Development and Multicenter Validation of an AI-Based Remote Photoplethysmography (rPPG) Facial Scan for Multimodal Health Assessment

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Conditions studied: Metabolic Syndrome, Hypertension, Diabetes (DM), Tachycardia, ASCVD, Depression Disorder, Anxiety, Stress (Psychology), Obesity & Overweight, Cardiometabolic Risk Factors, Cardiometabolic Health Indicators, Sleep, Wellness

In brief

The goal of this observational study is to learn if a non-contact facial scan using artificial intelligence (AI) can be used to check health status in adults living in urban areas such as Jakarta. The facial scan uses a method called remote photoplethysmography (rPPG), which measures small changes in blood flow from the face using a camera. The main questions this study aims to answer are: 1. How close are the results from the facial scan to standard medical measurements, such as heart rate, breathing rate, blood pressure, and oxygen levels? 2. Can the facial scan estimate other health indicators, such as blood sugar, lipid profile, HbA1c, and hemoglobin levels? 3. Is there a relationship between the facial scan results and mental health, such as stress, anxiety, and depression? Participants will take part in several simple and mostly non-invasive procedures: 1. Answer questionnaires about their mental health and daily habits 2. Have basic health checks, such as blood pressure, heart rate, and body measurements 3. Provide a blood sample for laboratory testing 4. Complete a facial scan using a camera for about 1 to 3 minutes Researchers will compare the results from the facial scan with standard clinical and laboratory tests to see how well the technology works. This study may help develop a simple and accessible screening tool that can be used for early detection of health risks. It may also support the use of digital health and telemedicine in community and clinical settings.

Key facts

Study ID
NCT07491978
Run by
Tarumanagara University
People needed
1000
Starts
2026-04-24
Expected to finish
2027-03-30
Last updated by the study team
2026-04-20

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Full record on ClinicalTrials.gov

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