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.

翻译：信号的自动解译在情感计算和人体活动识别（HAR）领域催生了众多令人瞩目的应用。本文探讨基于特定信号集进行认知活动识别的可能性，并以参与者所玩游戏类型的识别作为研究该问题的试验场景。我们构建了三种不同游戏（《太空侵略者》《俄罗斯方块》《塔防》）及其间暂停状态的分类器，并在玩家独立与玩家依赖两种场景下验证分类器性能。我们基于生物特征识别的视角，讨论了玩家依赖场景下的性能提升。基于游戏分类的研究结果，我们进一步探讨了该技术在智能监控与量化自我领域的潜在应用前景。