Dynamic entropy-based pattern learning to identify emotions from EEG signals across individuals

•Reliable emotional-relevant EEG features are extracted based on dynamic entropy measures over time.•Dynamic entropy-based pattern learning enables subject-independent emotion recognition with good generalization.•EEG in anterior hemisphere of the brain may be the preferred choice.•The best average...

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Veröffentlicht in:	Measurement : journal of the International Measurement Confederation 2020-01, Vol.150, p.107003, Article 107003
Hauptverfasser:	Lu, Yun, Wang, Mingjiang, Wu, Wanqing, Han, Yufei, Zhang, Qiquan, Chen, Shixiong
Format:	Artikel
Sprache:	eng
Schlagworte:	Decision making EEG Electroencephalography Emotion recognition Emotions Entropy measures Learning Machine learning Measurement Mental health Patterning Sample entropy SEED dataset Studies
Online-Zugang:	Volltext
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