Linked Life Data

19535314

Source:http://linkedlifedata.com/resource/pubmed/id/19535314

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2010-1-21
pubmed:abstractText
Successful employment of numerical techniques for the solution of forward and inverse ECG problems requires the ability to both quantify and minimize approximation errors introduced as part of the discretization process. Our objective is to develop discretization and refinement strategies involving hybrid-shaped finite elements so as to minimize approximation errors for the ECG inverse problem. We examine both the ill-posedness of the mathematical inverse problem and the ill-conditioning of the discretized system in order to propose strategies specifically designed for the ECG inverse problem. We demonstrate that previous discretization and approximation strategies may worsen the properties of the inverse problem approximation. We then demonstrate the efficacy of our strategies on both a simplified and a realistic 2-D torso model.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1558-2531
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
57
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
220-37
pubmed:dateRevised
2010-9-27
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Resolution strategies for the finite-element-based solution of the ECG inverse problem.
pubmed:affiliation
Computing and Imaging (SCI) Institute and the School of Computing, University of Utah, Salt Lake City, UT 84112, USA. dfwang@sci.utah.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, N.I.H., Extramural