Adaptive regularization based on noise estimation and its application to the inverse problem in electrocardiography

Simple item page
dc.contributor.advisorClark, John W., Jr.en_US
dc.creatorZhang, Fulongen_US
dc.date.accessioned2009-06-04T08:29:36Zen_US
dc.date.available2009-06-04T08:29:36Zen_US
dc.date.issued1998en_US
dc.description.abstractThe inverse problem was solved to reconstruct endocardial electrograms from cavitary electrograms measured with a noncontact multielectrode probe. Noise levels were estimated at each time instant by extrapolating noise energy from high spatial frequency components of probe potentials. Based on estimated noise and energy distribution of probe potentials, a matrix of weighting factors was derived to inversely mimic the band shape of the energy spectrum. By incorporating those weighting factors into the inverse procedure, a set of regularization parameters was derived and applied in solving the inverse problem (i.e. adaptive regularization). Adaptive regularization was tested on an experimental canine model. Both traditional uniform regularization and adaptive regularization were applied to compute endocardial electrograms during normal as well as paced rhythms. Adaptive regularization demonstrated a great improvement over uniform regularization in terms of improved correlation coefficients, reduced relative error, better estimation of activation times and localization of pacing sites.en_US
dc.format.extent92 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoTHESIS E.E. 1998 ZHANG, F.en_US
dc.identifier.citationZhang, Fulong. "Adaptive regularization based on noise estimation and its application to the inverse problem in electrocardiography." (1998) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/17227">https://hdl.handle.net/1911/17227</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/17227en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectBiomedical engineeringen_US
dc.subjectElectronicsen_US
dc.subjectElectrical engineeringen_US
dc.titleAdaptive regularization based on noise estimation and its application to the inverse problem in electrocardiographyen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentElectrical Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
1389138.PDF
Size:
2.99 MB
Format:
Adobe Portable Document Format
Download
Collections
Rice University Theses and Dissertations