Automated interpretation of signals yields many impressive applications from the area of affective computing and human activity recognition (HAR). In this paper we ask the question about possibility of cognitive activity recognition on the base of particular set of signals. We use recognition of the game played by the participant as a playground for exploration of the problem. We build classifier of three different games (Space Invaders, Tetris, Tower Defence) and inter-game pause. We validate classifier in the player-independent and player-dependent scenario. We discuss the improvement in the player-dependent scenario in the context of biometric person recognition. On the base of the results obtained in game classification, we consider potential applications in smart surveillance and quantified self.

自动信号解读在情感计算和人类活动识别领域有许多令人印象深刻的应用。本文探讨了通过一组特定信号对认知活动进行识别的可能性，并以参与者所玩游戏的识别作为问题探索的基础。我们构建了三种不同游戏（Space Invaders，Tetris，Tower Defence）和游戏间暂停的分类器，并在参与者独立和依赖于参与者的场景中进行了验证。我们讨论了在依赖于参与者的情况下，基于生物特征的个人识别方面的改进。根据游戏分类的结果，我们考虑了智能监控和个人数据量化方面的潜在应用。

基于生理信号和眼动的游戏类型识别