The combination method: a numerical technique for electrocardiographic calculations

Stanley, Peggy C.; Pilkington, T.C.

doi:10.1109/10.18752

Cited by 29 publications

(2 citation statements)

References 7 publications

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“…This approach is commonly termed the boundary element method (BEM). Regions of anisotropic conductivity can be handled by combining the BEM method with a volume-based approach (Stanley andPilkington 1989, Pullan 1996).…”

Section: Ecg Simulationmentioning

confidence: 99%

Computational framework for simulating the mechanisms and ECG of re-entrant ventricular fibrillation

Clayton

Holden

2002

Physiol. Meas.

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Ventricular arrhythmias remain an important cause of morbidity and mortality in the Western world. Although the underlying mechanisms of these arrhythmias can be studied experimentally, these investigations are in general limited to mapping electrical activity on the heart surface. Computational models of action potential propagation offer a potentially powerful way to study electrical activation and arrhythmias, but current models are not easy to link to the clinical environment. In this paper, we describe a framework for computing action potential propagation in which the geometry, electrophysiology and regional properties of ventricular myocardium can be specified so that, for example, different models for cardiac cellular electrophysiology can be used. We have computed action potential propagation during both normal beats and re-entry in an anatomically accurate model of ventricular geometry. By computing the resultant electric current flow in the torso we have also generated simulated ECG signals that result from specific activation patterns in the ventricular model. Models can be powerful tools for explaining observations, and this approach is able to provide a direct link between the different configurations of re-entry observed in computational and experimental studies, and the ECG signals observed in patients.

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Section: Ecg Simulationmentioning

confidence: 99%

Computational framework for simulating the mechanisms and ECG of re-entrant ventricular fibrillation

Clayton

Holden

2002

Physiol. Meas.

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“…In general, matrix relating the body potentials to the chest potentials is generated numerically and then inverted. Direct inversion [2,3,4,5,6,71 is not effective, so generally some type of stabilization is employed. Two of the most popular techniques are truncated Singular Value Decomposition (SVD) [8, 9, 10, 1 1, 121 and Tikhonov regularization [9, 13, 14, 151. Recently [16,17,181, we proposed some promising new Generalized Eigensystem (GES) finite element methods for stabilizing the inverse problem of electrocardiography.…”

Section: Introductionmentioning

confidence: 99%

Performance of generalized eigensystem and truncated singular value decomposition methods for the inverse problem of electrocardiography

Olson

Throne

Windle

1997

Inverse Problems in Engineering

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Communicated by G. S. DulikravichSingular Value Decomposition (SVD) and Generalized Eigensystern (GES) inverse techniques are compared for their ability to solve the inverse problem of electrocardiography. In the inverse problem of electrocardiography, electrical potential data for numerous locations on the body (torso) surface is used to infer the electrical potentials on the heart surface, while the governing equation and material properties are assumed known. This paper addresses two areas. First, the previously observed improved performance of GES compared to SVD is explained in terms of the unique nature of the GES vectors. Second, epicardial data from six in-vitro rabbit heart experiments are used to project body surface data for six different geometries, and inverse solutions are computed both with and without added noise. For concentric geometries, GES outperformed SVD in all instances. For eccentric heartlbody geometries, GES outperformed SVD when the inverse errors themselves were small. In all cases, GES was less sensitive to added noise than SVD.

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The Genesis of the Electrocardiogram ( ECG )

Rieta

Alcaraz

2017

Wiley Encyclopedia of Electrical and Electronics Engineering

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The graphical representation of the body surface potential difference originated by the electric activity of the heart between two points is known as the electrocardiogram (ECG). The aim of this article is to give an outline of the concepts that have been used to develop a model on the genesis of the ECG. In other words, the underlying principles relating the bioelectric sources of the heart to the body surface potentials. The genesis of the ECG signal is presented from two different perspectives. The first one considers the heart as a current dipole located in an infinite and homogeneous volume conductor. This scenario corresponds to the original theories introduced by Willem Einthoven at the beginning of the twentieth century on the mechanisms of ECG and it can be considered as the classical electrocardiography. The second perspective came about thanks to digital computers. Basically it consists of deriving numerically the body surface potentials created by the heart's electrical activity and considering a discretized representation of both the heart and the human torso. This new perspective, which allows the numerical solution of the heart's potentials at any place in the human body, is the so‐called forward problem of electrocardiography.

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The combination method: a numerical technique for electrocardiographic calculations

Cited by 29 publications

References 7 publications

Computational framework for simulating the mechanisms and ECG of re-entrant ventricular fibrillation

Computational framework for simulating the mechanisms and ECG of re-entrant ventricular fibrillation

Performance of generalized eigensystem and truncated singular value decomposition methods for the inverse problem of electrocardiography

The Genesis of the Electrocardiogram ( ECG )

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