Detection of Cardiovascular Anomalies: An Observer-Based Approach

Handle URI:
http://hdl.handle.net/10754/235371
Title:
Detection of Cardiovascular Anomalies: An Observer-Based Approach
Authors:
Ledezma, Fernando
Abstract:
In this thesis, a methodology for the detection of anomalies in the cardiovascular system is presented. The cardiovascular system is one of the most fascinating and complex physiological systems. Nowadays, cardiovascular diseases constitute one of the most important causes of mortality in the world. For instance, an estimate of 17.3 million people died in 2008 from cardiovascular diseases. Therefore, many studies have been devoted to modeling the cardiovascular system in order to better understand its behavior and find new reliable diagnosis techniques. The lumped parameter model of the cardiovascular system proposed in [1] is restructured using a hybrid systems approach in order to include a discrete input vector that represents the influence of the mitral and aortic valves in the different phases of the cardiac cycle. Parting from this model, a Taylor expansion around the nominal values of a vector of parameters is conducted. This expansion serves as the foundation for a component fault detection process to detect changes in the physiological parameters of the cardiovascular system which could be associated with cardiovascular anomalies such as atherosclerosis, aneurysm, high blood pressure, etc. An Extended Kalman Filter is used in order to achieve a joint estimation of the state vector and the changes in the considered parameters. Finally, a bank of filters is, as in [2], used in order to detect the appearance of heart valve diseases, particularly stenosis and regurgitation. The first numerical results obtained are presented.
Advisors:
Laleg-Kirati, Taous-Meriem ( 0000-0001-5944-0121 )
Committee Member:
Alouini, Mohamed-Slim ( 0000-0003-4827-1793 ) ; Claudel, Christian G. ( 0000-0003-0702-6548 )
KAUST Department:
Physical Sciences and Engineering (PSE) Division
Program:
Mechanical Engineering
Issue Date:
Jul-2012
Type:
Thesis
Appears in Collections:
Theses; Physical Sciences and Engineering (PSE) Division; Mechanical Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.advisorLaleg-Kirati, Taous-Meriemen
dc.contributor.authorLedezma, Fernandoen
dc.date.accessioned2012-07-24T08:03:17Z-
dc.date.available2012-07-24T08:03:17Z-
dc.date.issued2012-07en
dc.identifier.urihttp://hdl.handle.net/10754/235371en
dc.description.abstractIn this thesis, a methodology for the detection of anomalies in the cardiovascular system is presented. The cardiovascular system is one of the most fascinating and complex physiological systems. Nowadays, cardiovascular diseases constitute one of the most important causes of mortality in the world. For instance, an estimate of 17.3 million people died in 2008 from cardiovascular diseases. Therefore, many studies have been devoted to modeling the cardiovascular system in order to better understand its behavior and find new reliable diagnosis techniques. The lumped parameter model of the cardiovascular system proposed in [1] is restructured using a hybrid systems approach in order to include a discrete input vector that represents the influence of the mitral and aortic valves in the different phases of the cardiac cycle. Parting from this model, a Taylor expansion around the nominal values of a vector of parameters is conducted. This expansion serves as the foundation for a component fault detection process to detect changes in the physiological parameters of the cardiovascular system which could be associated with cardiovascular anomalies such as atherosclerosis, aneurysm, high blood pressure, etc. An Extended Kalman Filter is used in order to achieve a joint estimation of the state vector and the changes in the considered parameters. Finally, a bank of filters is, as in [2], used in order to detect the appearance of heart valve diseases, particularly stenosis and regurgitation. The first numerical results obtained are presented.en
dc.language.isoenen
dc.subjectObserversen
dc.subjectHybrid systemen
dc.subjectFault detection and isolationen
dc.subjectCardiovascular systemen
dc.titleDetection of Cardiovascular Anomalies: An Observer-Based Approachen
dc.typeThesisen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
thesis.degree.grantorKing Abdullah University of Science and Technologyen_GB
dc.contributor.committeememberAlouini, Mohamed-Slimen
dc.contributor.committeememberClaudel, Christian G.en
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.nameMaster of Scienceen
dc.person.id113135en
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