PL-DCP: A pairwise learning framework with domain and class prototypes for EEG emotion recognition under unseen target conditions

Key Points

• Emotion recognition is enhanced using a pairwise learning framework, focusing on domain and class prototypes for improved accuracy.
• The proposed method utilizes EEG signals, achieving detection rates that indicate significant potential across different conditions.
• Assessment using a pairwise learning framework aims to improve emotion recognition in scenarios not previously encountered.
• May enable more accurate emotion analysis in diverse settings, highlighting the need for further exploration of unseen target conditions.