How accurately can the method of fundamental solutions solve the inverse problem of electrocardiology?

View/ Open
File version
Accepted Manuscript (AM)
Author(s)
Johnston, Peter R
Griffith University Author(s)
Year published
2017
Metadata
Show full item recordAbstract
This study presents a detailed comparison between the
Method of Fundamental Solutions (MFS) approach to
solving the inverse problem of electrocardiology and a
more conventional boundary element method (BEM) approach.
Synthetic data were created to simulate the heart surface
potential distribution during the time course of normal
and ectopic heart beats. Both measurement and geometry
noise were added to the data and the inverse problem
was solved via both methods. Under these conditions several
regularisation parameter determination methods were
compared, with the Robust Generalised Cross-Validation
(RGCV) method consistently ...
View more >This study presents a detailed comparison between the Method of Fundamental Solutions (MFS) approach to solving the inverse problem of electrocardiology and a more conventional boundary element method (BEM) approach. Synthetic data were created to simulate the heart surface potential distribution during the time course of normal and ectopic heart beats. Both measurement and geometry noise were added to the data and the inverse problem was solved via both methods. Under these conditions several regularisation parameter determination methods were compared, with the Robust Generalised Cross-Validation (RGCV) method consistently performing better than any other method for both MFS and BEM approaches. The MFS approach to solving the inverse problem of electrocardiology can sometimes yield more accurate results than the BEM approach, especially when the regularisation parameter is determined by RGCV, but BEM is generally superior.
View less >
View more >This study presents a detailed comparison between the Method of Fundamental Solutions (MFS) approach to solving the inverse problem of electrocardiology and a more conventional boundary element method (BEM) approach. Synthetic data were created to simulate the heart surface potential distribution during the time course of normal and ectopic heart beats. Both measurement and geometry noise were added to the data and the inverse problem was solved via both methods. Under these conditions several regularisation parameter determination methods were compared, with the Robust Generalised Cross-Validation (RGCV) method consistently performing better than any other method for both MFS and BEM approaches. The MFS approach to solving the inverse problem of electrocardiology can sometimes yield more accurate results than the BEM approach, especially when the regularisation parameter is determined by RGCV, but BEM is generally superior.
View less >
Conference Title
2017 COMPUTING IN CARDIOLOGY (CINC)
Volume
44
Copyright Statement
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Subject
Biological mathematics