Li J, Luczak SE, Rosen IG. Comparing a Distributed Parameter Model-Based System Identification Technique with More Conventional Methods for Inverse Problems.
J Inverse Ill Posed Probl 2019;
27:703-717. [PMID:
31885419 PMCID:
PMC6934369 DOI:
10.1515/jiip-2018-0006]
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Abstract
Three methods for the estimation of blood or breath alcohol concentration (BAC/BrAC) from biosensor measured transdermal alcohol concentration (TAC) are evaluated and compared. Specifically, we consider a system identification/quasi-blind deconvolution scheme based on a distributed parameter model with unbounded input and output for ethanol transport in the skin and compare it to two more conventional system identification and filtering/deconvolution techniques for ill-posed inverse problems, one based on frequency domain methods, and the other on a time series approach using an ARMA input/output model. Our basis for comparison are five statistical measures of interest to alcohol researchers and clinicians: peak BAC/BrAC, time of peak BAC/BrAC, the ascending and descending slopes of the BAC/BrAC curve, and the area underneath the BAC/BrAC curve.
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