG) is readily available during initial patient evaluation, but …
ML–ResNet: A novel network to detect and locate myocardial infarction using 12 leads ECG
C Han, L Shi - Computer methods and programs in biomedicine, 2020 - Elsevier
Background and objective Myocardial infarction (MI) is one of the most threatening
cardiovascular diseases for human beings, which can be diagnosed by electrocardiogram …
cardiovascular diseases for human beings, which can be diagnosed by electrocardiogram …
Automated detection of conduct disorder and attention deficit hyperactivity disorder using decomposition and nonlinear techniques with EEG signals
HT Tor, CP Ooi, NSJ Lim-Ashworth, JKE Wei… - Computer Methods and …, 2021 - Elsevier
Background and objectives Attention deficit hyperactivity disorder (ADHD) is often presented
with conduct disorder (CD). There is currently no objective laboratory test or diagnostic …
with conduct disorder (CD). There is currently no objective laboratory test or diagnostic …
Automated characterization and classification of coronary artery disease and myocardial infarction by decomposition of ECG signals: A comparative study
Cardiovascular diseases (CVDs) are the main cause of cardiac death worldwide. The
Coronary Artery Disease (CAD) is one of the leading causes of these CVD deaths. CAD …
Coronary Artery Disease (CAD) is one of the leading causes of these CVD deaths. CAD …