Assessment method of depressive disorder level based on graph attention network

This paper presents an approach to predict the depression self-rating scale of Patient Health Questions-9 (PHQ-9) values from pupil-diameter data based on the graph attention network (GAT). The pupil diameter signal was derived from the eye information collected synchronously while the subjects were...

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Bibliographic Details
Published inITM web of conferences Vol. 45; p. 1039
Main Authors Lu, Shengfu, Kang, Jiaming, Zhang, Jinyu, Li, Mi
Format Journal Article Conference Proceeding
LanguageEnglish
Published Les Ulis EDP Sciences 2022
Subjects
Chebyshev approximation
Energy distribution
Entropy (Information theory)
Mental depression
Prediction models
Regression models
Statistical analysis
Virtual reality
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Summary:This paper presents an approach to predict the depression self-rating scale of Patient Health Questions-9 (PHQ-9) values from pupil-diameter data based on the graph attention network (GAT). The pupil diameter signal was derived from the eye information collected synchronously while the subjects were viewing the virtual reality emotional scene, and then the scores of PHQ-9 depression self-rating scale were collected for depression level. The chebyshev distance based GAT (Chebyshev-GAT) was constructed by extracting pupil-diameter change rate, emotional bandwidth, information entropy and energy, and their statistical distribution. The results show that, the error (MAE and SMRE)of the prediction results using Chebyshev-GAT is smaller then the traditional regression prediction model.
Bibliography:ObjectType-Conference Proceeding-1
SourceType-Conference Papers & Proceedings-1
content type line 21
ISSN:2271-2097
2431-7578
2271-2097
DOI:10.1051/itmconf/20224501039