A Computational Investigation into the Effect of Infarction on Clinical Human Electrophysiology Biomarkers
Paper in proceeding, 2014

The electrocardiogram (ECG) is often used to diag- nose myocardial infarction, but sensitivity and specificity are low. Here we present a computational framework for solving the bidomain equations over an image-based hu- man geometry and simulating the 12 lead ECG. First, we demonstrate this approach by evaluating a population of eight models with varying distributions of local action po- tential duration, and report that only the model with apico- basal and inter-ventricular heterogeneities produces con- cordant T waves. Second, we simulate the effects of an old anterior infarct, which causes a reduction in T wave amplitude and width. Our methodology can contribute to the understanding of ECG alterations under challenging conditions for clinical diagnosis.

Author

Louie Cardone-Noott

University of Oxford

Alfonso Bueno-Orovio

University of Oxford

Ana Mincholé

University of Oxford

Kevin Burrage

University of Oxford

University of Queensland

Mikael Wallman

Fraunhofer-Chalmers Centre

University of Oxford

Other publications Research

Nejib Zemzemi

Institut National de Recherche en Informatique et en Automatique (INRIA)

Erica Dall’Armellina

John Radcliffe Hospital

University of Oxford

Blanca Rodriguez

University of Oxford

Proceedings of the 41st Computing in Cardiology Conference, CinC 2014, Cambridge, United States, 7-10 September 2014

2325-8861 (ISSN)

Vol. 41 673-676

Subject Categories

Computational Mathematics

Other Medical and Health Sciences

Roots

Basic sciences

Areas of Advance

Life Science Engineering (2010-2018)

More information

Latest update

7/6/2021 9

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