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Worcester Polytechnic Institute Develops App That Detects Alcohol Intoxication

The National Highway Traffic and Safety Administration found that nearly 10,000 people died in alcohol-related car crashes in the United States in 2014 (which is the most recent year that data is available). In an effort to prevent these accidents, a student team from Worcester Polytechnic Institute (WPI) has developed new mobile app that can detect a person’s blood alcohol content within 90 percent accuracy on average, helping individuals determine that they are too drunk to drive.

AlcoGait is a smartphone app that analyzes a person’s movement before and after an individual consumes alcohol to calculate his or her intoxication level. It works by first recording and analyzing the motion data from a person walking normally for up to 30 seconds (with his or her mobile device in a hand, pocket or clipped to a belt). After consuming alcohol, the user can run the app in the background — without disrupting any other functions on the phone — to continuously analyze his or her walking pattern, or gait, for any anomalies that could signal impairment. Users can either check the app or AlcoGait will alert them with a text message when they have exceeded the legal limit.  

The app was first conceived as a capstone project for WPI computer science students working with Emmanuel Agu, an associate professor in WPI’s Computer Science Department. Under Agu’s direction, students Zachary Arnold and Danielle LaRose built the first working prototype for AlcoGait using data from a smartphone’s accelerometer, according to a university statement. Their project won the 2015 WPI Provost Award in 2015 as the top Computer Science Major Qualifying Project.

The project’s work was later continued by a graduate student in Agu’s lab, Christina Aiello, who “further refined its algorithms, incorporating data from the phone’s gyroscope,” according to a statement. The app was tested by 50 WPI volunteers who were outfitted with “Drunk Buster” goggles to simulate the experience of being intoxicated. Ariello’s work received a first-place award in WPI’s 2016 Graduate Research Innovation Exchange competition.

Another team of computer science students is working to adapt the mobile app for smartwatch use.

About the Author

Sri Ravipati is Web producer for THE Journal and Campus Technology. She can be reached at [email protected].

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