SECT: A Method of Shifted EEG Channel Transformer for Emotion Recognition-Reference-Cited by-同舟云学术

SECT: A Method of Shifted EEG Channel Transformer for Emotion Recognition

Published:2023-10 Issue:10 Volume:27 Page:4758-4767
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Bai Zhongli¹^ORCID,Hou Fazheng¹^ORCID,Sun Kaixuan¹^ORCID,Wu Qingzhou¹^ORCID,Zhu Mu¹^ORCID,Mao Zemin²^ORCID,Song Yu¹^ORCID,Gao Qiang³^ORCID

Affiliation:

1. Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems, School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin, China

2. Technical College for the Deaf, Tianjin University of Technology, Tianjin, China

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

Funder

National Natural Science Foundation of China

2022 Tianjin Postgraduate Research and Innovation Project

Tianjin University of Technology Graduate Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10272722/10209178.pdf?arnumber=10209178

Reference32 articles.

1. Comparison of hemispheric asymmetry measurements for emotional recordings from controls

2. DEAP: A Database for Emotion Analysis ;Using Physiological Signals

3. Spatial–Temporal Recurrent Neural Network for Emotion Recognition

4. Learning representations from EEG with deep recurrent-convolutional neural networks;bashivan;Proc 4th Int Conf Learn Representations,2016

5. E3GCAPS: Efficient EEG-based multi-capsule framework with dynamic attention for cross-subject cognitive state detection

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