Emotion recognition based on physiological signals has become a research hotspot.Under the background of increas-ing the proficiency analysis task of locating user knowledge blind spots in radar training simulator,this paper studies the method of identifying user proficiency based on physiological signals.The experimental paradigm of self-acquisition of two-class proficiency data sets based on multi-modal data such as EEG signals and eye movement signals is given,and a variety of proficiency recogni-tion experiments are carried out on this data set.It is concluded that the data richness of the proficiency data set proposed in this pa-per is sufficient to support the classical deep learning model.In addition,the average recognition accuracy of the proficiency model based on multiple physiological signals is higher than that based on the single-modal model.The average recognition accuracy of the multi-modal recognition model with the highest accuracy can reach 84%.
关键词
脑电信号/眼动信号/多模态/熟练度识别
Key words
EEG signal/eye movement signal/multi-modal/proficiency recognition
维普
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