Abstract
Understanding and profiling player motivation complements and extends research on gameflow, player profiling, and game artificial intelligence, which helps us design entertaining games. However, automated identification of a player’s motive profile remains an open challenge. An emerging technology that shows promise as a novel technique for identifying cognitive phenomena is electroencephalography (EEG). This paper begins with a survey of literature applying EEG to measure cognitive characteristics relevant to player motivation types. Then we present conceptual models that link motivation theory to mental states that can be identified using EEG including emotion, risk-taking, and social attitudes. We conclude this paper by examining the research challenges associated with using EEG to validate these models.
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