Validation of Remote Photoplethysmography (rPPG)-Derived Cardiovascular Parameters Against Standard Clinical Measurements and Risk Scores in a Community

Validation of Remote Photoplethysmography (rPPG)-Derived Cardiovascular Parameters Against Standard Clinical Measurements and Risk Scores in a Community-Based Population in Semanan, Jakarta

The goal of this observational study is to evaluate whether a contactless camera-based technology, called remote photoplethysmography (rPPG), can accurately measure cardiovascular parameters and estimate cardiovascular risk in adults aged 30 years and older living in a community setting in Semanan, Jakarta. This study aims to determine if rPPG can be used as a simple and accessible tool for early cardiovascular screening.

The main questions it aims to answer are:

1. Do cardiovascular parameters measured using rPPG (such as blood pressure, heart rate, and cardiac workload) agree with standard clinical measurements?
2. Do cardiovascular risk estimates generated by rPPG (such as ASCVD risk and Framingham heart age) correspond to risk calculations obtained using conventional clinical and laboratory methods?

Researchers will compare results obtained from rPPG-based facial video scans with results from standard medical assessments, including blood pressure measurements, heart rate evaluation, and laboratory tests for cholesterol levels, to determine the level of agreement and accuracy.

Participants will:

1. Undergo a short facial video scan (approximately 30-60 seconds) using an rPPG-based system
2. Receive standard clinical assessments, including blood pressure and heart rate measurements
3. Provide basic health information (such as age, sex, smoking status, and treatment history) Undergo simple laboratory testing for cholesterol levels

This study is expected to help determine whether rPPG can be used as a reliable, non-invasive, and scalable screening tool for cardiovascular risk in community and primary healthcare settings.

Study Overview

• Status: Not yet recruiting
• Conditions: Hypertension; Dyslipidemia; Heart Disease; Coronary Artery Disease (CAD); Diabetes (DM); Angina (Stable)

Detailed Description

Introduction Remote photoplethysmography (rPPG) is an emerging contactless technology that enables extraction of physiological signals from facial video, allowing estimation of cardiovascular parameters such as heart rate and blood pressure. With the growing burden of atherosclerotic cardiovascular disease (ASCVD), early and accessible risk screening tools are essential, particularly in community settings with limited access to laboratory-based assessments. Although established risk models such as the ASCVD and Framingham scores are widely used, their application often requires clinical and laboratory data that may not be readily available. The integration of rPPG-based measurements with cardiovascular risk estimation offers a promising approach; however, its clinical validity and agreement with standard methods remain insufficiently explored .

Objective This study aims to evaluate the agreement and concordance between rPPG-derived cardiovascular parameters and standard clinical measurements, as well as to assess the alignment of rPPG-estimated ASCVD risk and Framingham heart age with conventional risk calculations.

Methods This study will use an analytical observational cross-sectional design conducted in Kelurahan Semanan, Jakarta. Adult participants (≥30 years) will be recruited through community-based sampling. Each participant will undergo clinical anamnesis, physical examination (blood pressure and heart rate), and laboratory testing (total cholesterol and HDL). In parallel, rPPG-based facial video scans will be performed under standardized conditions to obtain systolic and diastolic blood pressure, mean arterial pressure, pulse pressure, heart rate, cardiac workload, ASCVD risk, and Framingham heart age. Framingham risk will be calculated using sex-specific equations based on clinical and laboratory variables. Agreement between rPPG and standard measurements will be assessed using Bland-Altman analysis, while correlations will be evaluated using Pearson or Spearman tests. Concordance for categorical risk classification will be analyzed using Cohen's Kappa.

Expected Results It is expected that rPPG-derived heart rate will demonstrate good agreement with standard measurements, while blood pressure parameters will show moderate agreement. Additionally, rPPG-based ASCVD risk and Framingham heart age are anticipated to exhibit acceptable concordance with conventional risk calculations. These findings may support the potential role of rPPG as a preliminary screening and risk stratification tool in community-based and telemedicine settings.

