Synthetic seismocardiogram generation using a transformer-based neural network

Abstract

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Apr 13, 2023
Source ID
10.1093/jamia/ocad067

Entities

People

  • Asim H Gazi
  • David J. Lin
  • Jonathan Zia
  • Mohammad Nikbakht
  • Omer T. Inan
  • Rishikesan Kamaleswaran
  • Sungtae An

Organizations

  • Emory University
  • Georgia Tech
  • National Institutes of Health
  • National Science Foundation
  • Office of Naval Research

Tags

Fields of Study

  • Computer science

Readers

  • Computer Engineering
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks