Self-organizing Network Simulation of Cardiac Electrical Dynamics
Research Poster Engineering 2025 Graduate ExhibitionPresentation by Runsang Liu
Exhibition Number 126
Abstract
Network provides a low-dimensional representation of the heart through a sparse adjacency matrix, which ushers in a new opportunity to conduct cardiac simulation. We discovered that a self-organizing network encodes and resembles complex heart geometry. This, in turn, helps characterize the structure-function relationship of the heart through network theory. However, very little has been done to investigate the simulation of electrical activity on a self-organizing network. Thus, this paper presents a new self-organizing network approach for simulating cardiac electrical dynamics. We formulate and solve dynamic equations on the network to simulate the propagation and turbulent behavior of electrical waves. Experimental results show that the proposed approach not only yields a compact network representation that resembles the heart geometry, but also provides an effective simulation of spatiotemporal dynamics when benchmarking with traditional finite element method (FEM) simulations.
Importance
Self-organizing network encodes and resembles the complex heart geometry through a sparse adjacency matrix. The investigation of dynamics on self-organizing networks is a unique study within complex network science. This paper is aimed at testing a new hypothesis -- ``whether and how cardiac electrical activity can be simulated on the network?'' Our experiments demonstrate a new approach for simulating cardiac electrical dynamics on a self-organizing network of the heart, thereby providing a compact yet effective tool for cardiac research.