• Study Type: Observational
• Enrollment (Estimated): 300

Contacts and Locations

• Study Contact: Name: Alexander Halim Santoso, MD; Phone Number: +6281381606869; Email: alexanders@fk.untar.ac.id
• Study Contact Backup: Name: Ernawati Ernawati, Dr; Phone Number: +6281389048199; Email: ernawati@fk.untar.ac.id

Study Locations

• Indonesia
  • Jakarta Special Capital Region
    • Jakarta, Jakarta Special Capital Region, Indonesia
      • Kelurahan Semanan
      • Contact: Wenny Sanwani; Phone Number: +6281585013412; Email: wenny.sanwani@gmail.com
      • Contact: Hanna Wijaya; Phone Number: +6281223787878; Email: hannwijaya@yahoo.com
      • Principal Investigator: Ernawati Ernawati
      • Sub-Investigator: Enny Irawaty
      • Sub-Investigator: Zita Atzmardina
      • Principal Investigator: Alexander Halim Santoso
      • Sub-Investigator: Wikrama Lokapradhana
      • Sub-Investigator: Amita Pradhani
      • Sub-Investigator: William Kuswandi
      • Sub-Investigator: Alya Dwiana
      • Sub-Investigator: David Wongso
      • Sub-Investigator: Diana Dinali
      • Sub-Investigator: Muhammad Fikri Dzakwan
      • Sub-Investigator: Clement Drew
      • Sub-Investigator: Silviana Tirtasari
      • Sub-Investigator: Triyana Sari
      • Sub-Investigator: Steve Geraldo Bustam
      • Sub-Investigator: Bryan Anna Wijaya

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

The study population consists of community-dwelling adults aged 30 years and older residing in Semanan, Jakarta, Indonesia. Participants will be recruited through community-based consecutive sampling, including local residents, visitors to primary healthcare facilities, and individuals participating in community health programs. Eligible participants are those who are able to provide informed consent and undergo facial video scanning, clinical examination, and basic laboratory testing. Individuals with conditions that may interfere with rPPG signal acquisition (e.g., significant facial abnormalities), inability to remain still during measurement, severe clinical instability, or incomplete key data will be excluded. This population represents a general adult community suitable for evaluating cardiovascular risk screening tools in real-world, primary care and community settings.

Description

Inclusion Criteria:

1. Adults aged ≥30 years
2. Willing to participate and provide informed consent
3. Able to undergo face scan, clinical examination, and laboratory testing

Exclusion Criteria:

1. Facial abnormalities interfering with rPPG signal acquisition
2. Inability to remain still during measurement
3. Severe clinical instability
4. Incomplete key variables

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Community Adults Undergoing rPPG and Standard Cardiovascular Assessment; This cohort includes adults aged ≥30 years residing in Semanan, Jakarta, recruited through community-based sampling. Participants will undergo both index testing using remote photoplethysmography (rPPG) via facial video scan and reference standard assessments, including blood pressure measurement, heart rate evaluation, and laboratory testing (total cholesterol and HDL). Additional data such as age, sex, smoking status, and antihypertensive treatment will be collected. There is no intervention applied; all procedures are non-invasive and observational. The study aims to compare rPPG-derived cardiovascular parameters and risk estimates (ASCVD risk and Framingham heart age) with standard clinical measurements to assess agreement and validity.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Agreement of rPPG-Derived Blood Pressure with Standard Measurements	Assessment of agreement between systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), and pulse pressure obtained from rPPG-based facial video analysis and standard measurements using aneroid or digital sphygmomanometers. Agreement will be evaluated using Bland-Altman analysis (mean difference and limits of agreement).	Day 1
Agreement of rPPG-Derived Heart Rate and Cardiac Workload	Evaluation of agreement between heart rate and cardiac workload obtained from rPPG and those measured using standard methods (palpation and pulse oximetry). Agreement will be analyzed using Bland-Altman and correlation analysis (Pearson/Spearman).	Day 1
Concordance of rPPG-Based ASCVD Risk with Standard Risk Calculation	Assessment of agreement and concordance between ASCVD risk (%) and risk categories (low, intermediate, high) estimated using rPPG and those calculated using conventional clinical and laboratory data. Concordance will be evaluated using Cohen's Kappa and correlation analysis.	Day 1
Concordance of rPPG-Derived Framingham Heart Age	Evaluation of agreement between Framingham heart age estimated using rPPG-derived parameters and heart age calculated using standard Framingham risk equations based on clinical and laboratory variables. Agreement will be assessed using correlation and Bland-Altman analysis.	Day 1

