Comparison of Bayesian MAP Estimation and Kalman Filter Methods in the Solution of Spatio-Temporal Inverse ECG Problem

Date

2009-09-12

Author

Aydin, Umit
Serinağaoğlu Doğrusöz, Yeşim

Metadata

Show full item record

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

Item Usage Stats

218
views

0
downloads

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 the training set itself to iteratively estimate the STM, and the second one uses the candidate solution obtained using the spatial only Bayesian MAP estimate. The results are quantitatively compared using the correlation coefficient, the relative difference measurement star, the computation time measures, and qualitatively compared using spatial and temporal displays of epicardial potentials.

Subject Keywords

Bayesian MAP, Kalman filter, Spatio-temporal methods, Inverse ECG

URI

https://hdl.handle.net/11511/53497

Conference Name

11th International Congress of the IUPESM/World Congress on Medical Physics and Biomedical Engineering

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

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...
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 ...
IMAGING THE ELECTRICAL ACTIVITY OF THE HEART USING A KALMAN FILTER BASED APPROACH: COMPARISON OF RESULTS USING DIFFERENT STM'S 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...
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 ...
Comparison of method of lines and finite difference solutions of 2-D Navier-Stokes equations for transient laminar pipe flow Selçuk, Nevin; Tanrikulu, S (2002-03-10) Performances of method of lines (MOL) and finite difference method (FDM) were tested from the viewpoints of solution accuracy and central processing unit (CPU) time by applying them to the solution of time-dependent 2-D Navier-Stokes equations for transient laminar flow without/with sudden expansion and comparing their results with steady-state numerical predictions and measurements previously reported in the literature. Predictions of both methods were obtained on the same computer by using the same order ...

Citation Formats

U. Aydin and Y. Serinağaoğlu Doğrusöz, “Comparison of Bayesian MAP Estimation and Kalman Filter Methods in the Solution of Spatio-Temporal Inverse ECG Problem,” Munich, GERMANY, 2009, vol. 25, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53497.