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Real Time Drunkness Analysis Through Games Using Artificial Neural Networks

Authors:
Audrey Robinel
Didier Puzenat

Keywords: User interfaces; Games; Neural network applications; Cognitive sciences; Psychology; Human factors.

Abstract:
In this paper, we describe a blood alcohol content estimation prototype based on a comportment analysis performed by artificial neural networks. We asked to subjects that had drunk alcohol to play a video-game after having measured their blood alcohol content with a breathalyser. A racing game was modified so that it could provide various data related to the use of the controls by the player. Using the collected data, we trained our neural network in order to be able to determine whether or not the subject had exceeded a blood alcohol content threshold. We also succeeded in estimating this blood alcohol content with a mean error of 0.1g/l. We could perform those estimations independently of the track played among the two ones used. It was also performed in “real time”, e.g., using only the data collected within the last 10 seconds of playing.

Pages: 206 to 211

Copyright: Copyright (c) IARIA, 2011

Publication date: February 23, 2011

Published in: conference

ISSN: 2308-4138

ISBN: 978-1-61208-117-5

Location: Gosier, Guadeloupe, France

Dates: from February 23, 2011 to February 28, 2011