Work

Reconstructing Cardiac Voltage Using Data Assimilation: Effects of Observation Distribution

Year: 2023

Type: conference-paper

Abstract: Both experimental and clinical cardiac electrophysiology data often are recorded with limited spatial resolution or inconsistent spatial distribution.Rather than interpolating such data, which neglects constraints imposed by dynamics, data assimilation can be used to mitigate the effects of low-resolution data by providing estimates of voltage in unmapped areas.Here, we investigate the effects of different spatial distributions of observation data on cardiac voltage reconstructions over time using data assimilation.We used an ensemble Kalman filter method to reconstruct complete, uniform voltage data from observational data with different spatial distributions.Stable spiral-wave and sustained spiral-wave breakup cases from the modified Mitchell-Schaeffer model were analyzed.Coarse uniform observations and observations restricted to half the domain were considered.Stable spiral wave dynamics could be reconstructed well, with some lag at the coarsest resolutions and for half-domain observations far from the spiral core.Breakup cases were more difficult to match quantitatively; scenarios with fewer spirals or greater observation coverage of the most intense breakup regions could be reconstructed more accurately.Overall, we found that accurate voltage reconstructions could be generated for stable waves and breakup cases using data assimilation, provided that observations include regions driving breakup.

Source: Computing in cardiology

DOI: 10.22489/cinc.2023.407

Authors: Shoale Badr, Flavio Fenton, Elizabeth Cherry

Institution: Georgia Institute of Technology

Language: English

Topic: Cardiac electrophysiology and arrhythmias

Subfield: Cardiology and Cardiovascular Medicine

Field: Medicine

Domain: Health Sciences

Open Access status: bronze

Funders: National Science Foundation, National Institutes of Health, National Heart, Lung, and Blood Institute, Division of Civil, Mechanical and Manufacturing Innovation

Awards: Collaborative Research: Developing a Quantitative Three-Dimensional Understanding of Cardiac Arrhythmias, CPS: Frontier: Collaborative Research: Compositional, Approximate, and Quantitative Reasoning for Medical Cyber-Physical Systems, Integrative High-Resolution Experimental and Multiscale Modeling of Arrhythmias to Optimize Low Energy Anti-fibrillation Pacing (LEAP)