A Comparison of Finite Element and Integral Equation Formulations for the Calculation of Electrocardiographic Potentials

Pilkington, T.C.; Morrow, Mary N.; Stanley, Peggy C.

doi:10.1109/tbme.1985.325438

Cited by 46 publications

(9 citation statements)

References 22 publications

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“…Residuals [26]. The finite element formulation of EIT using to its ability to model arbitrary geometries and various MWR with Galerkin approach is used to develop the EIT boundary conditions the FEM is the most common method forward solver though there are several different methods used currently used for the numerical solution of EIT problems in weighted residuals such as Collocation [18], Least Squares [24], [25]. The finite element method reduces a continuum [18].…”

Section: Biological Phantom Developed Eit Governing Equation Ismentioning

confidence: 99%

A FEM-Based Forward Solver for Studying the Forward Problem of Electrical Impedance Tomography (EIT) with A Practical Biological Phantom

Bera

Nagaraju

2009

2009 IEEE International Advance Computing Conference

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A Finite Element Method based forward solver is also depends on the Jacobean matrix formation, regularization developed for solving the forward problem of a 2D-Electrical technique and the converging nature of iterative algorithm Impedance Camera [15], was constructed by Henderson and E_ Webster to study the pulmonary edema in 1978. But due to VQtag poor signal to noise ratio [2] and poor spatial resolution [16] Measrementimaging. The reconstructed image quality in impedance tomography greatly depends on the performance of forward solver and the measurement errors which is influenced by the phantom geometry, electronic behavior of the current injector, Figure-i: An EIT system with electrode array on the domain to be imaged.data acquisition module and signal conditioners. Image quality 978-1-4244-2928-8/09/$250OO

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Section: Biological Phantom Developed Eit Governing Equation Ismentioning

confidence: 99%

A FEM-Based Forward Solver for Studying the Forward Problem of Electrical Impedance Tomography (EIT) with A Practical Biological Phantom

Bera

Nagaraju

2009

2009 IEEE International Advance Computing Conference

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“…Before extracting additional results from Eq. 2.1 we note that a variational principle has also been used in electrocardiography (Yamashita and Takahashi, 1984;Pilkington et al, 1985), but which differs from Eq. 2.1 in two important respects.…”

Section: The Variational Principlementioning

confidence: 99%

Return current in encephalography. Variational principles

Heller

1990

Biophysical Journal

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The encephalographic problem of finding the electric potential V and the return current associated with any assumed primary current, Jp, is put in the form of a variational principle. With Jp and the conductivity specified, the correct V is one which makes an integral quantity P[V] a maximum. The terms in P[V] are related to the rates at which work is done by the electric field on the primary and return currents. It is shown that there is a unique solution for the electric field, and it satisfies the conservation of energy; this condition can serve as a check on any numerical solution. With the conductivity a different constant in different regions, the variational principle is recast in terms of the charge density on the surfaces of discontinuity. An iteration-variation method for finding the solution is outlined, and possible computational advantages over other approaches are discussed.

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“…The spatial coordinates of the epicardial electrodes were used to triangulate the heart surface and thus determine each electrode's nearest neighbors.34 35 The gradient, E, was found by minimizing the function, F, that incorporates the distance (d) between an observer electrode and its neighbors and the voltage (v) difference between the observer electrode and its neighbors. The function F is given in equation 1: The symbols, x, y, and z represent the cartesian coordinates.…”

Section: Appendixmentioning

confidence: 99%

The potential gradient field created by epicardial defibrillation electrodes in dogs.

Chen¹,

Wolf²,

Claydon³

et al. 1986

Circulation

135

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Knowledge of the potential gradient field created by defibrillation electrodes is important for the understanding and improvement of defibrillation. To obtain this knowledge by direct measurements, potentials were recorded from 60 epicardial, eight septal, and 36 right ventricular transmural electrodes in six open-chest dogs while 1 to 2 V shocks were given through defibrillation electrodes (1) on the right atrium and left ventricular apex (RA. V) and (2) on the right and left ventricles (RV.LV). The potential gradient field across the ventricles was calculated for these low voltages. Ventricular fibrillation was electrically induced, and ventricular activation patterns were recorded after delivering high-voltage shocks just below the defibrillation threshold. With the low-voltage shocks, the potential gradient field was very uneven, with the highest gradient near the epicardial defibrillation electrodes and the weakest gradient distant from the defibrillation electrodes for both RA.V and RV.LV combinations. The mean ratio of the highest to the lowest measured gradient over the entire ventricular epicardium was 19.4 + 8. 1 SD for the RA.V combination and 14.4 ± 3.4 for the RV.LV combination. For both defibrillation electrode combinations, the earliest sites of activation after unsuccessful shocks just below the defibrillation threshold were located in areas where the potential gradient was weak for the low-voltage shocks. We conclude that (1) there is a markedly uneven distribution of potential gradients for epicardial defibrillation electrodes with most of the voltage drop occurring near the electrodes, (2) the potential gradient field is significant because it determines where shocks fail to halt fibrillation, and (3) determination of the potential gradient field should lead to the development of improved electrode locations for defibrillation. Circulation 74, No. 3, 626-636, 1986.

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A Comparison of Finite Element and Integral Equation Formulations for the Calculation of Electrocardiographic Potentials

Cited by 46 publications

References 22 publications

A FEM-Based Forward Solver for Studying the Forward Problem of Electrical Impedance Tomography (EIT) with A Practical Biological Phantom

A FEM-Based Forward Solver for Studying the Forward Problem of Electrical Impedance Tomography (EIT) with A Practical Biological Phantom

Return current in encephalography. Variational principles

The potential gradient field created by epicardial defibrillation electrodes in dogs.

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