arXiv (All)
open access
Kinematic signatures of impairment: Detecting alcohol intoxication in e-scooter riders using sensor data and machine learning
Alcohol intoxication is a leading contributor to fatal and severe-injured e-scooterist crashes. Current countermeasures, such as temporal restrictions or pre-ride cognitive screening, cannot continuously assess an e-scooterist's physical motor control or impairment in real time. We conducted a contr
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Accidents at work by sex, age, severity, NACE Rev. 2 activity and specific physical activity#814873
- Accidents at work by sex, age, severity, NACE Rev. 2 activity and material agent of specific physical activity#814875
- Alcohol Impaired Driving: From the Laboratory to the Natural Environment#899684
- CONCEPTUALIZING E-SCOOTER USER BEHAVIOR IN THE CONTEXT OF SUSTAINABLE MOBILITY: DEVELOPING THE ELECTRIC SCOOTER USER BEHAVIOR QUESTIONNAIRE, INVESTIGATING ITS RELATIONSHIP WITH SUSTAINABLE BEHAVIORS AND PERSONALITY#439634
- Relationship Between Physical Activity and Motor Vehicle Crashes Among Older Adult Drivers#406529
Record · ID 1142877
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive