The user’s behavior and his interpretation of interactions with others is influenced by his cultural background, which provides a number of heuristics or patterns of behavior and interpretation. This cultural influence on interaction has largely been neglected in HCI research due to two challenges: (i)
grasping culture as a computational term and (ii) infering the user’s cultural background by observable measures. In this paper, we describe how the Wiimote can be utilized to uncover the user’s cultural background by analyzing his patterns of gestural expressivity in a model based on cultural dimensions. With this information at hand, the behavior of an interactive system can be adapted to culture-dependent patterns of interaction.