Detecting Drunk Driving Using Off-the-Shelf Smartwatches
Alcohol-impaired driving remains a major yet preventable cause of road traffic injury and death, with many drivers underestimating their level of intoxication. Compared to in-vehicle systems, mobile drunk-driving detection using consumer smartwatches offers a scalable way to trigger preventive interventions and increase awareness without additional in-vehicle hardware. We introduce a system that leverages wrist accelerometer data and heart rate variability-derived physiological signals to detect alcohol-related driving impairment. We collected data in a randomized, controlled three-arm test-track study (n=54) and trained both logistic regression models with window-aggregated features and ...
| Authors | Robin Deuber, Lanlan Yang, Michal Bechny et al. |
|---|---|
| Primary category | cs.HC |
| Published | 22 May 2026 |
| Last updated at source | 22 May 2026 |
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