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Arrhythmia detection and classification using ECG and PPG techniques: A review
Electrocardiogram (ECG) and photoplethysmograph (PPG) are non-invasive techniques that
provide electrical and hemodynamic information of the heart, respectively. This information …
provide electrical and hemodynamic information of the heart, respectively. This information …
An ensemble of deep learning-based multi-model for ECG heartbeats arrhythmia classification
An automatic system for heart arrhythmia classification can perform a substantial role in
managing and treating cardiovascular diseases. In this paper, a deep learning-based multi …
managing and treating cardiovascular diseases. In this paper, a deep learning-based multi …
[HTML][HTML] ECG-based heartbeat classification for arrhythmia detection: A survey
An electrocardiogram (ECG) measures the electric activity of the heart and has been widely
used for detecting heart diseases due to its simplicity and non-invasive nature. By analyzing …
used for detecting heart diseases due to its simplicity and non-invasive nature. By analyzing …
ECG classification using wavelet packet entropy and random forests
T Li, M Zhou - Entropy, 2016 - mdpi.com
The electrocardiogram (ECG) is one of the most important techniques for heart disease
diagnosis. Many traditional methodologies of feature extraction and classification have been …
diagnosis. Many traditional methodologies of feature extraction and classification have been …
Ensemble deep learning approach for ecg-based cardiac disease detection: Signal and image analysis
The classification and identification of arrhythmias using ECG signals hold substantial
practical importance in the early prevention and detection of cardiac/cardiovascular …
practical importance in the early prevention and detection of cardiac/cardiovascular …
RETRACTED ARTICLE: Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
The heart disease is one of the most serious health problems in today's world. Over 50
million persons have cardiovascular diseases around the world. Our proposed work based …
million persons have cardiovascular diseases around the world. Our proposed work based …
Heartbeat classification fusing temporal and morphological information of ECGs via ensemble of classifiers
A method for the automatic classification of electrocardiograms (ECG) based on the
combination of multiple Support Vector Machines (SVMs) is presented in this work. The …
combination of multiple Support Vector Machines (SVMs) is presented in this work. The …
Novel methodology of cardiac health recognition based on ECG signals and evolutionary-neural system
P Pławiak - Expert Systems with Applications, 2018 - Elsevier
This article presents an innovative research methodology that enables the efficient
classification of cardiac disorders (17 classes) based on ECG signal analysis and an …
classification of cardiac disorders (17 classes) based on ECG signal analysis and an …
A hierarchical method based on weighted extreme gradient boosting in ECG heartbeat classification
Background and objective Electrocardiogram (ECG) is a useful tool for detecting heart
disease. Automated ECG diagnosis allows for heart monitoring on small devices, especially …
disease. Automated ECG diagnosis allows for heart monitoring on small devices, especially …
Novel genetic ensembles of classifiers applied to myocardium dysfunction recognition based on ECG signals
P Pławiak - Swarm and evolutionary computation, 2018 - Elsevier
This article presents an innovative genetic ensembles of classifiers applied to classification
of cardiac disorders (17 classes) based on electrocardiography (ECG) signal analysis. From …
of cardiac disorders (17 classes) based on electrocardiography (ECG) signal analysis. From …