The effects of electrode configuration on omnipolar signals: an in-silico approach
File(s)
Accepted version
Author(s)
Letchumy Mahendra Kumar, Jothi
Brook, Joe
Ntagiantas, Konstantinos
Panagopoulos, Dimitrios
S Peters, Nicholas
Type
Conference Paper
Abstract
Atrial Fibrillation (AF) is the most common cardiac ar-rhythmia, involving pathological triggers and substrate in the atria. In the clinical catheter laboratory, contact electrograms are an essential tool to characterise AF. Omnipolar electrograms (OE), derived from three or more neighbouring electrodes, are thought to be superior compared to traditional unipolar and bipolar electrograms by eliminating far-field effects and correcting for wavefront incidence angle. We sought to understand the changes in OE morphology under different electrode configurations using 2D simulations of healthy tissue and scarred tissue. Virtual unipolar electrograms (UE) were generated from single electrodes which were used to predict the local electric field and subsequently calculate OEs in cliques of 3, 4, and 6 electrodes at different inter-electrode spacings. Five features were identified on each OE to measure changes in OE morphology under different clique configurations. Additionally, the morphology of the OE signals in the presence of fibrosis was examined. OE signals obtained from scarred tissue are more fractionated compared to healthy tissue. The most appropriate inter-electrode distance for interpreting the OE signals was found to be 2-3mm, using either three or four electrodes.
Date Issued
2022-12-31
Date Acceptance
2022-09-01
Citation
Computing in Cardiology Conference (CinC), 2022
ISSN
2325-887X
Publisher
Computing in Cardiology
Journal / Book Title
Computing in Cardiology Conference (CinC)
Copyright Statement
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Identifier
http://dx.doi.org/10.22489/cinc.2022.247
Source
2022 Computing in Cardiology Conference
Publication Status
Published
Start Date
2022-09-04
Finish Date
2022-09-07
Coverage Spatial
Tampere, Finland