S-ADL: Exploring Smartphone-based Activities of Daily Living to Detect Blood Alcohol Concentration in a Controlled Environment

Hansoo Lee, Auk Kim, Sang Won Bae, Uichin Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In public health and safety, precise detection of blood alcohol concentration (BAC) plays a critical role in implementing responsive interventions that can save lives. While previous research has primarily focused on computer-based or neuropsychological tests for BAC identification, the potential use of daily smartphone activities for BAC detection in real-life scenarios remains largely unexplored. Drawing inspiration from Instrumental Activities of Daily Living (I-ADL), our hypothesis suggests that Smartphone-based Activities of Daily Living (S-ADL) can serve as a viable method for identifying BAC. In our proof-of-concept study, we propose, design, and assess the feasibility of using S-ADLs to detect BAC in a scenario-based controlled laboratory experiment involving 40 young adults. In this study, we identify key S-ADL metrics, such as delayed texting in SMS, site searching, and finance management, that significantly contribute to BAC detection (with an AUC-ROC and accuracy of 81%). We further discuss potential real-life applications of the proposed BAC model.

Original languageEnglish
Title of host publicationCHI 2024 - Proceedings of the 2024 CHI Conference on Human Factors in Computing Sytems
ISBN (Electronic)9798400703300
DOIs
StatePublished - 11 May 2024
Event2024 CHI Conference on Human Factors in Computing Sytems, CHI 2024 - Hybrid, Honolulu, United States
Duration: 11 May 202416 May 2024

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2024 CHI Conference on Human Factors in Computing Sytems, CHI 2024
Country/TerritoryUnited States
CityHybrid, Honolulu
Period11/05/2416/05/24

Keywords

  • Activities of daily living
  • Alcohol drinking detection
  • Functional assessment
  • Machine learning
  • Smartphone app usage

Fingerprint

Dive into the research topics of 'S-ADL: Exploring Smartphone-based Activities of Daily Living to Detect Blood Alcohol Concentration in a Controlled Environment'. Together they form a unique fingerprint.

Cite this