To build physiological states model for body-controlled games,the change of physiological signals during playing bodycontrolled games was investigated and analyzed. An experiment was conducted to obtain the heart rate (HR) and heart rate variability (HRV) of twelve healthy participants (mean age: 26.6, SD: 1.62) while playing a body-controlled game. The results indicate that HR and some of frequency domain HRV parameters, obtained at different physiological states (rest, fitness, and fatigue), show a statistically significant change (p<0.05). Moreover, a discriminant model was built based on Fisher linear discriminant analysis, which can be used to classify the physiological states of players. Self-validation and cross-validation were used to evaluate the model, and the correct rates of the two validation schemes were higher than 75%. The experimental results indicate that this discriminant model can completely classify the physiological states of players during playing body-controlled games.
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