Deconvolving an estimate of breath measured blood alcohol concentration from biosensor collected transdermal ethanol data

Abstract

Biosensor measurement of transdermal alcohol oncentration in perspiration exhibits significant variance from subject to subject and device to device. Short duration data collected in a controlled clinical setting is used to calibrate a forward model for ethanol transport from the blood to the sensor. The calibrated model is then used to invert transdermal signals collected in the field (short or long duration) to obtain an estimate for breath measured blood alcohol concentration. A distributed parameter model for the forward transport of ethanol from the blood through the skin and its processing by the sensor is developed. Model calibration is formulated as a nonlinear least squares fit to data. The fit model is then used as part of a spline based scheme in the form of a regularized, non-negatively constrained linear deconvolution. Fully discrete, steepest descent based schemes for solving the resulting optimization problems are developed. The adjoint method is used to accurately and efficiently compute requisite gradients. Efficacy is demonstrated on subject field data.

Estimating BrAC from Transdermal Alcohol Concentration Data Using the BrAC Estimator Software Program

“…The BrAC Estimator software program is based upon a mathematically sophisticated first principles forward model for the transport of alcohol from the blood through the skin to the TAS sensor and its oxidation by the TAS sensor (see Dumett et al, 2008; Rosen et al, 2013; in press, for details on the mathematical models). Unlike a breath analyzer, which relies on a relatively simple model from elementary chemistry (i.e.…”

“…Until now, however, these TAS devices have been used almost exclusively as abstinence monitors (see Marques and McKnight, 2009; Sakai et al, 2006). This is primarily for two reasons: first, the alcohol community, which has traditionally relied upon blood alcohol concentration (BAC) and breath alcohol concentration (BrAC) as the standard quantitative indices of intoxication, has no experience in, or benchmarks for, interpreting or analyzing the transdermal alcohol concentration (TAC) data that TAS devices produce; and second, evidence has shown that, unlike the breath analyzer, there is significant variation from individual to individual and device to device when correlating TAC with BAC or BrAC (Dumett et al, 2008). …”

Innovation in biotechnology: moving from academic research to product development—the case of biosensors

“…For example, the alcohol wristwatch has been developed through collaboration between the University of Southern California and the Brown University Medical School, based on the simulation of alcohol metabolism (Dumett et al, 2008), that will produced by Giner Inc., USA.…”

Using drinking data and pharmacokinetic modeling to calibrate transport model and blind deconvolution based data analysis software for transdermal alcohol biosensors

“…In earlier work [12, 28, 29, 37, 38], we have considered the problem of estimating BAC or BrAC from biosensor measurements of TAC based on the following general approach. We developed, analyzed, and made use of first principle mathematical models to create associated MATLAB software that converts TAC data into either BAC or BrAC estimates, depending on which kind of data was used to calibrate the models.…”

“…Once an estimated BAC/BrAC curve has been obtained in this way, the software then produces estimates for three statistics that are of primary interest to alcohol researchers and clinicians: peak BAC/BrAC, time of peak BAC/BrAC, and area under the BAC/BrAC curve, along with the (essentially) continuous BAC /BrAC profile for the entire drinking episode. We first laid out this general approach in [12] and demonstrated the efficacy of our method on data collected in a clinical or laboratory setting. In [28] we reported on the development of a real-time assessment protocol that used a web application and a TAC sensor together with our BAC/BrAC estimator to assess changes in BrAC, alcohol responses, behaviors, and contexts over the course of a drinking event in thirty-two college students based on calibration data collected in a laboratory drinking session followed by a 2-week field trial.…”