EEG-based emotion recognition using 4D convolutional recurrent neural network

• Published in: Cognitive neurodynamics Vol. 14; no. 6; pp. 815 - 828
• Main Authors: Shen, Fangyao, Dai, Guojun, Lin, Guang, Zhang, Jianhai, Kong, Wanzeng, Zeng, Hong
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.12.2020; Springer Nature B.V
• Subjects: Artificial Intelligence; Artificial neural networks; Biochemistry; Biomedical and Life Sciences; Biomedicine; Cognitive Psychology; Computer Science; Deep learning; EEG; Electrodes; Electroencephalography; Emotion recognition; Emotions; Frequency dependence; Long short-term memory; Methods; Neural networks; Neurosciences; Normal distribution; Physiology; Random variables; Recurrent neural networks; Research Article; Spatial data; Convolutional recurrent neural network; Emotion recognition; 4D data; EEG

In this paper, we present a novel method, called four-dimensional convolutional recurrent neural network, which integrating frequency, spatial and temporal information of multichannel EEG signals explicitly to improve EEG-based emotion recognition accuracy. First, to maintain these three kinds of in...