Collaborators and Investigators

• Sponsor: Tarumanagara University
• Investigators: Study Director: David Wongso, DexWellness; Study Director: Yohanes Firmansyah, Universitas Tarumanagara; Principal Investigator: Ernawati Ernawati, Universitas Tarumanagara; Study Director: Alexander Halim Santoso, Universitas Tarumanagara; Study Director: Ratheesh Nair, Watch Your Health; Study Chair: Sri Tiarti, Universitas Tarumanagara; Study Chair: Noer Saelan Tadjudin, Universitas Tarumanagara; Principal Investigator: Clement Drew, Universitas Tarumanagara; Study Director: Zita Atzmardina, Universitas Tarumanagara; Study Director: Andria Priyana, Universitas Tarumanagara; Study Chair: Putu Tommy Yudha Sumatera Suyasa, Universitas Tarumanagara; Study Director: Kieren Nathan Wong, Monash University; Study Director: Jaydee Kirani Wong, Melbourne University; Study Chair: Meiske Yunithree Suparman, Universitas Tarumanagara

Publications and helpful links

General Publications

• Debnath U, Kim S. A comprehensive review of heart rate measurement using remote photoplethysmography and deep learning. Biomed Eng Online. 2025 Jun 20;24(1):73. doi: 10.1186/s12938-025-01405-5.
• van Es VAA, Lopata RGP, Scilingo EP, Nardelli M. Contactless Cardiovascular Assessment by Imaging Photoplethysmography: A Comparison with Wearable Monitoring. Sensors (Basel). 2023 Jan 29;23(3):1505. doi: 10.3390/s23031505.
• Shetty NS, Gaonkar M, Patel N, Vekariya N, Li P, Arora G, Arora P. PREVENT and Pooled Cohort Equations in Mortality Risk Prediction: National Health and Nutrition Examination Survey. JACC Adv. 2024 Dec 26;3(12):101372. doi: 10.1016/j.jacadv.2024.101372. eCollection 2024 Dec.
• Pandey A, Mehta A, Paluch A, Ning H, Carnethon MR, Allen NB, Michos ED, Berry JD, Lloyd-Jones DM, Wilkins JT. Performance of the American Heart Association/American College of Cardiology Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Self-reported Physical Activity Levels. JAMA Cardiol. 2021 Jun 1;6(6):690-696. doi: 10.1001/jamacardio.2021.0948.
• Nguyen QD, Odden MC, Peralta CA, Kim DH. Predicting Risk of Atherosclerotic Cardiovascular Disease Using Pooled Cohort Equations in Older Adults With Frailty, Multimorbidity, and Competing Risks. J Am Heart Assoc. 2020 Sep 15;9(18):e016003. doi: 10.1161/JAHA.119.016003. Epub 2020 Sep 2.
• Muntner P, Colantonio LD, Cushman M, Goff DC Jr, Howard G, Howard VJ, Kissela B, Levitan EB, Lloyd-Jones DM, Safford MM. Validation of the atherosclerotic cardiovascular disease Pooled Cohort risk equations. JAMA. 2014 Apr 9;311(14):1406-15. doi: 10.1001/jama.2014.2630.
• Mora S, Wenger NK, Cook NR, Liu J, Howard BV, Limacher MC, Liu S, Margolis KL, Martin LW, Paynter NP, Ridker PM, Robinson JG, Rossouw JE, Safford MM, Manson JE. Evaluation of the Pooled Cohort Risk Equations for Cardiovascular Risk Prediction in a Multiethnic Cohort From the Women's Health Initiative. JAMA Intern Med. 2018 Sep 1;178(9):1231-1240. doi: 10.1001/jamainternmed.2018.2875.
• Khera R, Pandey A, Ayers CR, Carnethon MR, Greenland P, Ndumele CE, Nambi V, Seliger SL, Chaves PHM, Safford MM, Cushman M, Xanthakis V, Vasan RS, Mentz RJ, Correa A, Lloyd-Jones DM, Berry JD, de Lemos JA, Neeland IJ. Performance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index. JAMA Netw Open. 2020 Oct 1;3(10):e2023242. doi: 10.1001/jamanetworkopen.2020.23242.
• Chin JW, Chan PHD, Chen S, Cheng CH, So RHY, Chow E, Fok BSP, Wong KL. Clinical Validation of rPPG-Enabled Contactless Pulse Rate Monitoring Software in Cardiovascular Disease Patients. Bioengineering (Basel). 2026 Feb 20;13(2):246. doi: 10.3390/bioengineering13020246.
• Allado E, Poussel M, Moussu A, Hily O, Temperelli M, Cherifi A, Saunier V, Bernard Y, Albuisson E, Chenuel B. Accurate and Reliable Assessment of Heart Rate in Real-Life Clinical Settings Using an Imaging Photoplethysmography. J Clin Med. 2022 Oct 17;11(20):6101. doi: 10.3390/jcm11206101.

