Kalman filter approach provides a natural way to include the spatio-temporal prior information in cardiac electrical imaging. This study focuses on the performance of Kalman filter approach with geometric errors present in inverse Electrocardiography (ECG) problem. The geometric errors considered here are the wrong determination of the heart's size and location. In addition to Kalman filtering, we also compare the performances of Tikhonov regularization and Bayesian MAP estimation when geometric errors are present. After presenting the effects of geometric errors on the solutions, a possible model to reduce the effects of the geometric errors in the inverse ECG problem for Bayes-MAP and Kalman solution is studied. To this purpose, a method that is suggested to overcome modeling errors in inverse problem solutions by Heino et. al. is modified and its effectiveness for inverse ECG problem is shown. Here the main idea is to assume geometric errors as additive noise and adding them to the covariance matrices used in the algorithms [1]. To the best of our knowledge, this is the first study in which it has been applied to the inverse problem of ECG.


Comparison of Bayesian MAP Estimation and Kalman Filter Methods in the Solution of Spatio-Temporal Inverse ECG Problem
Aydin, Umit; Serinağaoğlu Doğrusöz, Yeşim (2009-09-12)
In this study, spatial only, and spatio-temporal Bayesian Maximum a Posteriori (MAP) methods and an another spatio-temporal method, the Kalman filter approach, are used to solve the inverse electrocardiography (ECG) problem. Training sets are used to obtain the required a priori information for all methods. Two different approaches are employed to calculate the state transition matrix (STM), which maps the epicardial potentials in two consecutive time instants in the Kalman filter method. The first one uses...
Serinağaoğlu Doğrusöz, Yeşim (2009-07-01)
Kalman filter based solutions have been of particular interest in inverse problem of Electrocardiography (ECG) in recent years. One of the major problems with this approach however is the determination of the state transition matrix (STM) that relates the epicardial potentials at the current time instant to the potentials at the previous time instant. In this work, we use the solutions of Tikhonov regularization and Bayes-MAP algorithm to construct a STM, and we use these STMs in Kalman filtering. Our resul...
Analysis of magnetic resonance imaging in inhomogenous main magnetic field
Arpınar, Volkan Emre; Eyüboğlu, Behçet Murat; Department of Electrical and Electronics Engineering (2009)
In this study, analysis of Magnetic Resonance Imaging (MRI) in inhomogeneous main magnetic field is conducted. A numerical model based on Bloch equation is implemented for MRI, to understand effect of inhomogeneous magnetic field to Magnetic Resonance (MR) signal. Using the model, relations between inhomogeneity levels in main magnetic field with energy, decay time, bandwidth of the FID signal is investigated. Also relation between the magnetic field inhomogeneity and field of view is determined. To simulat...
Robust Attitude Estimation Using IMU-Only Measurements
Candan, Batu; Söken, Halil Ersin (2021-01-01)
© 1963-2012 IEEE.This article proposes two novel covariance-tuning methods to form a robust Kalman filter (RKF) algorithm for attitude (i.e., roll and pitch) estimation using the measurements of only an inertial measurement unit (IMU). KF-based and complementary filtering (CF)-based approaches are the two common methods for solving the attitude estimation problem. Efficiency and optimality of the KF-based attitude filters are correlated with appropriate tuning of the covariance matrices. Manual tuning proce...
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...
Citation Formats
U. Aydin and Y. Serinağaoğlu Doğrusöz, “STATISTICAL MODELING OF THE GEOMETRIC ERROR IN CARDIAC ELECTRICAL IMAGING,” 2009, Accessed: 00, 2020. [Online]. Available: