SAE+LSTM: A New Framework for Emotion Recognition From Multi-Channel EEG

EEG-based automatic emotion recognition can help brain-inspired robots in improving their interactions with humans. This paper presents a novel framework for emotion recognition using multi-channel electroencephalogram (EEG). The framework consists of a linear EEG mixing model and an emotion timing...

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Vydané v:	Frontiers in neurorobotics Ročník 13; s. 37
Hlavní autori:	Xing, Xiaofen, Li, Zhenqi, Xu, Tianyuan, Shu, Lin, Hu, Bin, Xu, Xiangmin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland Frontiers Research Foundation 12.06.2019 Frontiers Media S.A
Predmet:	Algorithms Arousal Asymmetry Brain research EEG emotion recognition Emotions International conferences Long short-term memory LSTM Methods neural network Neural networks Noise Physiology Robotics and AI Signal processing Stack AutoEncoder Wavelet transforms China Stack AutoEncoder LSTM emotion recognition neural network EEG
ISSN:	1662-5218, 1662-5218
On-line prístup:	Získať plný text
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