Self-supervised EEG emotion recognition models based on CNN

Emotion plays crucial roles in human life. Recently, emotion classification from electroencephalogram (EEG) signal has attracted attention by researchers due to the rapid development of brain computer interface (BCI) techniques and machine learning algorithms. However, recent studies on emotion clas...

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Veröffentlicht in:	IEEE transactions on neural systems and rehabilitation engineering 2023-01, Vol.31, p.1-1
Hauptverfasser:	Wang, Xingyi, Ma, Yuliang, Cammon, Jared, Fang, Feng, Gao, Yunyuan, Zhang, Yingchun
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Brain Brain modeling Classification Computer applications Convolution Convolutional neural networks EEG Electroencephalography Electroencephalography - methods emotion classification Emotion recognition Emotions Feature extraction Human-computer interface Humans Implants Learning algorithms Machine Learning Multi-Task Learning Neural networks Neural Networks, Computer Resource utilization Self-supervised Self-supervised learning Signal classification Task analysis Transformations
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