Theses and Dissertations from UMD

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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

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Author: search.filters.author.Lee, JongchanSubject: search.filters.subject.mathematical modeling

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    SUBJECT-SPECIFIC MULTICHANNEL BLIND SYSTEM IDENTIFICATION OF HUMAN ARTERIAL TREE VIA CUFF OSCILLATION MEASUREMENTS
    (2016) Lee, Jongchan; Hahn, Jin-Oh; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    We 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.