Personality first in emotion: a deep neural network based on electroencephalogram channel attention for cross-subject emotion recognition.

ABSTRACT: In recent years, more and more researchers have focused on emotion recognition methods based on electroencephalogram (EEG) signals. However, most studies only consider the spatio-temporal characteristics of EEG and the modelling based on this feature, without considering personality factors, let alone studying the potential correlation between different subjects. Considering the particularity of emotions, different individuals may have different subjective responses to the same physical stimulus. Therefore, emotion recognition methods based on EEG signals should tend to be personalized. This paper models the personalized EEG emotion recognition from the macro and micro levels. At the macro level, we use personality characteristics to classify the individuals' personalities from the perspec

SUBMITTER: Tian Z 

PROVIDER: S-EPMC8371362 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature