  With the increasing demands of emotion comprehension and regulation in our
daily life, a customized music-based emotion regulation system is introduced by
employing current EEG information and song features, which predicts users'
emotion variation in the valence-arousal model before recommending music. The
work shows that: (1) a novel music-based emotion regulation system with a
commercial EEG device is designed without employing deterministic emotion
recognition models for daily usage; (2) the system considers users' variant
emotions towards the same song, and by which calculate user's emotion
instability and it is in accordance with Big Five Personality Test; (3) the
system supports different emotion regulation styles with users' designation of
desired emotion variation, and achieves an accuracy of over $0.85$ with
2-seconds EEG data; (4) people feel easier to report their emotion variation
comparing with absolute emotional states, and would accept a more delicate
music recommendation system for emotion regulation according to the
questionnaire.
