Key result
EEG-based model classifies emotions with ~90% accuracy, showing joy music improves negative states.
Why the study?
Music therapy is increasingly used to promote physical health, but objective emotion semantic recognition using EEG signals was needed to improve emotional judgment reliability and explore music-emotion correlations.
Does an EEG-based emotion recognition model and music-based emotion classification model accurately identify emotions and map the influence of music on emotional changes?
Does an EEG-based emotion recognition model and music-based emotion classification model accurately identify emotions and map the influence of music on emotional changes?
An EEG-based emotion recognition model and music-based emotion classification model achieved high accuracy in identifying emotions and mapping the influence of different music types on emotional changes.
Answers are grounded in this paper and cite their sources.
Requires prospective validation before clinical emotion applications; leaves open therapeutic utility of music-mapped EEG models.
Music therapy is increasingly being used to promote physical health. Emotion semantic recognition is more objective and provides direct awareness of the real emotional state based on electroencephalogram (EEG) signals. Therefore, we proposed a music therapy method to carry out emotion semantic matching between the EEG signal and music audio signal, which can improve the reliability of emotional judgments, and, furthermore, deeply mine the potential influence correlations between music and emotions. Our proposed EER model (EEG-based Emotion Recognition Model) could identify 20 types of emotions based on 32 EEG channels, and the average recognition accuracy was above 90% and 80%, respectively. Our proposed music-based emotion classification model (MEC model) could classify eight typical emotion types of music based on nine music feature combinations, and the average classification accuracy was above 90%. In addition, the semantic mapping was analyzed according to the influence of different music types on emotional changes from different perspectives based on the two models, and the results showed that the joy type of music video could improve fear, disgust, mania, and trust emotions into surprise or intimacy emotions, while the sad type of music video could reduce intimacy to the fear emotion.
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Zhou et al. (2022) studied Emotion recognition in psychological healthcare. EEG-based Emotion Recognition Model (EER) and Music-based Emotion Classification Model (MEC) was evaluated on Emotion recognition accuracy and music emotion classification accuracy. An EEG-based emotion recognition model identified 20 emotion types with >90% average accuracy, and semantic mapping showed joy music improved negative emotions into surprise or intimacy.
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