Alcohol Drinking Clinical Trial
Official title:
A Machine Learning Approach for Inferring Alcohol Intoxication Levels From Gait Data
This study aims to develop a phone app to assess gait differences at different levels of alcohol intoxication.
250 adult volunteers who will each participate in a single laboratory-based visit. At the
orientation, each participant will provide informed consent, be weighed, and undergo a
medical history to confirm eligibility. A urine drug quick-screen will be given. Female
participants will take a urine pregnancy test. Baseline questionnaires will be administered.
After giving participants the phone on which the AlcoGait 2.0 app is installed, baseline
assessment of gait will be performed with the participant walking a distance of 50 yards ten
times.
Drinking will then commence. The total amount will be consumed over 30 minutes. Participants
will have their BrAC assessed multiple times during and after drinking has commenced and
finished. At BrAC levels of .02, .04, .06 and .08 g%, will perform the gait task. After the
last gait task, participant data will be transmitted to a secure server. Participants will
receive a meal, and will be escorted to a sitting area with a DVR and videos, and allowed to
use their own electronic devices. Their BrAC will be periodically tested until it reaches .02
g% or below, then a taxi will be called to take them home.
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