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Study on the change of physiological signals during playing body-controlled games

In this paper, we give an experiment to investigate the change of physiological signals during playing body-controlled games. The physiological signals, including pulse rate, skin temperature, saturation of peripheral oxygen (SpO2), and galvanic skin response (GSR), of eleven healthy participants were recorded while playing body-controlled games. Based on the results of the experiment, we propose a discriminant model to predict the fatigue state of players. Our model can identify non-fatigue with 78.90% accuracy and fatigue with 82.76% accuracy. This model can be used with biofeedback hardware to continuously predict players' fatigue state and to improve the adaptation design of body-controlled games.