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dc.contributor.advisorRichard Cohen.en_US
dc.contributor.authorDosani, Adnan, 1982-en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2005-09-27T18:00:18Z
dc.date.available2005-09-27T18:00:18Z
dc.date.copyright2004en_US
dc.date.issued2004en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/28726
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.en_US
dc.descriptionIncludes bibliographical references (leaves 93-96).en_US
dc.description.abstractThe goal of our thesis was to investigate if P-wave and PQ segment alternans can be used to detect and predict Paroxysmal Atrial Fibrillation (PAF) from an Electrocardiogram (ECG). The work involved implementing an algorithm for computing alternans information for a region of ECG, applying the algorithm to derive P-wave and PQ segment alternans information, and analyzing data generated for normal and PAF ECGs for evidence of any distinguishable predictive characteristics. Based on analysis of total 80 patient records (35 normal and 45 PAF) with validation on 30 records randomly selected from those (achieving c-indexes between 0.66 and 0.70), we concluded that alternans can potentially be a useful predictor for PAF.en_US
dc.description.statementofresponsibilityby Adnan Dosani.en_US
dc.format.extent96 leavesen_US
dc.format.extent3876089 bytes
dc.format.extent3887201 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleExploring alternans characteristics of electrocardiogram for prediction of Paroxysmal Atrial Fibrillationen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc59554446en_US


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