MT-RCAF: A Multi-Task Residual Cross Attention Framework for EEG-based emotion recognition and mood disorder detection.

Journal: Computer methods and programs in biomedicine
Published Date: May 17, 2025

Abstract

BACKGROUND AND OBJECTIVE: Prolonged abnormal emotions can gradually evolve into mood disorders such as anxiety and depression, making it critical to study the relationship between emotions and mood disorders to explore the causes of mood disorders. Existing research on EEG-based emotion recognition and mood disorder detection typically treats these two tasks separately, missing potential synergies between them. The purpose is to reveal the relationship between emotions and mood disorders and propose a Multi-Task Residual Cross Attention Framework (MT-RCAF) to enhance both classification performances.

Authors

  • Xinni Kong
    School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, Zhejiang, China.
  • Yaru Guo
    School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, Zhejiang, China.
  • Yu Ouyang
    Hangzhou Dianzi University, School of Computer Science and Technology, HangZhou, ZheJiang, China. Electronic address: 222050269@hdu.edu.cn.
  • Wenjie Cheng
    School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, Zhejiang, China.
  • Ming Tao
    College of Engineering, South China Agricultural University, Guangzhou 510642, China.
  • Hong Zeng
    School of Computer Science and Technology, Hangzhou Dianzi University, China.

Keywords

External Resources

Popular Topics
Recent Journals