Emotion Arousal Assessment Based on Multimodal Physiological Signals for Game Users
2023 (English)In: IEEE Transactions on Affective Computing, E-ISSN 1949-3045, Vol. 14, no 4, p. 2582-2594Article in journal (Refereed) Published
Abstract [en]
Emotional arousal, an essential dimension of game users' experience, plays a crucial role in determining whether a game is successful. Game users' emotion arousal assessment (GUEA) is of great importance. However, GUEA often faces challenges, such as selecting emotion-inducing games, labeling emotional arousal, and improving accuracy. In this study, the scheme for verifying the effectiveness of emotion-induced games is proposed so that the selected games can induce the target emotions. In addition, the personalized arousal label generation method is developed to reduce the errors caused by individual differences among subjects. Furthermore, to improve the accuracy of GUEA, the Breath Rate Variability (BRV) signal is used as a GUEA indicator along with commonly used physiological signals. Comparative experiments on GUEA based on multimodal physiological signals are conducted. The experimental result shows that the accuracy of GUEA is improved by adding the BRV signal, up to 92%. IEEE
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023. Vol. 14, no 4, p. 2582-2594
Keywords [en]
BRV signal, Data collection, Electrocardiography, emotion arousal assessment, Emotion recognition, game user, Games, Labeling, physiological signal, Physiology, Training, Breath rate variability signal, Game, Generation method, Labelings, Multi-modal, Physiological signals
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-24487DOI: 10.1109/TAFFC.2023.3265008ISI: 001124163900011Scopus ID: 2-s2.0-85153358278OAI: oai:DiVA.org:bth-24487DiVA, id: diva2:1755163
2023-05-052023-05-052024-03-04Bibliographically approved