Solution of inverse electrocardiography problem using minimum relative entropy method

Bircan, Ali
The interpretation of heart's electrical activity is very important in clinical medicine since contraction of cardiac muscles is initiated by the electrical activity of the heart. The electrocardiogram (ECG) is a diagnostic tool that measures and records the electrical activity of the heart. The conventional 12 lead ECG is a clinical tool that provides information about the heart status. However, it has limited information about functionality of heart due to limited number of recordings. A better alternative approach for understanding cardiac electrical activity is the incorporation of body surface potential measurements with torso geometry and the estimation of the equivalent cardiac sources. The problem of the estimating the cardiac sources from the torso potentials and the body geometry is called the inverse problem of electrocardiography. The aim of this thesis is reconstructing accurate high resolution maps of epicardial potential representing the electrical activity of the heart from the body surface measurements. However, accurate estimation of the epicardial potentials is not an easy problem due to ill-posed nature of the inverse problem. In this thesis, the linear inverse ECG problem is solved using different optimization techniques such as Conic Quadratic Programming, multiple constrained convex optimization, Linearly Constrained Tikhonov Regularization and Minimum Relative Entropy (MRE) method. The prior information used in MRE method is the lower and upper bounds of epicardial potentials and a prior expected value of epicardial potentials. The results are compared with Tikhonov Regularization and with the true potentials


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Mazloumi Gavgani, Alireza; Serinağaoğlu Doğrusöz, Yeşim; Department of Electrical and Electronics Engineering (2011)
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 ...
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The electrocardiogram (ECG) signals are basically the combination of sequential electrical impulses generated by tissues in the heart. In the last decades, by using ECG signals, various studies such as heart beat classification, arrhythmia analysis, anomaly detection, and diagnosis of heart-related diseases have been conducted with various neural network (NN), and machine learning (ML) approaches. Regardless of the approach to obtain more accurate results, various preprocessing methods are applied to data. ...
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Electric currents are applied to body in numerous applications in medicine such as electrical impedance tomography, cardiac defibrillation, electrocautery, and physiotherapy. If the magnetic field within a region is measured, the currents generating these fields can be calculated using the curl operator. In this study, magnetic fields generated within a phantom by currents passing through an external wire is measured using a magnetic resonance imaging (MRI) system, A pulse sequence that is originally design...
Solution of inverse problem of electrocardiography using state space models
Aydın, Ümit; Serinağaoğlu Doğrusöz, Yeşim; Department of Electrical and Electronics Engineering (2009)
Heart is a vital organ that pumps blood to whole body. Synchronous contraction of the heart muscles assures that the required blood flow is supplied to organs. But sometimes the synchrony between those muscles is distorted, which results in reduced cardiac output that might lead to severe diseases, and even death. The most common of heart diseases are myocardial infarction and arrhythmias. The contraction of heart muscles is controlled by the electrical activity of the heart, therefore determination of that...
Body surface lead reduction algorithm and its use in inverse problem of electrocardiography
Gharbalchi No, Fourough; Serinağaoğlu Doğrusöz, Yeşim; Department of Biomedical Engineering (2015)
Determining electrical activity of the heart in a non-invasive way is one of the main issues in electrocardiography (ECG). Although several cardiac abnormalities can be diagnosed by the standard 12-lead ECG, many others are not detectable by this fixed lead configuration. One alternative to compensate for the imperfection of standard 12-lead ECG in detecting many of the most informative signals is Body Surface Potential Mapping (BSPM), which measures ECG signals from a dense array of electrodes (32-256 elec...
Citation Formats
A. Bircan, “Solution of inverse electrocardiography problem using minimum relative entropy method,” M.S. - Master of Science, Middle East Technical University, 2010.