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

• 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

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...