Identifying ECG Clusters in Congenital Heart Disease

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dc.contributor.advisorRiviere, Beatrice M.en_US
dc.contributor.committeeMemberRusin, Craigen_US
dc.contributor.committeeMemberCox, Stevenen_US
dc.contributor.committeeMemberDabaghian, Yurien_US
dc.creatorHendryx, Emilyen_US
dc.date.accessioned2016-01-25T21:54:36Zen_US
dc.date.available2016-01-25T21:54:36Zen_US
dc.date.created2015-05en_US
dc.date.issued2015-04-23en_US
dc.date.submittedMay 2015en_US
dc.date.updated2016-01-25T21:54:36Zen_US
dc.description.abstractThis thesis presents a method of clustering ECG morphologies for the identification of individual ECG features in congenital heart disease. Clustering is performed on the computed heart dipole moment magnitude using k-medoids clustering with variants of dynamic time warping. The method is applied to both synthetic data and patient data with different parameter values for classic and derivative dynamic time warping. A deterministic k-medoids algorithm demonstrates poor clustering results on both data sets, but an iterative approach with random initialization shows marked improvement. The synthetic data clusters are generally well-defined with the expected number of clusters. Though the patient data derivative results are inconclusive, upon closer examination, the clustering results from classic dynamic time warping with a small warping window seem sensible. Through this project, the groundwork is laid for the future classification of ECG recordings and the development of predictive models in patients with congenital heart disease.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationHendryx, Emily. "Identifying ECG Clusters in Congenital Heart Disease." (2015) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/88126">https://hdl.handle.net/1911/88126</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/88126en_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.subjectTime series clusteringen_US
dc.subjectECGen_US
dc.subjectdynamic time warpingen_US
dc.subjectk-medoidsen_US
dc.titleIdentifying ECG Clusters in Congenital Heart Diseaseen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentComputational and Applied Mathematicsen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Artsen_US
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