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POPULATION MODELING AND BAYESIAN ESTIMATION FOR THE
DECONVOLUTION OF BLOOD ALCOHOL CONCENTRATION FROM
TRANSDERMAL ALCOHOL BIOSENSOR DATA
by
Yuliya Piterbarg
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Ful llment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(APPLIED MATHEMATICS)
May 2009
Copyright 2009 Yuliya Piterbarg
Object Description
| Title | Population modeling and Bayesian estimation for the deconvolution of blood alcohol concentration from transdermal alcohol biosensor data |
| Author | Piterbarg, Yuliya |
| Author email | julia@piterbarg.com; jpiterbarg@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Applied Mathematics |
| School | College of Letters, Arts and Sciences |
| Date defended/completed | 2008-12-17 |
| Date submitted | 2009 |
| Restricted until | Unrestricted |
| Date published | 2009-02-06 |
| Advisor (committee chair) | Rosen, Gary |
| Advisor (committee member) |
Schumitzky, Alan D'Argenio, David |
| Abstract | We develop statistical methods to estimate blood alcohol concentration (BAC) from transdermal alcohol concentration (TAC) measurements supplied by a transdermal alcohol sensor (TAS). This eliminates the need for clinical test data for each patient to calibrate the underlying mathematical models to each subject and each device. We parametrically estimate the distribution for transport parameters in a transdermal ethanol model based on population analysis and simulated data using the Global Two-Stage Method (GTS). We implement the GTS method using generated data and clinical data obtained from 17 healthy volunteers with approximately the same body mass index assuming log-normal distributions for their skin model parameters. Next, we develop a Bayesian approach to estimate BAC for new patients from the population using TAS data generated by a full body alcohol model. The BAC signal is approximated by piecewise-constant (zero-order spline) functions. Prior distributions are assumed for skin model parameters (based on population analysis) and BAC spline coefficients. The new patient's TAS data is used to estimate BAC via maximization of a posterior distribution for skin parameters and input coefficients. This yields a maximum a-posteriori (MAP) estimate. With basic assumptions on the BAC spline coefficients and the TAS noise model, we obtain direct samples from the posterior distribution. This allows us to construct 95% confidence intervals (CI) for BAC. |
| Keyword | Bayesian deconvolution; population analysis; global two-stage method; blind deconvolution; alcohol transdermal sensor; blood alcohol concentration |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m1970 |
| Contributing entity | University of Southern California |
| Rights | Piterbarg, Yuliya |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@dots.usc.edu |
| Filename | etd-Piterbarg-2601 |
| Archival file | uscthesesreloadpub_Volume29/etd-Piterbarg-2601.pdf |
Description
| Title | Page 1 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@dots.usc.edu |
| Full text | POPULATION MODELING AND BAYESIAN ESTIMATION FOR THE DECONVOLUTION OF BLOOD ALCOHOL CONCENTRATION FROM TRANSDERMAL ALCOHOL BIOSENSOR DATA by Yuliya Piterbarg A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Ful llment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (APPLIED MATHEMATICS) May 2009 Copyright 2009 Yuliya Piterbarg |
