Remote sensing of alcohol consumption using machine learning speckle pattern analysis.

Journal: Journal of biomedical optics
PMID: 40041370

Abstract

SIGNIFICANCE: Alcohol consumption monitoring is essential for forensic and healthcare applications. While breath and blood alcohol concentration sensors are currently the most common methods, there is a growing need for faster, non-invasive, and more efficient assessment techniques. The rationale for our binary classification relates to law enforcement applications in countries with strict limits on alcohol consumption such as China, which seeks to prevent driving with even the smallest amount of alcohol in the bloodstream.

Authors

  • Doron Duadi
    Bar Ilan University, Faculty of Engineering and Nanotechnology Center, Ramat Gan, Israel.
  • Avraham Yosovich
    Bar Ilan University, Faculty of Engineering and Nanotechnology Center, Ramat Gan, Israel.
  • Marianna Beiderman
    Ruppin Academic Center, Faculty of Engineering, Kfar Monash, Israel.
  • Sergey Agdarov
    Bar-Ilan University, Faculty of Engineering, Ramat Gan, Israel.
  • Nisan Ozana
    Bar Ilan University, Faculty of Engineering and Nanotechnology Center, Ramat Gan, Israel.
  • Yevgeny Beiderman
    Bar-Ilan University, Faculty of Engineering, Nanotechnology Center, Ramat-Gan, Israel.
  • Zeev Zalevsky
    Faculty of Engineering and the Nano-Technology Center, Bar-Ilan University, Ramat Gan, 52900 Israel.

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