1. bookVolume 14 (2014): Issue 3 (June 2014)
Journal Details
License
Format
Journal
eISSN
1335-8871
First Published
07 Mar 2008
Publication timeframe
6 times per year
Languages
English
access type Open Access

Simplified 2D Bidomain Model of Whole Heart Electrical Activity and ECG Generation

Published Online: 17 Jun 2014
Volume & Issue: Volume 14 (2014) - Issue 3 (June 2014)
Page range: 136 - 143
Received: 11 Nov 2013
Accepted: 28 Jun 2014
Journal Details
License
Format
Journal
eISSN
1335-8871
First Published
07 Mar 2008
Publication timeframe
6 times per year
Languages
English
Abstract

The aim of this study was the development of a geometrically simple and highly computationally-efficient two dimensional (2D) biophysical model of whole heart electrical activity, incorporating spontaneous activation of the sinoatrial node (SAN), the specialized conduction system, and realistic surface ECG morphology computed on the torso. The FitzHugh-Nagumo (FHN) equations were incorporated into a bidomain finite element model of cardiac electrical activity, which was comprised of a simplified geometry of the whole heart with the blood cavities, the lungs and the torso as an extracellular volume conductor. To model the ECG, we placed four electrodes on the surface of the torso to simulate three Einthoven leads VI, VII and VIII from the standard 12-lead system. The 2D model was able to reconstruct ECG morphology on the torso from action potentials generated at various regions of the heart, including the sinoatrial node, atria, atrioventricular node, His bundle, bundle branches, Purkinje fibers, and ventricles. Our 2D cardiac model offers a good compromise between computational load and model complexity, and can be used as a first step towards three dimensional (3D) ECG models with more complex, precise and accurate geometry of anatomical structures, to investigate the effect of various cardiac electrophysiological parameters on ECG morphology.

Keywords

[1] Pullan, A.J., Buist, M.L., Cheng, L.K. (2005). Mathematically Modelling the Electrical Activity of the Heart - From Cell to Body Surface and Back Again. World Scientific.Search in Google Scholar

[2] Seemann, G. et al. (2010). Electrophysiological modeling for cardiology: Methods and potential applications. it - Information Technology, 52 (5), 242-249.10.1524/itit.2010.0598Search in Google Scholar

[3] Trayanova, N.A. (2011). Whole-heart modeling - Applications to cardiac electrophysiology and electromechanics. Circulation Research, 108, 113-128.10.1161/CIRCRESAHA.110.223610303196321212393Search in Google Scholar

[4] Trudel, M.-C. et al. (2004). Simulation of QRST integral maps with a membrane-based computer heart model employing parallel processing. IEEE Transactions of Biomedical Engineering, 51 (8), 1319-1329.10.1109/TBME.2004.82793415311816Search in Google Scholar

[5] Jacquemet, V., van Oosterom, A., Vesin, J., Kappenberger, L. (2006). Analysis of electrocardiograms during atrial fibrillation. IEEE Engineering in Medicine and Biology Magazine, 25 (6), 79-88.10.1109/EMB-M.2006.250511Search in Google Scholar

[6] Pfeifer, B. et al. (2007). A training whole-heart model for simulating propagation and ECG patters. Biomedical Signal Processing and Control, 2 (4), 323-330.10.1016/j.bspc.2007.06.002Search in Google Scholar

[7] Van Oosterom, A., Oostendorp, T.F. (2003). ECGSIM: An interactive tool for studying the genesis of QRST waveforms. Heart, 90 (2), 165-168.Search in Google Scholar

[8] Garny, A., Noble, D., Kohl, P. (2005). Dimensionality in cardiac modelling. Progress in Biophysics and Molecular Biology, 87 (1), 47-66.10.1016/j.pbiomolbio.2004.06.00615471590Search in Google Scholar

[9] Sovilj, S., Magjarevic, R., Lovell, N., Dokos, S. (2013). Realistic 3D bidomain model of whole heart electrical activity and ECG generation. In Computing in Cardiology Conference, 22-25 September 2013. IEEE, 377-380.Search in Google Scholar

[10] Sovilj, S., Magjarevic, R., Lovell, N., Dokos, S. (2013). A simplified 3D model of whole heart electrical activity and 12-lead ECG generation. Computational and Mathematical Methods in Medicine, article ID 134208-10.10.1155/2013/134208365463923710247Search in Google Scholar

[11] Gibbons Kroeker, C.A., Adeeb, S., Tyberg, J.V., Shrive, N.G. (2006). A 2D FE model of the heart demonstrates the role of the pericardium in ventricular deformation. American Journal of Physiology - Heart and Circulatory Physiology, 291 (5), H2229-2236.Search in Google Scholar

[12] Gabriel, S., Lau, R.W., Gabriel, C. (1996). The dielectric properties of biological tissues: II. Measurements in the frequency range 10 Hz to 20 GHz. Physics in Medicine and Biology, 41, 2251-2269.10.1088/0031-9155/41/11/0028938025Search in Google Scholar

[13] Malmivuo, J., Plonsey, R. (1995). Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Fields. Oxford University Press.Search in Google Scholar

[14] Fenton, F.H., Cherry, E.M. (2008). Models of cardiac cell. Scholarpedia, 3 (8), 1868.10.4249/scholarpedia.1868Search in Google Scholar

[15] Dokos, S., Cloherty, S.L., Lovell, N.H. (2007). Computational model of atrial electrical activation and propagation. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 908-911.10.1109/IEMBS.2007.435243818002104Search in Google Scholar

[16] Rogers, J.M., McCulloch, A.D. (1994). A collocation- Galerkin finite element model of cardiac action potential propagation. IEEE Transactions on Biomedical Engineering, 41, 743-757.10.1109/10.3100907927397Search in Google Scholar

[17] Petra, N., Gobbert, K.M. (2009). Parallel performance studies for COMSOL multiphysics using scripting and batch processing. In Proceedings of the COMSOL Conference 2009 Boston.Search in Google Scholar

[18] Janse, M.J. (1997). Why does atrial fibrillation occur? European Heart Journal, 18, C12-C18.10.1093/eurheartj/18.suppl_C.12Search in Google Scholar

[19] Nattel, S. (2002). New ideas about atrial fibrillation 50 years on. Nature, 415, 219-226.10.1038/415219a11805846Search in Google Scholar

[20] Seed, W.A. et al. (1987). Relation of human cardiac action potential duration to the interval between beats: Implications for the validity of rate corrected QT interval (QTc). British Heart Journal, 57, 32-37.10.1136/hrt.57.1.3212771433801256Search in Google Scholar

[21] Sovilj, S., Rajsman, G., Magjarevic, R. (2011). ECG based prediction of atrial fibrillation using support vector classifier. Automatika - Journal for Control, Measurement, Electronics, Computing and Communications, 52 (1), 58-67.10.1080/00051144.2011.11828404Search in Google Scholar

[22] Sovilj, S., Van Oosterom, A., Rajsman, G., Magjarevic, R. (2010). ECG based prediction of atrial fibrillation development following coronary artery bypass grafting. Physiological Measurement, 31, 663-677. 10.1088/0967-3334/31/5/00520308773Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo