A fast model for solving the ECG forward problem based on an evolutionary algorithm

Houari, Karim El; Kachenoura, Amar; Albera, Laurent; Bensaid, Siouar; Karfoul, Ahmad; Boichon-Grivot, Christelle; Rochette, Michel; Hernández, Alfredo

doi:10.1109/camsap.2017.8313083

Cited by 7 publications

(7 citation statements)

References 11 publications

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“…Parameter C m is the membrane surface and could be considered to have a constant physical value. We have also excluded c 1 , c 2 , d, e, k, A and B because they appear to be less influent on electrical activity in a previous study [15]. Nevertheless, the method was applied on 3 parameters (χ, a and b) for 16 segments, which represent a total of 48 parameters.…”

Section: Sensitivity Analysis Methodsmentioning

confidence: 99%

“…Propagation of the transmembrane potential V m was represented under the hypothesis of equal anisotropy ratio [29,30,15]:…”

Section: Electrical Problemmentioning

confidence: 99%

“…where a, b, c 1 , c 2 , d, e, k, A and B are region specific parameters [31,15]. A point N exct of the domain Ω is electrically stimulated with a value I stim for a preset time t exc (ν is the unit outward normal vector):…”

Section: Electrical Problemmentioning

confidence: 99%

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Sensitivity Analysis of a Left Ventricle Model in the Context of Intraventricular Dyssynchrony

et al. 2019

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The objective of the current study was to propose a sensitivity analysis of a 3D left ventricle model in order to assess the influence of parameters on myocardial mechanical dispersion. A finite element model (FEM) of LV electromechanical activity was proposed and a screening method was used to evaluate the sensitivity of model parameters on the standard deviation of time to peak strain (TPS-SD). Results highlight the importance of propagation parameters associated with septal and lateral segments activation. Simulated curves were compared to myocardial strains, obtained from echocardiography of one healthy subject and one patient diagnosed with intraventricular dyssynchrony and coronary artery disease. Results show a close match between simulation and clinical strains and illustrate the model ability to reproduce myocardial strains in the context of intraventricular dyssynchrony.

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Section: Sensitivity Analysis Methodsmentioning

confidence: 99%

“…Propagation of the transmembrane potential V m was represented under the hypothesis of equal anisotropy ratio [29,30,15]:…”

Section: Electrical Problemmentioning

confidence: 99%

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Sensitivity Analysis of a Left Ventricle Model in the Context of Intraventricular Dyssynchrony

et al. 2019

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“…The literature dealing with dipole models for the electric activity of the heart is very extensive 5,6,7,8,9,10,11,12,13,14,15 . Alternative approaches dealing with specific aspects of the heart's electric activity are also too many to be easily summarised 16,17,18,19,20,21 .…”

Section: Mainmentioning

confidence: 99%

A Unique Cardiac Electrophysiological 3D Model

Rueda¹,

Rodríguez-Collado²,

Fernández³

et al. 2022

Preprint

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Mathematical models of cardiac electrical activity are one of the most important tools for elucidating information about the heart diagnostic. Even though it is one of the major problems in biomedical research, an efficient mathematical formulation for this modelling has still not been found. In this paper, we present an outstanding mathematical model. It relies on a five dipole representation of the cardiac electric source, each one associated with the well-known waves of the electrocardiogram signal. The mathematical formulation is simple enough to be easily parametrized and rich enough to provide realistic signals. Beyond the physical basis of the model, the parameters are physiologically interpretable as they characterize the wave shape, similar to what a physician would look for in signals, thus making them very useful in diagnosis. The model accurately reproduces the electrocardiogram and vectocardiogram signals of any diseased or healthy heart, bringing together different systems in a single model. Furthermore, a novel algorithm accurately identifies the model parameters. This new discovery represents a revolution in electrocardiography research, solving one of the main problems in this field. It is especially useful for the automatic diagnosis of cardiovascular diseases, patient follow-up or decision-making on new therapies.

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“…Substantial computational cost is required to analyze the cardiac phenomena in a whole-body model, which commonly consists of a relatively large number of elements (e.g., voxel models applying finite difference methods and tetrahedral models using finite element methods). One of the limitations to processing whole-body models is the computationally expensive forward problems that need to be resolved to solve the main inverse problem [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

ECG Localization Method Based on Volume Conductor Model and Kalman Filtering

Nakano

Rashed

Nakane

et al. 2021

Sensors

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The 12-lead electrocardiogram was invented more than 100 years ago and is still used as an essential tool in the early detection of heart disease. By estimating the time-varying source of the electrical activity from the potential changes, several types of heart disease can be noninvasively identified. However, most previous studies are based on signal processing, and thus an approach that includes physics modeling would be helpful for source localization problems. This study proposes a localization method for cardiac sources by combining an electrical analysis with a volume conductor model of the human body as a forward problem and a sparse reconstruction method as an inverse problem. Our formulation estimates not only the current source location but also the current direction. For a 12-lead electrocardiogram system, a sensitivity analysis of the localization to cardiac volume, tilted angle, and model inhomogeneity was evaluated. Finally, the estimated source location is corrected by Kalman filter, considering the estimated electrocardiogram source as time-sequence data. For a high signal-to-noise ratio (greater than 20 dB), the dominant error sources were the model inhomogeneity, which is mainly attributable to the high conductivity of the blood in the heart. The average localization error of the electric dipole sources in the heart was 12.6 mm, which is comparable to that in previous studies, where a less detailed anatomical structure was considered. A time-series source localization with Kalman filtering indicated that source mislocalization could be compensated, suggesting the effectiveness of the source estimation using the current direction and location simultaneously. For the electrocardiogram R-wave, the mean distance error was reduced to less than 7.3 mm using the proposed method. Considering the physical properties of the human body with Kalman filtering enables highly accurate estimation of the cardiac electric signal source location and direction. This proposal is also applicable to electrode configuration, such as ECG sensing systems.

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A fast model for solving the ECG forward problem based on an evolutionary algorithm

Cited by 7 publications

References 11 publications

Sensitivity Analysis of a Left Ventricle Model in the Context of Intraventricular Dyssynchrony

Sensitivity Analysis of a Left Ventricle Model in the Context of Intraventricular Dyssynchrony

A Unique Cardiac Electrophysiological 3D Model

ECG Localization Method Based on Volume Conductor Model and Kalman Filtering

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