A review: Music-emotion recognition and analysis based on EEG signals - Cui, Xu; Wu, Yongrong; Wu, Jipeng; You, Zhiyu; Xiahou, Jianbing; Ouyang, Menglin (Frontiers in Neuroinformatics, 2022)
Music plays an essential role in human life, which can act as an expression to evoke human emotions. The diversity of music makes the listener's experience of music appear diverse. Different music can induce various emotions, and the same theme can also generate other feelings related to the listener's current psychological state. Music emotion recognition (MER) has recently attracted widespread attention in academics and industry. With the development of brain science, MER has been widely used in different fields, e.g., recommendation systems, automatic music composing, psychotherapy, music visualization. Especially with the rapid development of artificial intelligence, deep learning-based music emotion recognition is gradually becoming mainstream. Based on this, this paper surveys electroencephalogram (EEG) music emotional analysis, using EEG signals to analyze music emotion recognition. This paper involves the process of the analysis focused on the music emotion analysis method, e.g., data processing, emotion model, feature extraction. Then, challenging problems and development trends of EEG-based music emotion recognition is proposed. Finally, the whole paper is summarized.