Using machine learning for real-time BAC estimation from a new-generation transdermal biosensor in the laboratory.

Journal: Drug and alcohol dependence
Published Date:

Abstract

BACKGROUND: Transdermal biosensors offer a noninvasive, low-cost technology for the assessment of alcohol consumption with broad potential applications in addiction science. Older-generation transdermal devices feature bulky designs and sparse sampling intervals, limiting potential applications for transdermal technology. Recently a new-generation of transdermal device has become available, featuring smartphone connectivity, compact designs, and rapid sampling. Here we present initial laboratory research examining the validity of a new-generation transdermal sensor prototype.

Authors

  • Catharine E Fairbairn
    Department of Psychology, University of Illinois-Urbana-Champaign, 603 East Daniel Street, Champaign, IL, 61820, USA. Electronic address: cfairbai@illinois.edu.
  • Dahyeon Kang
    Department of Psychology, University of Illinois-Urbana-Champaign, 603 East Daniel Street, Champaign, IL, 61820, USA.
  • Nigel Bosch
    School of Information Sciences and Department of Educational Psychology University of Illinois Urbana-Champaign.