Date of Award

6-2012

Document Type

Open Access

Degree Name

Bachelor of Science

Department

Computer Engineering

First Advisor

Aaron Cass

Language

English

Keywords

outcome, study, drinking, alcohol, smart phone, tests

Abstract

This research and development undertaking during the senior year is a culmination of undergraduate study at Union College and is an opportunity to put knowledge gained to use. The purpose of this specific capstone project is to bring together not just the research and implementation techniques learned as a Computer Engineer but to also meld this discipline with another; Neuroscience. The objective of the project was to develop a full function software prototype in the form of a mobile phone application. The mobile application (Mobile Intoxication Assessment Tool) constitutes a grouping of simple subtasks that can be completed on the touch screen of an Android powered smart phone. These subtasks are designed in such a way that they evaluate five primary abilities that are disrupted by acute alcohol intoxication. The five affected faculties include memory and problem solving abilities, fine muscle control, vision, and reaction time. The result of a user’s cumulative scores on these simple tests paired with their personal information such as body weight, age, and height is compared to a “baseline sobriety reading”. This baseline reading is calculated, at the time of the application’s download, when the sober user completes a variation of the tests that will be administered during intoxication. This project aims to identify a quantitative correlation between blood alcohol content (BAC) and the degradation of a users test scores from their “baseline sobriety reading” scores. Through a month long study, of 25 participants of legal drinking age, this correlation between variations in test scores and users intoxication was searched for. As was the ideal outcome, a strong correlation was discovered and the software prototype resulting from this research is able to provide a BAC reading. The software has yet to achieve the level of BAC prediction accuracy of a commercially available breathalyzer but further research is planned to remedy this.

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