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Multimodal Identification of Depressive Symptoms in the Elderly
Sponsor: Wuhan Mental Health Centre
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.
Official title: Multimodal Identification of Depressive Symptoms
Key Details
Gender
All
Age Range
60 Years - 100 Years
Study Type
OBSERVATIONAL
Enrollment
2000
Start Date
2025-09-01
Completion Date
2027-12-30
Last Updated
2025-08-11
Healthy Volunteers
Yes
Conditions
Interventions
data collection
Collect the facial expressions, audio, text and postural behavior data of the respondents using electronic devices.
Locations (1)
Wuhan Mental Health Center
Wuhan, Hubei, China