The effects of geometric errors on inverse ECG solutions using Kalman filter and Bayesian MAP estimation Kalman filtre ve Bayes-MAP ile ters EKG çözümlerinde geometrik hatalarin etkisi

Geometric errors in inverse ECG are usually the errors occur in the mathematical model used for solution due to wrong interpretation of heart's position and size, conductivities of organs in the model and electrode positions. In this study the effects of geometric errors in inverse ECG problem for Kalman filter and Bayes-AMP methods are studied Furthermore the method suggested by Kaipio et. al., which assumes that these geometric errors are additive noise and independent of the epicardial potentials, is implemented. With this method, the effects of geometric errors on Kalman filter and Bayes-MAP solutions are reduced al the cost of smoothing the wavefront.
14th National Biomedical Engineering Meeting


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In this article, we aimed to reduce the effects of geometric errors and measurement noise on the inverse problem of Electrocardiography (ECG) solutions. We used the Kalman filter to solve the inverse problem in terms of epicardial potential distributions. The geometric errors were introduced into the problem via wrong determination of the size and location of the heart in simulations. An error model, which is called the enhanced error model (EEM), was modified to be used in inverse problem of ECG to compens...
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Citation Formats
Ü. Aydin and Y. Serinağaoğlu Doğrusöz, “The effects of geometric errors on inverse ECG solutions using Kalman filter and Bayesian MAP estimation Kalman filtre ve Bayes-MAP ile ters EKG çözümlerinde geometrik hatalarin etkisi,” presented at the 14th National Biomedical Engineering Meeting, Izmir, TURKEY, 2009, Accessed: 00, 2020. [Online]. Available: