Evidence map›Paper›PMID 41749785›Full record

ArticleBioengineering (Basel, Switzerland)2026

Clinical Validation of rPPG-Enabled Contactless Pulse Rate Monitoring Software in Cardiovascular Disease Patients.

Jing Wei Chin, Po Him David Chan, Shutao Chen, Chun Hong Cheng, Richard H Y So, Elaine Chow, Benny S P Fok, Kwan Long Wong

Registry-linked trialAbstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07502703 (Validation of Remote Photoplethysmography), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07502703 not yet recruitingnot on this map

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

TypeobservationalSponsorTarumanagara UniversityRan2026 to 2026Enrolled300ConditionsDyslipidemia, Angina (Stable), Coronary Artery Disease (CAD), Heart Disease
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jing Wei ChinDepartment of Clinical AI, PanopticAI, Hong Kong SAR, China.ORCID 0000-0001-9406-5224
Po Him David ChanDepartment of Clinical AI, PanopticAI, Hong Kong SAR, China.
Shutao ChenDepartment of Clinical AI, PanopticAI, Hong Kong SAR, China.
Chun Hong ChengDepartment of Clinical AI, PanopticAI, Hong Kong SAR, China.
Richard H Y SoDepartment of Industrial Engineering and Decision Analytics, The Hong Kong University of Science and Technology, Hong Kong SAR, China.
Elaine ChowPhase 1 Clinical Trial Centre, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR, China.ORCID 0000-0002-4147-3387
Benny S P FokPhase 1 Clinical Trial Centre, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR, China.
Kwan Long WongDepartment of Clinical AI, PanopticAI, Hong Kong SAR, China.ORCID 0000-0002-5847-9734

Funding

HKUST's Sports Development Fund SSTRG24EG09Hong Kong Science and Technology Parks Corporation MedTech Co-create Funding Scheme MTCC-010-C7Innovation Technology Commission of Hong Kong TSSSU/HKUST/21/10 and PsH/053/22
6 · The paper itself

Abstract

backgroundCardiovascular disease (CVD) is the leading cause of mortality worldwide, creating demand for continuous, unobtrusive monitoring solutions. This clinical validation evaluates the accuracy of remote photoplethysmography (rPPG), a contactless method using camera video, for measuring pulse rate (PR) in patients with CVD.

methodsWe enrolled 50 adults with confirmed CVD at a clinical trial center. In a 6 min rested session, synchronized facial video (under controlled lighting), electrocardiogram (ECG), and photoplethysmography (PPG) signals were recorded. PR was derived from 25 s video segments using rPPG-enabled software and compared to ECG-derived PR via regression and Bland-Altman analysis.

resultsData from 47 participants (

conclusionThe rPPG method provides accurate, contactless PR monitoring in CVD patients, supporting its potential for remote patient monitoring and early deterioration detection. Future work will validate rPPG for irregular rhythms, additional vital signs, and diverse cohorts to strengthen clinical robustness for cardiometabolic risk assessment.

Indexed as

cardiovascular diseaseclinical validationcontactless pulse rate monitoringremote photoplethysmography (rPPG)

Identifiers

PMID41749785
PMCPMC12938449

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.