EESCN: A novel spiking neural network method for EEG-based emotion recognition.

Journal: Computer methods and programs in biomedicine
Published Date: Nov 20, 2023

Abstract

BACKGROUND AND OBJECTIVE: Although existing artificial neural networks have achieved good results in electroencephalograph (EEG) emotion recognition, further improvements are needed in terms of bio-interpretability and robustness. In this research, we aim to develop a highly efficient and high-performance method for emotion recognition based on EEG.

Authors

  • FeiFan Xu
    Hangzhou Dianzi University, School of Computer Science and Technology, HangZhou, ZheJiang, China. Electronic address: 212050125@hdu.edu.cn.
  • Deng Pan
    Hefei National Laboratory for Physical Sciences at the Microscale, Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, CAS Key Laboratory of Mechanical Behavior and Design of Materials, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
  • Haohao Zheng
    Hangzhou Dianzi University, School of Computer Science and Technology, HangZhou, ZheJiang, China. Electronic address: zhenghaohao@hdu.edu.cn.
  • Yu Ouyang
    Hangzhou Dianzi University, School of Computer Science and Technology, HangZhou, ZheJiang, China. Electronic address: 222050269@hdu.edu.cn.
  • Zhe Jia
    Hangzhou Dianzi University, School of Computer Science and Technology, HangZhou, ZheJiang, China. Electronic address: 222050129@hdu.edu.cn.
  • Hong Zeng
    School of Computer Science and Technology, Hangzhou Dianzi University, China.

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