Research progress of emotion recognition based on electroencephalogram signal
10.3760/cma.j.cn121382-20250507-00036
- VernacularTitle:基于脑电信号的情绪识别研究进展
- Author:
Kunqi DAI
1
;
Ren MA
;
Tao YIN
;
Zhipeng LIU
Author Information
1. 中国医学科学院 北京协和医学院生物医学工程研究所，天津 300192
- Keywords:
Machine learning;
Deep learning;
Electroencephalogram signal;
Emotion recognition
- From:
International Journal of Biomedical Engineering
2025;48(5):482-488
- CountryChina
- Language:Chinese
-
Abstract:
Emotion is defined as a physiological and psychological state that encompasses human thoughts, behaviors, and feelings. This phenomenon is also regarded as a spontaneous physiological and psychological response generated by the human body to external stimuli. Given the established correlation between electroencephalogram signal and cerebral activity, it is possible to extrapolate the emotional state of subjects by means of electroencephalogram signal analysis. In this review, emotion models, datasets, and popular machine learning and deep learning methods in recent years used in emotion recognition research were summarized. In addition, the research progress of emotion recognition based on electroencephalogram signal was reviewed, with the aim of assisting subsequent researchers in understanding developments in electroencephalogram signal domain and offering insights for addressing clinical challenges in emotion recognition.
