Deconvolving an estimate of breath measured blood alcohol concentration from biosensor collected transdermal ethanol data
Open accessAbstract
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.
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BrAC instruments calculate BAC by following Henry's law, but may compromise accuracy because results can be easily affected by humidity, temperature, and individual traits.
“BrAC instruments calculate BAC by following Henry's law, but may compromise accuracy since the results can be easily affected by humidity, temperature, and individual traits.7,8”
From Noninvasive Alcohol Monitoring Using a Wearable Tattoo-Based Iontophoretic-Biosensing System (2016) · cites this paper as [8]
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Noninvasive Alcohol Monitoring Using a Wearable Tattoo-Based Iontophoretic-Biosensing System
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- Authors
- Dumett, M. A., Rosen, I. G., Sabat, J., Shaman, A., Tempelman, L., Wang, C., & Swift, R. M.
- Affiliations
- University of Southern California (US)
- Giner (United States) (US)
- Brown University (US)
- Corresponding author
- Dumett, M.A.
- Venue
- Applied Mathematics and Computation
- Publisher
- Elsevier BV
- Published
- 2008-03
- Volume
- 196
- Issue
- 2
- Pages
- 724-743
- ISSN
- 0096-3003 (ISSN-L)
- PMC
- PMC2597868
- OpenAlex
- W1988263497
- Cited by
- 53
- References
- 28
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 3 · 2022: 7 · 2021: 2 · 2020: 3 · 2019: 3 · 2018: 11 · 2017: 4 · 2016: 3 · 2015: 2 · 2014: 4 · 2013: 2 · 2012: 2
- FWCI
- 1.35
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Applied Mathematics and Computation (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Alcohol Abuse and Alcoholism (N01AA33002)
- National Institutes of Health
- Topics
- Physical Sciences › Mathematics › Mathematical Physics › Numerical methods in inverse problems
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- blood alcohol concentration, distributed parameter model, nonlinear least squares, steepest descent optimization, adjoint method, inverse problems
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