Generation of 12-Lead Electrocardiogram with Subject-Specific, Image-Derived Characteristics Using a Conditional Variational Autoencoder

Deep learning models have proven their value in the analysis of electrocardiogram (ECG). Among these, deep generative models have shown their ability in ECG generation. In this paper, we propose a conditional variational autoencoder (cVAE) to automatically generate realistic 12-lead ECG signals. Our...

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Bibliographic Details

Published in:	Proceedings (International Symposium on Biomedical Imaging) pp. 1 - 5
Main Authors:	Sang, Yuling, Beetz, Marcel, Grau, Vicente
Format:	Conference Proceeding
Language:	English
Published:	IEEE 28.03.2022
Subjects:	Analytical models Biological system modeling Deep learning ECG Generation Electrocardiography Heart Heart Position and Orientation Morphology Sensitivity Variational Auto-encoder
ISSN:	1945-8452
Online Access:	Get full text
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