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Activity Number: 187 - Contributed Poster Presentations: Section on Nonparametric Statistics
Type: Contributed
Date/Time: Monday, July 29, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract #304598
Title: Nonparametric Estimation of Blood Alcohol Concentration from Transdermal Alcohol Measurements Using Alcohol Biosensor Devices
Author(s): Bryan Vader* and Alona Kryshchenko and Melike Sirlanci
Companies: CSU Channel Islands and CSU Channel Islands and California Technical University
Keywords: Nonparametric; Estimation; Stochastic; Maximum Likelihood; Modeling; Differential Equation

Alcohol biosensor devices have the prospect to positively impact medicine and law enforcement by giving a noninvasive method to acquire continuous alcohol readings. We propose to develop a nonparametric estimation algorithm that estimates the joint distribution of the parameters of the model which are assumed to be random due to natural irregularity in an individual’s body conditions and the variability of population data. This is superior to parametric estimation methods since it can capture unusual fluctuations of a subject's condition as well as environmental factors. This will help to ascertain a precise relation between blood alcohol concentration and transdermal alcohol concentration. We are using a stochastic differential equation model to estimate the diffusion of alcohol through transdermal layers using a nonparametric maximum likelihood approach while taking into account noise in the data.

Authors who are presenting talks have a * after their name.

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