Acrophobia screening method based on gridding feature extraction
The screening methods based on visual exploration features mainly use pupil features.However,pupil features are easily disturbed by ambient light intensity,which seriously affects the accuracy of the acrophobia screening model.To solve this problem,the grid-based visual exploration feature extraction(GVEFE)algorithm is proposed.This method involves dividing visual exploration data into grids and decoupling light intensity infor-mation before extracting relevant signal and behavioral features.Meanwhile,the active visual exploration elicita-tion(AVEE)paradigm is also proposed to better induce the acrophobia state.Experimental results show that the GVEFE improves the accuracy by 11.77％,while the AVEE paradigm improves the degree of acrophobia elicita-tion by 13.57％.The results show that the GVEFE algorithm and the AVEE paradigm hold promising application prospects.
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