Fatigue Prediction and Intervention for Continuous Play in Video Games

Abstract

Recently, there are many video games that keep relatively high difficulty for an extended period of time. However, the game with high level of challenges will induce more frustration and tiredness causing players to take more short breaks than usual. While mental fatigue has been studied widely, there are not many game studies and applications related to mental fatigue. One of the possible applications that we want to explore is artificial insertion of an interval serving as a break for players before they get fatigue and take a break from playing games. We plan to use Electroencephalogram (EEG) for fatigue monitoring and machine learning approaches to help predict the right time for intervention. Currently, we have created a prototype game to be used in the experiment and collect sample data for the machine learning.