Physics-based deep spatio-temporal metamodeling for cardiac electrical conduction simulation

Hao Yan, Xinyu Zhao, Zhiyong Hu, Dongping Du

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Modeling and simulation have been widely used in both cardiac research and clinical study to investigate cardiac disease mechanism and develop new treatment design. Electrical conduction among cardiac tissue is commonly modeled with a partial differential equation, i.e., reaction-diffusion equation, where the reaction term describes cellular excitation and diffusion term describes electrical propagation. Cellular excitation can be modeled by either detailed human cellular models or simplified models such as the FitzHugh-Nagumo model; electrical propagation can be simulated using either biodomain or mono-domain tissue model. However, existing cardiac models have a great level of complexity, and the simulation is often time-consuming. This paper develops a new spatiotemporal model as a surrogate model of the timeconsuming cardiac model. Specifically, we propose to investigate the auto-regressive convolutional neural network (AR-CNN) and convolutional long short-term memory (Conv-LSTM) to model the spatial and temporal structure for the metamodeling. Model predictions are compared to the one-dimensional simulation data to validate the prediction accuracy. The metamodel can accurately capture the properties of the individual cardiac cell, as well as the electrical wave morphology in cardiac fiber at different simulation scenarios, which demonstrates its superior performance in modeling and the long-term prediction.

Original languageEnglish (US)
Title of host publication2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019
PublisherIEEE Computer Society
Pages152-157
Number of pages6
ISBN (Electronic)9781728103556
DOIs
StatePublished - Aug 2019
Externally publishedYes
Event15th IEEE International Conference on Automation Science and Engineering, CASE 2019 - Vancouver, Canada
Duration: Aug 22 2019Aug 26 2019

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2019-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference15th IEEE International Conference on Automation Science and Engineering, CASE 2019
CountryCanada
CityVancouver
Period8/22/198/26/19

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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