Predicting Real-Time Affective States by Modeling Facial Emotions Captured During Educational Video Game Play

Autor:	Ashish Amresh, Hansol Rheem, Scotty D. Craig, Ajay Bansal, Vipin Verma
Rok vydání:	2020
Předmět:	Facial expression Binomial regression medicine Boredom medicine.symptom Psychology Affective computing human activities Video game Session (web analytics) Personalization Cognitive psychology
Zdroj:	Lecture Notes in Computer Science ISBN: 9783030634636 GALA
Popis:	In an attempt to predict the cognitive-affective states of a player during an educational video game session, this study used a self-emote procedure in which participants’ facial expressions and emotions were continuously recorded along with self-reported data about their emotional states. Participants’ facial expressions and emotions were captured using Affdex SDK from Affectiva. The captured data were used for binomial logistic regression to predict the cognitive-affective states of flow, frustration, and boredom. The binomial logistic regression uncovered that expressions and emotions could be used to predict these cognitive-affective states of a player. We discuss these predictors and their potential to adapt an educational video game session with non-intrusive and affect-sensitive personalization capabilities. The current study provides a pathway for the educational play design and suggests that it should be non-intrusive while being adaptive to a player’s capabilities.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d4df71fe64b3a0e0dcc6f7a84e3382ea https://doi.org/10.1007/978-3-030-63464-3_45 Zobrazit plný text záznamu