NCT07112118

Multimodal Identification of Depressive Symptoms in the Elderly

Multimodal Identification of Depressive Symptoms

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 2,000 (estimated)
• Sponsor: Wuhan Mental Health Centre · Academic / Other
• Sex: All
• Age: 60 Years – 100 Years
• Healthy volunteers: Accepted

Summary

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.

Conditions

• Depression

Interventions

Type	Name	Description
OTHER	data collection	Collect the facial expressions, audio, text and postural behavior data of the respondents using electronic devices.

Timeline

• Start date: 2025-09-01
• Primary completion: 2026-09-01
• Completion: 2027-12-30
• First posted: 2025-08-08
• Last updated: 2025-08-11

Locations

1 site across 1 country: China