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.
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Agreement of rPPG-Derived Vital Signs With Standardized Clinical Measurements
Timeframe: At a single study visit during baseline assessment (cross-sectional measurement)
Concordance Between rPPG-Derived Biomarker Estimates and Standard Laboratory Measurements
Timeframe: At a single study visit during baseline assessment (cross-sectional measurement)
Association Between rPPG-Derived Physiological Parameters and Psychological Status
Timeframe: At a single study visit during baseline assessment (cross-sectional measurement)
Agreement of rPPG-Derived Cardiovascular Risk Indices With Standard Clinical Calculations
Timeframe: At a single study visit during baseline assessment (cross-sectional measurement)