Synthetic seismocardiogram generation using a transformer-based neural network.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Jun 20, 2023

Abstract

OBJECTIVE: To design and validate a novel deep generative model for seismocardiogram (SCG) dataset augmentation. SCG is a noninvasively acquired cardiomechanical signal used in a wide range of cardivascular monitoring tasks; however, these approaches are limited due to the scarcity of SCG data.

Authors

  • Mohammad Nikbakht
    Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
  • Asim H Gazi
    Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
  • Jonathan Zia
    Emory University School of Medicine, Atlanta, GA, United States.
  • Sungtae An
    Georgia Institute of Technology, College of Computing, Atlanta, GA, USA.
  • David J Lin
    Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
  • Omer T Inan
    School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
  • Rishikesan Kamaleswaran
    Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA.

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