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

NCT07502703 | Not Yet Recruiting DMC

• 1 other identifier: 20260325
• Study Type: observational
• Target: 300
• Locations: 1 country
• Sites: 1

Brief Summary

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

Conditions

Dyslipidemia; Angina (Stable); Coronary Artery Disease (CAD); Heart Disease; Hypertension; Diabetes (DM)

Keywords

remote photoplethysmography; rPPG; cardiovascular risk; ASCVD; Framingham score; digital health; screening tool

Outcome Measures

Primary Outcomes (4)

• 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

Study Arms (1)

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.

Eligibility Criteria

• Age: 30 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• 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.

You may qualify if:

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

You may not qualify if:

• Facial abnormalities interfering with rPPG signal acquisition
• Inability to remain still during measurement
• Severe clinical instability
• Incomplete key variables

Sponsors & Collaborators

• Tarumanagara University: lead

Study Sites (1)

Kelurahan Semanan

Jakarta, Jakarta Special Capital Region, Indonesia

Location

Related Publications (10)

• 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.

  PMID: 36772543 BACKGROUND

• 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.

  PMID: 39817066 BACKGROUND

• 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.

  PMID: 40542336 BACKGROUND

• 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.

  PMID: 33909016 BACKGROUND

• 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.

  PMID: 32875939 BACKGROUND

• 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.

  PMID: 24682252 BACKGROUND

• 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.

  PMID: 30039172 BACKGROUND

• 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.

  PMID: 33119108 BACKGROUND

• 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.

  PMID: 41749785 BACKGROUND

• 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.

  PMID: 36294422 BACKGROUND

Biospecimen

Retention: SAMPLES WITHOUT DNA

Blood samples will be collected from participants for routine biochemical analysis, specifically for the measurement of total cholesterol and high-density lipoprotein (HDL) levels. These samples are obtained using point-of-care testing (POCT) and/or standard clinical laboratory methods. No genetic testing or DNA extraction will be performed. Any remaining biospecimens, if temporarily stored for quality control or repeat analysis, will not be used for future research purposes and will be disposed of according to standard laboratory and biosafety protocols.

MeSH Terms

Conditions

Dyslipidemias; Angina, Stable; Coronary Artery Disease; Heart Diseases; Hypertension; Diabetes Mellitus

Condition Hierarchy (Ancestors)

Lipid Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Angina Pectoris; Myocardial Ischemia; Cardiovascular Diseases; Vascular Diseases; Chest Pain; Pain; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Coronary Disease; Arteriosclerosis; Arterial Occlusive Diseases; Glucose Metabolism Disorders; Endocrine System Diseases

Study Officials

• Ernawati Ernawati

  Universitas Tarumanagara

  PRINCIPAL INVESTIGATOR

• Yohanes Firmansyah

  Universitas Tarumanagara

  STUDY DIRECTOR

• Alexander Halim Santoso

  Universitas Tarumanagara

  STUDY DIRECTOR

• David Wongso

  DexWellness

  STUDY DIRECTOR

• Ratheesh Nair

  Watch Your Health

  STUDY DIRECTOR

• Sri Tiarti

  Universitas Tarumanagara

  STUDY CHAIR

• Noer Saelan Tadjudin

  Universitas Tarumanagara

  STUDY CHAIR

• Clement Drew

  Universitas Tarumanagara

  PRINCIPAL INVESTIGATOR

• Zita Atzmardina

  Universitas Tarumanagara

  STUDY DIRECTOR

• Andria Priyana

  Universitas Tarumanagara

  STUDY DIRECTOR

• Putu Tommy Yudha Sumatera Suyasa

  Universitas Tarumanagara

  STUDY CHAIR

• Kieren Nathan Wong

  Monash University

  STUDY DIRECTOR

• Jaydee Kirani Wong

  Melbourne University

  STUDY DIRECTOR

• Meiske Yunithree Suparman

  Universitas Tarumanagara

  STUDY CHAIR

Central Study Contacts

Alexander Halim Santoso, MD

CONTACT

+6281381606869; alexanders@fk.untar.ac.id

Ernawati Ernawati, Dr

CONTACT

+6281389048199; ernawati@fk.untar.ac.id

Study Design

• Study Type: observational
• Observational Model: ECOLOGIC OR COMMUNITY
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: March 24, 2026
• First Posted: March 31, 2026
• Study Start: April 23, 2026
• Primary Completion (Estimated): June 30, 2026
• Study Completion (Estimated): December 30, 2026
• Last Updated: April 20, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, ICF, CSR
• 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.
• 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.

Locations

ID (1)