Alday, EAP, Colman, MA orcid.org/0000-0003-2817-8508 and Zhang, H (2017) Reconstruction of atrial ectopic focal and Re-entrant excitations from body surface potentials. Insights from 3D virtual human atria and torso. In: Computing in Cardiology 2016 (CinC 2016). CinC 2016, 11-14 Sep 2016, Vancouver, Canada. IEEE , pp. 701-704. ISBN 9781509008964
Abstract
Non-invasive electrocardiographic imaging has been seen as a painless and economic method to map the electrical functions of the heart. However, it is still a great challenge to obtain accurate reconstruction of cardiac electrical activity from body surface potentials (BSP) due to the ill-posed behaviour of the cardiac inverse-problem. Though some advances have been made in solving the inverse-problem, few studies have been conducted for the atria, which have dramatic differences to the ventricles in their anatomical structures and electrophysiological properties. It is unclear either how the spatial resolution of electrodes on the BSP and rapid excitation rates of atrial activation during atrial fibrillation affect the accuracy of the inverse-problem. In this study, we used a biophysically detailed model of the human atria and torso to investigate effects of multi-lead ECG on the accuracy of reconstructed atrial excitation pattern on the epicardiac surface during the time courses of atrial fibrillation induced by electrical remodelling. It was shown that the solution of the atrial inverse-problem was dependent on the spatial resolution of electrodes on the body surface. The solution was also influenced by the morphology of the AP, rate and types of atrial excitation as well as the implantation of variant orders of the Tikhonov regularization method.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2017, the Author(s). This is an open access paper under the terms of the Creative Commons Attribution License CC-BY [https://creativecommons.org/licenses/by/2.5/]. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biomedical Sciences (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 May 2017 16:03 |
Last Modified: | 05 Oct 2017 16:19 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.22489/CinC.2016.205-397 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:116368 |