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

Official title

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

Overview

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.

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.

Primary outcome measures

• Agreement of rPPG-Derived Blood Pressure with Standard Measurements [Time frame: Day 1]
• Agreement of rPPG-Derived Heart Rate and Cardiac Workload [Time frame: Day 1]
• Concordance of rPPG-Based ASCVD Risk with Standard Risk Calculation [Time frame: Day 1]
• Concordance of rPPG-Derived Framingham Heart Age [Time frame: Day 1]

Eligibility criteria

Inclusion criteria

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

Exclusion criteria

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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model

Ecologic or community

Study locations

Indonesia · 1 center

• Kelurahan Semanan — Jakarta

Publications

• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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/jamanet PMID 33119108

Identifiers

NCT: NCT07502703 · 20260325

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