Location Estimation of Atrial Activity from Epicardial Electrogram measurements

Master thesis (2023)

Authors

A. Suresan Electrical Engineering, Mathematics and Computer Science

Contributors

R.F. Remis Tera-Hertz Sensing - EEMCS (mentor)
R.C. Hendriks Signal Processing Systems - EEMCS (mentor)
C.M. Boutry Electronic Components, Technology and Materials - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2023 Anjali Suresan
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Published Date

30-08-2023

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Atrial Fibrillation (AF) is a cardiac arrhythmia that occurs due to the initiation of electrical impulses in the heart in an uncoordinated manner, giving rise to a disorganized and rapid heartbeat. The progression of AF over time can lead to complications such as stroke and heart failure. Catheter ablation is an established treatment protocol adopted to eliminate AF triggers and restore normal sinus rhythm in patients. To improve the success rates of ablation procedures, mapping and localizing the regions in the heart that give rise to uncoordinated impulses is crucial. This work focuses on obtaining a visual estimate of the location of irregular electrical activity within a volume domain of cardiac tissue using epicardial electrogram measurements.
A straightforward, effective, and computationally fast backprojection imaging method is proposed that provides an indication of the regions in a given volume of cardiac tissue that exhibit prominent irregular atrial activity. The chosen volume is subdivided into non-overlapping voxels, and the standard electrogram signal model is discretized to a matrix multiplication form. The inverse problem of reconstructing the transmembrane current distribution in the volume is solved using the epicardial electrogram readings obtained from the surface and the inverse distances matrix containing the inverse of the distances from each electrode to each voxel within the volume domain. The generated backprojection images are visualized to estimate the location (x and y coordinate information) and depth of irregular atrial activity in the volume. To improve the accuracy of localization while maintaining the computationally fast nature of the proposed solution, Singular Value decomposition (SVD) of the inverse distances matrix is proposed for the transmembrane current reconstruction. The obtained visual estimates can guide ablation procedures, making them more targeted, and reducing the need for repeat ablation procedures due to AF recurrence.