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Proposed dataset
The proposed dataset is a custom dataset created for the purpose of this paper. It includes 500 EEG signals, each of 23.6 seconds duration. -
1D Self-Organized Operational Neural Networks
The proposed 1D Self-ONNs for patient-specific ECG classification and arrhythmia detection. -
ECG Arrhythmia Classification Dataset
The dataset used in this paper for ECG arrhythmia classification, combining ECG rhythms from the MIT-BIH Arhythmia Database (MITDB), Long-Term Atrial Fibrillation Database... -
12-lead ECG Database for Arrhythmia Research
ECG dataset used for arrhythmia research -
European ST-T Database
Five open ECG databases from PhysioNet are involved in this study namely the MIT-BIH arrhythmia database,St-Petersburg Institute of Cardiological Technics 12-lead Arrhythmia... -
The MIT-BIH Long Term Database
Five open ECG databases from PhysioNet are involved in this study namely the MIT-BIH arrhythmia database,St-Petersburg Institute of Cardiological Technics 12-lead Arrhythmia... -
The MIT-BIH Normal Sinus Rhythm Database
Five open ECG databases from PhysioNet are involved in this study namely the MIT-BIH arrhythmia database,St-Petersburg Institute of Cardiological Technics 12-lead Arrhythmia... -
St-Petersburg Institute of Cardiological Technics 12-lead Arrhythmia Database
Five open ECG databases from PhysioNet are involved in this study namely the MIT-BIH arrhythmia database,St-Petersburg Institute of Cardiological Technics 12-lead Arrhythmia... -
MIT-BIH arrhythmia database
Five open ECG databases from PhysioNet are involved in this study namely the MIT-BIH arrhythmia database,St-Petersburg Institute of Cardiological Technics 12-lead Arrhythmia... -
ECG Classification System for Arrhythmia Detection Using Convolutional Neural ...
ECG classification system for arrhythmia detection using Convolutional Neural Network -
MIT-BIH dataset
The MIT-BIH dataset contains 48 hours of two-channel ambulatory ECG signals obtained from 47 subjects. -
Proposed Framework
The proposed framework aims to address the limitations of deep learning applications for ECG signal classification. Secondly, we proposed a new classifier for ECG signals. When... -
MIT-BIH Arrhythmia dataset
MIT-BIH Arrhythmia dataset
