Multimodal Identification of Depressive Symptoms in the Elderly

Screening with depression scales alone is subjective, and relying on single-modal data often leads to incomplete identification of symptoms that are easily missed or misdiagnosed. In this study, we first aim to use artificial intelligence to construct a depression symptom recognition model, concatenate multimodal features such as facial expression, audio, text, and postural behavior, and deeply fuse them to construct a multimodal model.

NCT Number	NCT07112118
Lead Sponsor	Wuhan Mental Health Centre
Conditions	Depression
Enrollment	2,000 participants
Start Date	2025-09-01
Primary Completion	2026-09-01 (estimated)
Study Completion	2027-12-30 (estimated)
Updated on ClinicalTrials.gov	2025-08-11