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dc.contributor.advisorGeorge C. Verghese.en_US
dc.contributor.authorRenjifo, Carlos Aen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2006-07-13T15:17:21Z
dc.date.available2006-07-13T15:17:21Z
dc.date.copyright2005en_US
dc.date.issued2005en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/33350
dc.descriptionThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.en_US
dc.descriptionIncludes bibliographical references (p. 119-120).en_US
dc.description.abstractThis report studies physiological signals measured from patients in the Intensive Care Unit (ICU). The signals explored include heart rate, arterial blood pressure, pulmonary artery pressure, and central venous pressure measurements. Following an introduction to these signals, several methods are proposed for visualizing the data using time and frequency domain techniques. By way of a patient case study we motivate a novel method for data clustering based on the singular value decomposition and present some potential applications based on this method for use within the ICU setting.en_US
dc.description.statementofresponsibilityby Carlos A. Renjifo.en_US
dc.format.extent120 p.en_US
dc.format.extent5707859 bytes
dc.format.extent5712889 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoengen_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.titleExploration, processing and visualization of physiological signals from the ICUen_US
dc.typeThesisen_US
dc.description.degreeM.Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc62412698en_US


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