摘要
Emotions,formed in the process of perceiving external environment,directly affect human daily life,such as social interaction,work efficiency,physical wellness,and mental health.In recent decades,emotion recognition has become a promising research direction with significant application values.Taking the advantages of electroencephalogram(EEG)signals(i.e.,high time resolution)and video-based external emotion evoking(i.e.,rich media information),video-triggered emotion recognition with EEG signals has been proven as a useful tool to conduct emotion-related studies in a laboratory environment,which provides constructive technical supports for establishing real-time emotion interaction systems.In this paper,we will focus on video-triggered EEG-based emotion recognition and present a systematical introduction of the current available video-triggered EEG-based emotion databases with the corresponding analysis methods.First,current video-triggered EEG databases for emotion recognition(e.g.,DEAP,MAHNOB-HCI,SEED series databases)will be presented with full details.Then,the commonly used EEG feature extraction,feature selection,and modeling methods in video-triggered EEG-based emotion recognition will be systematically summarized and a brief review of current situation about video-triggered EEG-based emotion studies will be provided.Finally,the limitations and possible prospects of the existing video-triggered EEG-emotion databases will be fully discussed.
基金
funded by the National Natural Science Foundation of China(Grant No.61906122)