Genetic algorithm-based regularization parameter estimation for the inverse electrocardiography problem using multiple constraints

Date

2013-04-01

Author

Serinağaoğlu Doğrusöz, Yeşim
Gavgani, Alireza Mazloumi

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

224
views

0
downloads

In inverse electrocardiography, the goal is to estimate cardiac electrical sources from potential measurements on the body surface. It is by nature an ill-posed problem, and regularization must be employed to obtain reliable solutions. This paper employs the multiple constraint solution approach proposed in Brooks et al. (IEEE Trans Biomed Eng 46(1):3-18, 1999) and extends its practical applicability to include more than two constraints by finding appropriate values for the multiple regularization parameters. Here, we propose the use of real-valued genetic algorithms for the estimation of multiple regularization parameters. Theoretically, it is possible to include as many constraints as necessary and find the corresponding regularization parameters using this approach. We have shown the feasibility of our method using two and three constraints. The results indicate that GA could be a good approach for the estimation of multiple regularization parameters.

Subject Keywords

Inverse electrocardiography, Multiple constraints, Regularization parameter, Genetic algorithm

URI

https://hdl.handle.net/11511/33331

Journal

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING

DOI

https://doi.org/10.1007/s11517-012-1005-6

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

Effects of a priori parameter selection in minimum relative entropy method on inverse electrocardiography problem ONAK, Onder Nazim; Serinağaoğlu Doğrusöz, Yeşim; WEBER, GERHARD WİLHELM (2018-01-01) The goal in inverse electrocardiography (ECG) is to reconstruct cardiac electrical sources from body surface measurements and a mathematical model of torso-heart geometry that relates the sources to the measurements. This problem is ill-posed due to attenuation and smoothing that occur inside the thorax, and small errors in the measurements yield large reconstruction errors. To overcome this, ill-posedness, traditional regularization methods such as Tikhonov regularization and truncated singular value decom...
Improved performance of Bayesian solutions for inverse Electrocardiography using multiple information sources Serinağaoğlu Doğrusöz, Yeşim; MACLEOD, Robert (2006-10-01) The usual goal in inverse electrocardiography (ECG) is to reconstruct cardiac electrical sources from body surface potentials and a mathematical model that relates the sources to the measurements. Due to attenuation and smoothing that occurs in the thorax, the inverse ECG problem is ill-posed and imposition of a priori constraints is needed to combat this ill-posedness. When the problem is posed in terms of reconstructing heart surface potentials, solutions have not yet achieved clinical utility; limitation...
SOLVING THE INVERSE PROBLEM OF ELECTROCARDIOGRAPHY FOR SPONTANEOUS PVC LOCALIZATION: ANALYSIS OF CLINICAL ELECTROCARDIOGRAPHIC DATA Rasoolzadeh, Nika; Serinağaoğlu Doğrusöz, Yeşim; Department of Scientific Computing (2023-1-27) The inverse problem of electrocardiography refers to the determination of the electrical activity of the heart from the body surface potential measurements (BSPM). Knowledge of the electrical activity state of the heart can provide valuable insights for the diagnosis of cardiac disorders and aid in the facilitation of the development of appropriate treatments. Consequently, efficient resolution of this problem has the potential to be of significant benefit to clinical practices, making it imperative to cont...
Combination of conventional regularization methods and genetic algorithm for solving the inverse problem of electrocardiography Sarikaya, Sedat; Weber, Gerhard-Wilhelm; Serinağaoğlu Doğrusöz, Yeşim (2010-07-16) Distribution of electrical potentials over the surface of the heart, which is called the epicardial potential distribution, is a valuable tool to understand whether there is a defect in the heart. Direct measurement of these potentials requires highly invasive procedures. An alternative is to reconstruct these epicardial potentials non-invasively from the body surface potentials, which constitutes one form of the ill-posed inverse problem of electrocardiography (ECG). The goal of this study is to solve the ...
Lanczos bidiagonalization-based inverse solution methods applied to electrical imaging of the heart by using reduced lead-sets: A simulation study GHARBALCHİ, Fourough; Serinağaoğlu Doğrusöz, Yeşim; Weber, GERHARD WİLHELM (2016-01-01) In inverse problem of electrocardiography (ECG), electrical activity of the heart is estimated from body surface potential measurements. This electrical activity provides useful information about the state of the heart, thus it may help clinicians diagnose and treat heart diseases before they cause serious health problems. For practical application of the method, having fewer number of electrodes for data acquisition is an advantage. Additionally, inverse problem of ECG is ill-posed due to attenuation and s...

Citation Formats

Y. Serinağaoğlu Doğrusöz and A. M. Gavgani, “Genetic algorithm-based regularization parameter estimation for the inverse electrocardiography problem using multiple constraints,” MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, pp. 367–375, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/33331.