Study record dates

Study Major Dates

• Study Start (Estimated): April 23, 2026
• Primary Completion (Estimated): June 30, 2026
• Study Completion (Estimated): December 30, 2026

Study Registration Dates

• First Submitted: March 24, 2026
• First Submitted That Met QC Criteria: March 24, 2026
• First Posted (Actual): March 31, 2026

Study Record Updates

• Last Update Posted (Actual): April 20, 2026
• Last Update Submitted That Met QC Criteria: April 15, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: cardiovascular risk; digital health; remote photoplethysmography; ASCVD; screening tool; rPPG; Framingham score
• Additional Relevant MeSH Terms: Pain; Neurologic Manifestations; Endocrine System Diseases; Vascular Diseases; Cardiovascular Diseases; Metabolic Diseases; Glucose Metabolism Disorders; Lipid Metabolism Disorders; Arteriosclerosis; Arterial Occlusive Diseases; Coronary Disease; Myocardial Ischemia; Chest Pain; Angina Pectoris; Pathological Conditions, Signs and Symptoms; Nutritional and Metabolic Diseases; Signs and Symptoms; Hypertension; Heart Diseases; Diabetes Mellitus; Coronary Artery Disease; Dyslipidemias; Angina, Stable
• Other Study ID Numbers: 20260325

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: De-identified individual participant data (IPD) will be shared, including demographic variables (age, sex), clinical data (blood pressure, heart rate, smoking status, antihypertensive treatment), laboratory results (total cholesterol, HDL), and rPPG-derived parameters (systolic and diastolic blood pressure, mean arterial pressure, pulse pressure, heart rate, cardiac workload, ASCVD risk, and Framingham heart age). Derived variables such as calculated ASCVD risk scores and Framingham heart age based on standard methods will also be included. All shared data will be anonymized to remove any personally identifiable information, ensuring participant confidentiality. Supporting documents such as the study protocol, statistical analysis plan, and data dictionary will also be made available upon request.
• IPD Sharing Time Frame: De-identified IPD and supporting documents will be available beginning 6 months after publication of the primary study results and will remain available for up to 5 years. Access may be extended upon reasonable request and subject to approval by the principal investigator and institutional ethics committee.
• IPD Sharing Access Criteria: Access will be granted to qualified researchers, academic institutions, and public health organizations for scientifically valid purposes. Investigators must submit a formal request outlining research objectives, analysis plan, and data protection measures. Approved users will sign a data use agreement (DUA) to ensure confidentiality and appropriate use. Shared materials will include de-identified IPD, study protocol, statistical analysis plan, and data dictionary. Data will be provided via secure electronic transfer or controlled-access repository.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; ICF; CSR

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No