DocumentCode :
1102826
Title :
A generalized eigensystem approach to the inverse problem of electrocardiography
Author :
Throne, Robert D. ; Olson, Lorraine G.
Author_Institution :
Dept. of Electr. Eng., Nebraska Univ., Lincoln, NE, USA
Volume :
41
Issue :
6
fYear :
1994
fDate :
6/1/1994 12:00:00 AM
Firstpage :
592
Lastpage :
600
Abstract :
The authors develop a new approach to the ill-conditioned inverse problem of electrocardiography which employs finite element techniques to generate a truncated eigenvector expansion to stabilize the inversion. Ordinary three-dimensional isoparametric finite elements are used to generate the conductivity matrix for the body. The authors introduce a related eigenproblem, for which a special two-dimensional isoparametric area matrix is used, and solve for the lowest eigenvalues and eigenvectors. The body surface potentials are expanded in terms, of the eigenvectors, and a least squares fit to the measured body surface potentials is used to determine the coefficients of the expansion. This expansion is then used directly to determine the potentials on the surface of the heart. The number of measurement points on the surface of the body can be less than the number of finite element nodes on the body surface, and the number of modes employed in the expansion can be adjusted to reduce errors due to noise.
Keywords :
electrocardiography; finite element analysis; inverse problems; medical signal processing; 2D isoparametric area matrix; body conductivity matrix; body surface potentials; electrocardiography inverse problem; expansion coefficients; finite element nodes; generalized eigensystem approach; heart surface potentials; least squares fit; measurement points number; noise-induced errors reduction; Conductivity; Eigenvalues and eigenfunctions; Electrocardiography; Finite element methods; Heart; Inverse problems; Least squares methods; Noise measurement; Noise reduction; Surface fitting; Action Potentials; Algorithms; Artifacts; Bias (Epidemiology); Body Surface Area; Electric Conductivity; Electrocardiography; Factor Analysis, Statistical; Humans; Least-Squares Analysis; Models, Cardiovascular; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.293247
Filename :
293247
Link To Document :
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