Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Use of genetic algorithm for selection of regularization parameters in multiple constraint inverse ECG problem
Download
index.pdf
Date
2011
Author
Mazloumi Gavgani, Alireza
Metadata
Show full item record
Item Usage Stats
265
views
234
downloads
Cite This
The main goal in inverse and forward problems of electrocardiography (ECG) is to better understand the electrical activity of the heart. In the forward problem of ECG, one obtains the body surface potential (BSP) distribution (i.e., the measurements) when the electrical sources in the heart are assumed to be known. The result is a mathematical model that relates the sources to the measurements. In the inverse problem of ECG, the unknown cardiac electrical sources are estimated from the BSP measurements and the mathematical model of the torso. Inverse problem of ECG is an ill-posed problem, and regularization should be applied in order to obtain a good solution. Tikhonov regularization is a well-known method, which introduces a trade-off between how well the solution fits the measurements and how well the constraints on the solution are satisfied. This trade-off is controlled by a regularization parameter, which can be easily calculated by the L-curve method. It is theoretically possible to include more than one constraint in the cost function; however finding more than one regularization parameter to use with each constraint is a challenging problem. It is the aim of this thesis to use genetic algorithm (GA) optimization method to obtain regularization parameters to solve the inverse ECG problem when multiple constraints are used for regularization. The results are presented when there are two spatial constraints, when there is one spatial, one temporal constraint, and when there are two spatial one temporal constraints; the performances of these three applications are compared to Tikhonov regularization results and to each other. As a conlcusion, it is possible to obtain correct regularization parameters using the GA method, and using more than one constraints yields improvements in the results.
Subject Keywords
Electrocardiography.
,
Electrical and Electronics Engineering.
URI
http://etd.lib.metu.edu.tr/upload/12612984/index.pdf
https://hdl.handle.net/11511/20450
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
Evaluation of multivariate adaptive non-parametric reduced-order model for solving the inverse electrocardiography problem: a simulation study
Onak, Onder Nazim; Serinağaoğlu Doğrusöz, Yeşim; Weber, Gerhard Wilhelm (Springer Science and Business Media LLC, 2019-05-01)
In the inverse electrocardiography (ECG) problem, the goal is to reconstruct the heart's electrical activity from multichannel body surface potentials and a mathematical model of the torso. Over the years, researchers have employed various approaches to solve this ill-posed problem including regularization, optimization, and statistical estimation. It is still a topic of interest especially for researchers and clinicians whose goal is to adopt this technique in clinical applications. Among the wide range of...
Comparison of ML and MAP parameter estimation techniques for the solution of inverse electrocardiography problem
Erenler, Taha; Serinağaoğlu Doğrusöz, Yeşim; Department of Electrical and Electronics Engineering (2018)
This study aims to determine the cardiac electrical activity from body surface potential measurements. This problem is called the inverse problem of electrocardiography. Reconstruction of the cardiac electrical activity from the body surface potential measurements is not an easy task, since this problem has an ill-posed nature due to attenuation and spatial smoothing inside the medium between the source and the measurement sites, meaning that even small errors in the mathematical model or noise in the measu...
Use of Activation Time Based Kalman Filtering in Inverse Problem of Electrocardiography
Aydin, Umit; Serinağaoğlu Doğrusöz, Yeşim (2008-11-27)
The goal of this study is to solve inverse problem of electrocardiography (ECG) in terms of epicardial potentials using body surface (torso) potential measurements. The problem is ill-posed and regularization must be applied. Kalman filter is one of the regularization approaches, which includes both spatial and temporal correlations of epicardial potentials. However, in order to use the Kalman filter, one needs the state transition matrix (STM) that models the time evolution of the epicardial potentials. In...
Evaulation of spatial and spatio-temporal regularization approaches in inverse problem of electrocardiography
Önal, Murat; Serinağaoğlu Doğrusöz, Yeşim; Department of Electrical and Electronics Engineering (2008)
Conventional electrocardiography (ECG) is an essential tool for investigating cardiac disorders such as arrhythmias or myocardial infarction. It consists of interpretation of potentials recorded at the body surface that occur due to the electrical activity of the heart. However, electrical signals originated at the heart suffer from attenuation and smoothing within the thorax, therefore ECG signal measured on the body surface lacks some important details. The goal of forward and inverse ECG problems is to r...
Forward problem of electrocardiography in terms of 3D transmembrane potentials using COMSOL
Bedir, Gizem; Serinağaoğlu Doğrusöz, Yeşim; Çetin, Barbaros; Department of Biomedical Engineering (2015)
Computation of body surface potentials from equivalent cardiac sources is called as forward problem of electrocardiography (ECG). There exist different solution meth- ods for solving the forward ECG problem. These solution methods depend on the choice of the equivalent cardiac sources. In this study, bidomain model based trans- membrane potential (TMP) distribution is used as equivalent cardiac source to exam- ine the cellular electrophysiology macroscopically. With this type of source defini- tion, the TMP...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
A. Mazloumi Gavgani, “Use of genetic algorithm for selection of regularization parameters in multiple constraint inverse ECG problem,” M.S. - Master of Science, Middle East Technical University, 2011.
