IMAGING THE ELECTRICAL ACTIVITY OF THE HEART USING A KALMAN FILTER BASED APPROACH: COMPARISON OF RESULTS USING DIFFERENT STM'S

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 results indicate that the Kalman filter that uses a STM obtained from Bayes-MAP solutions produces accurate solutions.
IEEE International Symposium on Biomedical Imaging - From Nano to Macro

Suggestions

STATISTICAL MODELING OF THE GEOMETRIC ERROR IN CARDIAC ELECTRICAL IMAGING
Aydin, Umit; Serinağaoğlu Doğrusöz, Yeşim (2009-07-01)
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 ...
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...
Estimation of state transition matrix in the Kalman filter based inverse ECG solution with the help of training sets Ters EKG probleminin Kalman filtre ile çözümünde durum geçiş matrisinin eǧitici kümeler yardimi ile kestirimi
Aydin, Ümit; Serinağaoğlu Doğrusöz, Yeşim (2009-10-27)
At this study the main motivation is to solve inverse problem of ECG with Kalman filter. In order to obtain feasible solutions determination of the state transition matrix (STM) correctly is vital. In literature the STM is usually found by using the test data itself which is not a realistic scenario. The major goal of this study is to determine STM without using test data. For that purpose a two stage method is suggested. At the first step the probability density function (pdf) is calculated using training ...
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...
Comparison of Kalman filter and Bayesian-MAP approaches in the spatio-temporal solution of the inverse electrocardiography Ters elektrokardiyografinin zaman-uzamsal çözümünde Kalman filtre ve Bayes-MAP yöntemlerinin karşilaştirilmasi
Aydin, Ümit; Serinağaoğlu Doğrusöz, Yeşim (2010-07-15)
In this study some of the spatial and spatio-temporal methods for the solution of the inverse problem of electrocardiography (ECG) are compared with each other. Comparisons are also made for the cases with geometric errors, where the location of the heart is shifted for 10mm and the size of the heart is reduced by 5%. The compared methods are the Kalman filter and Bayesian maximum a posteriori estimation (MAP). Two different Bayesian-MAP algorithms are used. While one uses only spatial information the other...
Citation Formats
Y. Serinağaoğlu Doğrusöz, “IMAGING THE ELECTRICAL ACTIVITY OF THE HEART USING A KALMAN FILTER BASED APPROACH: COMPARISON OF RESULTS USING DIFFERENT STM’S,” presented at the IEEE International Symposium on Biomedical Imaging - From Nano to Macro, Boston, MA, 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38490.