Spatial-Temporal Feature Fusion Neural Network for EEG-Based Emotion Recognition

Author:

Wang Zhe1ORCID,Wang Yongxiong1ORCID,Zhang Jiapeng1ORCID,Hu Chuanfei2ORCID,Yin Zhong1,Song Yu3ORCID

Affiliation:

1. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China

2. Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing, China

3. Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems, Tianjin University of Technology, Tianjin, China

Funder

Natural Science Foundation of Shanghai

National Natural Science Foundation of China

Key technologies R&D program of Tianjin

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Reference41 articles.

1. Emotion recognition based on EEG using LSTM recurrent neural network;alhagry;Emotion,2017

2. Multimodal emotion recognition using a hierarchical fusion convolutional neural network;zhang;IEEE Access,2020

3. Emotional processing in anterior cingulate and medial prefrontal cortex

4. Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech

5. Squeeze-and-Excitation Networks

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