This application relates to the field of
data processing technology, and discloses an orthogonal fusion model of emotion, fatigue, and subjective will, as well as a method for assessing
mental state. For the problem of
emotion recognition, this application proposes a spatiotemporal entropy
feature extraction method, which has good adaptability to
small sample EEG data; for the problem of low recognition rate in fatigue
state recognition, it proposes a power spectrum normalization
feature extraction method for brain
functional connectivity, which shows higher accuracy in fatigue
state recognition; for the problem of
feature fusion of emotion, fatigue, and work will, it proposes a
mental state assessment model based on the Taguchi
orthogonal method that fuses subjective and objective indicators. Experimental results show that the spatiotemporal entropy feature
emotion recognition, the power spectrum recognition fatigue
state recognition of brain
functional connectivity, and the orthogonal fusion
mental state assessment model of subjective and objective indicators proposed in this invention can complete the task of recognizing emotional state, fatigue state, and mental state.