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Behavior analysis through games using artificial neural networks

Abstract : This paper demonstrates that a human being using an interface can be efficiently evaluated - in real time - by embedding basic measurements in the interface and using a suitable trained artificial neural network. The approach is introduced through video games but is suitable for any machine capable of valuable measurements on user actions. Of course, the quality of the "diagnostic" depends of the learnability of the task and of the size and quality of the learning base. Typical applications include the detection of fatigue, stress, emotions, the influence of a drug or of medical treatments ; screening a deficit or adequateness to a task, etc. Two successful prototypes are presented, one to predict the mental age of children through a set of simple basic games, and the other to detect if a subject is right-handed of left-handed through a racing car simulation.
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Contributor : Didier Puzenat <>
Submitted on : Friday, June 17, 2011 - 6:35:14 PM
Last modification on : Wednesday, July 18, 2018 - 8:11:27 PM


  • HAL Id : hal-00601476, version 1



Didier Puzenat, Verlut Isabelle. Behavior analysis through games using artificial neural networks. Third International Conferences on Advances in Computer-Human Interactions, Feb 2010, St. Maarten, Netherlands Antilles. pp.134-138. ⟨hal-00601476⟩



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