A Machine Learning Approach for Inferring Alcohol Intoxication Levels From Gait Data

Completed · Not applicable

Conditions studied: Alcohol Drinking

In brief

This study aims to develop a phone app to assess gait differences at different levels of alcohol intoxication.

Key facts

Study ID: NCT03246490
Run by: Butler Hospital
People needed: 141
Starts: 2017-12-12
Expected to finish: 2019-07-31
Last updated by the study team: 2020-04-07

Who can join

Age: 21 and older, up to 75. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

ages 21-65
drinking at least 5 drinks per occasion for men (4 for women) during a single drinking episode at least once in the last month to ensure, for safety reasons, that people are accustomed to consuming alcohol in amounts comparable to what we will administer
willingness to drink beer (since only beer will be provided in the session to standardize drinks more easily).

You may not qualify if…

past 6 months or current treatment for alcohol or drug abuse by self-report (for ethical reasons)
Score > 5 on (the short version of the Michigan Alcohol Screening Test [SMAST]48) given during the screening interview
positive family history of alcohol use disorder
weight ≥ 230 lbs (to prevent excessive volume of beverage)
current use of medications that are contraindicated for alcohol
a health condition that contraindicates alcohol (e.g. peptic ulcer disease)
a health condition that affects ability to walk
if female, pregnant or nursing
use of recreational drugs (e.g., marijuana, opioids, stimulants, benzodiazepines) within the last week (self-report plus urine screening cup)
persons who report alcohol-induced flushing, an untoward reaction that is often accompanied by headache, nausea and other symptoms

Where it is running

Butler Hospital — Providence, Rhode Island, United States

Full record on ClinicalTrials.gov

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