This paper proposes an approach based on emotion recognition to maintain engagement of players in a game by modulating the game difficulty. Physiological and questionnaire data were gathered from 20 players during and after playing a Tetris game at different difficulty levels. Both physiological and self-report analyses lead to the conclusion that playing at different levels gave rise to different emotional states and that playing at the same level of difficulty several times elicits boredom. Emotion assessment from physiological signals was performed using a SVM (Support Vector Machine). An accuracy of 53.33% was obtained on the discrimination of three emotional classes, namely boredom, anxiety, engagement.