Atrial constitutive neural networks

arXiv (Cornell University)

Abstract

This work presents a novel approach for characterizing the mechanical behavior of atrial tissue using constitutive neural networks. Based on experimental biaxial tensile test data of healthy human atria, we automatically discover the most appropriate constitutive material model, thereby overcoming the limitations of traditional, pre-defined models. This approach offers a new perspective on modeling atrial mechanics and is a significant step towards improved simulation and prediction of cardiac health.

Authors 3

1. Mathias Peirlinck

   Delft University of Technology

   Affiliation as printed

   dept. BioMechanical Engineering , Delft University of Technology , Delft , The Netherlands

2. Kevin Linka Aachen Institute of Applied Mechanics

   RWTH Aachen University

   Affiliation as printed

   Institute of Applied Mechanics , RWTH Aachen , Aachen , Germany

3. Ellen Kuhl

   Stanford University

   Affiliation as printed

   dept. Mechanical Engineering , Stanford University , Stanford , CA , USA