Journal of Zhejiang University SCIENCE B 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/jzus.B2500705


Three-dimensional face reconstruction for emotional dynamics: a novel approach to distinguishing bipolar disorder from major depressive disorders


Author(s):  Tao DU1,3, Jinchao GE2, Hong LYU1,3, Yutong ZHANG1,4, Xin XU5,6,7, Shaohua HU1,6,7,9, Jingkai CHEN1,8

Affiliation(s):  1. 1Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China 2School of Computing and Information Technology, University of Wollongong, Northfields Avenue, Wollongong NSW 2522, Australia 3School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang 110159, China 4Department of?Computer Science, Loughborough University, Loughborough?LE11?3TU, UK 5School of Public Health, The Second Affiliated Hospital of School of Medicine, Zhejiang University, Hangzhou 310058, China 6Nanhu Brain-computer Interface institute, Hangzhou 311100, China 7The State Key Lab of Brain-Machine Intelligence, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University School of Medicine, Hangzhou 310003, China 8The Zhejiang Key Laboratory of Precision Psychiatry, Hangzhou 310003, China 9Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou 310000, China

Corresponding email(s):   Jingkai CHEN, wzcjk922@163.com Shaohua HU, dorhushaohua@zju.edu.cn Xin XU, xuxinsummer@zju.edu.cn

Key Words:  Major depressive disorder, Bipolar disorder, 3D facial reconstruction, Emotion dynamics, Valence and arousal


Tao DU1,3, Jinchao GE2, Hong LYU1,3, Yutong ZHANG1,4, Xin XU5,6,7 , Shaohua HU1,6,7,9, Jingkai CHEN1,8. Three-dimensional face reconstruction for emotional dynamics: a novel approach to distinguishing bipolar disorder from major depressive disorders[J]. Journal of Zhejiang University Science B, 1998, -1(-1): .

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Abstract: 
major depressive disorder (MDD) and bipolar disorder (BD) are frequently misdiagnosed in clinical practice due to their overlapping symptoms, resulting in delayed treatment and an increased burden on patients. Reliable biomarkers for early differential diagnosis are currently lacking. To address this, we developed a clinical facial video dataset of patients with BD and MDD and introduced Adaptive Shape Model with Vision-to-Language (AsmV2L), a vision-language-guided fine-grained 3D face reconstruction framework that better preserves affect-related facial cues from monocular videos. Using valence-arousal (VA) representations estimated from these reconstructed 3D faces, we identified distinct affective patterns that differentiated the two disorders. In subject-level downstream evaluation, the emotional dynamic features extracted by our framework achieved 88.9% accuracy in distinguishing BD from MDD. Additionally, experiments on public benchmark datasets demonstrated that AsmV2L maintains competitive 3D reconstruction accuracy while preserving emotion-related semantic information more effectively.

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On-line Access: 2026-05-25

Received: 2025-11-09

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