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Multimodal Identification of Depressive Symptoms in the Elderly

NCT07112118 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 2000

Last updated 2025-08-11

No results posted yet for this study

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

Interventions

OTHER

data collection

Collect the facial expressions, audio, text and postural behavior data of the respondents using electronic devices.

Sponsors & Collaborators

  • Wuhan Mental Health Centre

    lead OTHER

Principal Investigators

  • Xiaoxv Yin, PhD · Huazhong University of Science and Technology

Eligibility

Min Age
60 Years
Max Age
100 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-09-01
Primary Completion
2026-09-01
Completion
2027-12-30

Countries

  • China

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07112118 on ClinicalTrials.gov