Each human activity involves feelings and subjective emotions: different people will perform and sense the same task with different outcomes and experience; to understand this experience, concepts like Flow or Boredom must be investigated using objective data provided by methods like electroencephalography. This work carries on the analysis of EEG data coming from brain-computer interface and videogame “Neverwinter Nights 2”: we propose an experimental methodology comparing results coming from different off-the-shelf machine learning techniques, employed on the gaming activities, to check if each affective state corresponds to the hypothesis fixed in their formal design guidelines.
CITATION STYLE
Balducci, F., & Grana, C. (2017). Affective Classification of Gaming Activities Coming from RPG Gaming Sessions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10345 LNCS, pp. 93–100). Springer Verlag. https://doi.org/10.1007/978-3-319-65849-0_11
Mendeley helps you to discover research relevant for your work.