A Parameter Optimization to Solve the Inverse Problem in Electrocardiography
Langue
en
Communication dans un congrès
Ce document a été publié dans
Lecture Notes in Computer Science, Lecture Notes in Computer Science, FIMH 2017 - 9th International Conference on Functional Imaging and Modelling of the Heart, 2017-06-11, Toronto. 2017, vol. 10263, p. 219-229
Springer
Résumé en anglais
The main challenge of electrocardiography is to retrieve the best possible electrical information from body surface electrical potential maps. The most common methods reconstruct epicardial potentials. Here we propose a ...Lire la suite >
The main challenge of electrocardiography is to retrieve the best possible electrical information from body surface electrical potential maps. The most common methods reconstruct epicardial potentials. Here we propose a method based on a parameter identification problem to reconstruct both activation and repolarization times. The shape of an action potential (AP) is well known and can be described as a parameterized function. From the parameterized APs we compute the electrical potentials on the torso. The inverse problem is reduced to the identification of all the parameters. The method was tested on in silico and experimental data, for single ventricular pacing. We reconstructed activation and repolarization times with good accuracy accurate (CC between 0.71 and 0.9).< Réduire
Mots clés en anglais
inverse problem
ECGi
parameter optimization
Project ANR
L'Institut de Rythmologie et modélisation Cardiaque - ANR-10-IAHU-0004
Origine
Importé de halUnités de recherche