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dc.contributor.authorClifford, Gari D.
dc.contributor.authorSameni, Reza
dc.contributor.authorJutten, Christian
dc.contributor.authorShamsollahi, Mohammad B.
dc.date.accessioned2011-11-30T22:40:51Z
dc.date.available2011-11-30T22:40:51Z
dc.date.issued2007-01
dc.date.submitted2006-11
dc.identifier.issn1687-0433
dc.identifier.issn1110-8657
dc.identifier.urihttp://hdl.handle.net/1721.1/67338
dc.description.abstractA three-dimensional dynamic model of the electrical activity of the heart is presented. The model is based on the single dipole model of the heart and is later related to the body surface potentials through a linear model which accounts for the temporal movements and rotations of the cardiac dipole, together with a realistic ECG noise model. The proposed model is also generalized to maternal and fetal ECG mixtures recorded from the abdomen of pregnant women in single and multiple pregnancies. The applicability of the model for the evaluation of signal processing algorithms is illustrated using independent component analysis. Considering the difficulties and limitations of recording long-term ECG data, especially from pregnant women, the model described in this paper may serve as an effective means of simulation and analysis of a wide range of ECGs, including adults and fetuses.en_US
dc.description.sponsorshipIranian-French Scientific Cooperation Programen_US
dc.description.sponsorshipIran Telecommunication Research Centeren_US
dc.description.sponsorshipNational Institute of Biomedical Imaging and Bioengineering (U.S.) (Grant no. R01 EB001659)en_US
dc.publisherHindawi Publishing Corporationen_US
dc.relation.isversionofhttp://dx.doi.org/10.1155/2007/43407en_US
dc.titleMultichannel ECG and Noise Modeling: Application to Maternal and Fetal ECG Signalsen_US
dc.typeArticleen_US
dc.identifier.citationSameni, Reza et al. “Multichannel ECG and Noise Modeling: Application to Maternal and Fetal ECG Signals.” EURASIP Journal on Advances in Signal Processing 2007 (2007): 043407. Web. 30 Nov. 2011. © 2007 Reza Sameni et al.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.departmentHarvard--MIT Program in Health Sciences and Technology. Laboratory for Computational Physiologyen_US
dc.contributor.approverClifford, Gari D.
dc.contributor.mitauthorClifford, Gari D.
dc.relation.journalEURASIP Journal on Applied Signal Processingen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2011-11-15T12:24:10Z
dc.language.rfc3066en
dc.rights.holderet al.; licensee BioMed Central Ltd.
dspace.orderedauthorsSameni, Reza; Clifford, Gari D; Jutten, Christian; Shamsollahi, Mohammad Ben
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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