Electrodynamic heart model construction and ECG simulation.

Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
Methods of Information in Medicine (Impact Factor: 1.08). 02/2006; 45(5):564-73.
Source: PubMed

ABSTRACT In this paper, we present a unified electrodynamic heart model that permits simulations of the body surface potentials generated by the heart in motion. The inclusion of motion in the heart model significantly improves the accuracy of the simulated body surface potentials and therefore also the 12-lead ECG.
The key step is to construct an electromechanical heart model. The cardiac excitation propagation is simulated by an electrical heart model, and the resulting cardiac active forces are used to calculate the ventricular wall motion based on a mechanical model. The source-field point relative position changes during heart systole and diastole. These can be obtained, and then used to calculate body surface ECG based on the electrical heart-torso model.
An electromechanical biventricular heart model is constructed and a standard 12-lead ECG is simulated. Compared with a simulated ECG based on the static electrical heart model, the simulated ECG based on the dynamic heart model is more accordant with a clinically recorded ECG, especially for the ST segment and T wave of a V1-V6 lead ECG. For slight-degree myocardial ischemia ECG simulation, the ST segment and T wave changes can be observed from the simulated ECG based on a dynamic heart model, while the ST segment and T wave of simulated ECG based on a static heart model is almost unchanged when compared with a normal ECG.
This study confirms the importance of the mechanical factor in the ECG simulation. The dynamic heart model could provide more accurate ECG simulation, especially for myocardial ischemia or infarction simulation, since the main ECG changes occur at the ST segment and T wave, which correspond with cardiac systole and diastole phases.

1 Bookmark
  • [Show abstract] [Hide abstract]
    ABSTRACT: The heart movement affects the body surface electrocardiogram (ECG) and magnetocardiography (MCG). However, in the previous MCG simulation studies, the heart was always assumed static and the heart movement was seldom taken into account. In this paper, we present a simulation study of MCG based on an electrodynamic heart model to investigate the effect of heart movement on MCG. The electrodynamic biventricular model was constructed based on an electrical heart model by a weak electric-mechanic coupling. From the electrodynamic heart model, the deformation of the heart and the relationship of the dipole source and the cardiac electromagnetic field were obtained. The different performance of the MCG and ECG caused by the effects of heart movement and volume conductor model were investigated and compared. The simulation results demonstrated that the including of the heart movement will improve the accuracy of both the simulated ECG and MCG, especially for the ST interval, and the effect of heart movement on MCG is lager than that of on ECG. The volume conductor, however, has larger effect on simulated ECG/MCG of the static heart model based than that of the dynamic heart model based. This study suggested that the heart movement is more important for MCG than ECG, and should be considered in future MCG simulation study.
    IEEE Transactions on Magnetics 10/2011; · 1.42 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this study, the effects of cardiac fibroblast proliferation on cardiac electric excitation conduction and mechanical contraction were investigated using a proposed integrated myocardial-fibroblastic electromechanical model. At the cellular level, models of the human ventricular myocyte and fibroblast were modified to incorporate a model of cardiac mechanical contraction and cooperativity mechanisms. Cellular electromechanical coupling was realized with a calcium buffer. At the tissue level, electrical excitation conduction was coupled to an elastic mechanics model in which the finite difference method (FDM) was used to solve electrical excitation equations, and the finite element method (FEM) was used to solve mechanics equations. The electromechanical properties of the proposed integrated model were investigated in one or two dimensions under normal and ischemic pathological conditions. Fibroblast proliferation slowed wave propagation, induced a conduction block, decreased strains in the fibroblast proliferous tissue, and increased dispersions in depolarization, repolarization, and action potential duration (APD). It also distorted the wave-front, leading to the initiation and maintenance of re-entry, and resulted in a sustained contraction in the proliferous areas. This study demonstrated the important role that fibroblast proliferation plays in modulating cardiac electromechanical behaviour and which should be considered in planning future heart-modeling studies.
    Journal of Zhejiang University SCIENCE B 03/2014; 15(3):225-42. · 1.11 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, two hybrid regularization frameworks, LSQR-Tik and Tik-LSQR, which integrate the properties of the direct regularization method (Tikhonov) and the iterative regularization method (LSQR), have been proposed and investigated for solving ECG inverse problems. The LSQR-Tik method is based on the Lanczos process, which yields a sequence of small bidiagonal systems to approximate the original ill-posed problem and then the Tikhonov regularization method is applied to stabilize the projected problem. The Tik-LSQR method is formulated as an iterative LSQR inverse, augmented with a Tikhonov-like prior information term. The performances of these two hybrid methods are evaluated using a realistic heart-torso model simulation protocol, in which the heart surface source method is employed to calculate the simulated epicardial potentials (EPs) from the action potentials (APs), and then the acquired EPs are used to calculate simulated body surface potentials (BSPs). The results show that the regularized solutions obtained by the LSQR-Tik method are approximate to those of the Tikhonov method, the computational cost of the LSQR-Tik method, however, is much less than that of the Tikhonov method. Moreover, the Tik-LSQR scheme can reconstruct the epcicardial potential distribution more accurately, specifically for the BSPs with large noisy cases. This investigation suggests that hybrid regularization methods may be more effective than separate regularization approaches for ECG inverse problems.
    Physics in Medicine and Biology 10/2008; 53(18):5151-64. · 2.70 Impact Factor