Predicting game-induced emotions using EEG, data mining and machine learning

• Published in: Bulletin of the National Research Centre Vol. 48; no. 1; pp. 57 - 10
• Main Authors: Lim, Min Xuan, Teo, Jason
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2024; Springer Nature B.V; SpringerOpen
• Subjects: Agriculture; Algorithms; Annotations; Classification; Classifiers; Computer & video games; Data acquisition; Data mining; Data processing; Datasets; EEG; EEG-based emotion recognition; Electroencephalography; Emotion recognition; Emotional factors; Emotions; Engineering; Feature extraction; Game-induced EEG; Humanities and Social Sciences; Machine learning; Molecular Biology and Biotechnology; multidisciplinary; Performance evaluation; Science; Science (multidisciplinary); Support vector machines; Data mining; Game-induced EEG; EEG-based emotion recognition; Machine learning
• ISSN: 2522-8307; 2522-8307
• DOI: 10.1186/s42269-024-01200-7

Background Emotion is a complex phenomenon that greatly affects human behavior and thinking in daily life. Electroencephalography (EEG), one of the human physiological signals, has been emphasized by most researchers in emotion recognition as its specific properties are closely associated with human...