SUBJECT-SPECIFIC MULTICHANNEL BLIND SYSTEM IDENTIFICATION OF HUMAN ARTERIAL TREE VIA CUFF OSCILLATION MEASUREMENTS

dc.contributor.advisorHahn, Jin-Ohen_US
dc.contributor.authorLee, Jongchanen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2017-01-25T06:40:49Z
dc.date.available2017-01-25T06:40:49Z
dc.date.issued2016en_US
dc.description.abstractWe developed and evaluated a mathematical model-based method to monitor cardiovascular health and estimate risk predictors from two peripheral cuff oscillation measurements. The model structure was established by studying tube-load models individually augmented with a gain, Voigt model, and standard linear solid model to best capture the relationship between carotid tonometry and cuff waveforms at the upper arm and ankle. The arm-cuff interface was better modeled with increasing viscoelasticity but not as much for the ankle-cuff interface. Next, model-estimated ankle blood pressure waveforms were used to formulate a matrix equation for estimating wave reflection. Subsequently derived risk predictors were adequately correlated with those from reference methods. Finally, subject-specific central blood pressure waveforms were estimated from two cuff oscillation signals via multichannel blind system identification. The model estimated central arterial blood pressure waveforms with good accuracy with a median RMSE of 3.08 mmHg and IQR of 1.71 mmHg.en_US
dc.identifierhttps://doi.org/10.13016/M26J9F
dc.identifier.urihttp://hdl.handle.net/1903/19097
dc.language.isoenen_US
dc.subject.pqcontrolledBiomedical engineeringen_US
dc.subject.pqcontrolledMechanical engineeringen_US
dc.subject.pqcontrolledBiomechanicsen_US
dc.subject.pquncontrolledarterial blood pressureen_US
dc.subject.pquncontrolledarterial treeen_US
dc.subject.pquncontrolledmathematical modelingen_US
dc.subject.pquncontrolledpulse volume waveformen_US
dc.subject.pquncontrolledtransfer functionen_US
dc.subject.pquncontrolledviscoelastic modelen_US
dc.titleSUBJECT-SPECIFIC MULTICHANNEL BLIND SYSTEM IDENTIFICATION OF HUMAN ARTERIAL TREE VIA CUFF OSCILLATION MEASUREMENTSen_US
dc.typeThesisen_US

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