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El Bouny et al., 2020 - Google Patents

ECG heartbeat classification based on multi-scale wavelet convolutional neural networks

El Bouny et al., 2020

Document ID
3107297938753030171
Author
El Bouny L
Khalil M
Adib A
Publication year
Publication venue
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

External Links

Snippet

This paper proposes a novel Deep Learning technique for ECG beats classification. Unlike the traditional Deep Learning models, a new Multi-Scale Wavelet Convolutional Neural Networks (MS-WCNN) is proposed to recognize automatically various cardiac arrhythmias …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

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    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A—HUMAN NECESSITIES
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    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0402—Electrocardiography, i.e. ECG
    • A61B5/0452—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/04525—Detecting specific parameters of the electrocardiograph cycle by template matching
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