An EEG-based cross-subject interpretable CNN for game player expertise level classification

• Published in: Expert systems with applications Vol. 237; p. 121658
• Main Authors: Lin, Liqi, Li, Pengrui, Wang, Qinghua, Bai, Binnan, Cui, Ruifang, Yu, Zhenxia, Gao, Dongrui, Zhang, Yongqing
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2024
• Subjects: Cross-subject; Depthwise separable convolution; Electroencephalography (EEG); Game player; Interpretable technology; Electroencephalography (EEG); Depthwise separable convolution; Cross-subject; Interpretable technology; Game player

Electroencephalogram (EEG) signals have been demonstrated to be an effective method for game player expertise level classification, as it can reflect the activity state of the player’s brain during the game task. Although many efforts have been made to classify the expertise level of game players ba...