ArticleJournal of clinical medicine2022
Remote Photoplethysmography Is an Accurate Method to Remotely Measure Respiratory Rate: A Hospital-Based Trial.
Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07491978 (Development and Multicenter Validation of an AI-Based Remote Photoplethysmography), which is not on this map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Development and Multicenter Validation of an AI-Based Remote Photoplethysmography (rPPG) Facial Scan for Multimodal Health Assessment: Agreement With Clinical, Laboratory, and Psychological Parameters in an Urban Population
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Non-Contact Vision-Based Techniques of Vital Sign Monitoring: Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Motion-Based Confidence Score to Support the Practical Application of rPPG Methods in Health Monitoring.Journal of medical systems · 2026Article
- Article
- Seconds Matter: Rapid Non-Contact Monitoring of Heart and Respiratory Rate from Face Videos.Sensors (Basel, Switzerland) · 2026Article
- Smart Healthcare at Home: A Review of AI-Enabled Wearables and Diagnostics Through the Lens of the Pi-CON Methodology.Sensors (Basel, Switzerland) · 2025Review
- Remote photoplethysmography for health assessment: a review informed by IntelliProve technology.Frontiers in digital health · 2025Review
- Hybrid Deep Learning-Based Enhanced Occlusion Segmentation in PICU Patient Monitoring.IEEE open journal of engineering in medicine and biology · 2025Article
- Introducing the Pi-CON Methodology to Overcome Usability Deficits during Remote Patient Monitoring.Sensors (Basel, Switzerland) · 2024Review
- Challenges and prospects of visual contactless physiological monitoring in clinical study.NPJ digital medicine · 2023Review
- Vitality surveillance at distance using thin-film tandem-like narrowband near-infrared photodiodes with light-enhanced responsivity.Science advances · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Remote photoplethysmography imaging (rPPG) is a new solution proposed to measure vital signs, such as respiratory rate (RR) in teleconsultation, by using a webcam. The results, presented here, aim at evaluating the accuracy of such remote measurement methods, compared with existing measurement methods, in a real-life clinical setting. For each patient, measurement of RR, using the standard system (control), has been carried out concomitantly with the experimental system. A 60-s time frame was used for the measurements made by our rPPG system. Age, gender, BMI, and skin phototype were collected. We performed the intraclass correlation coefficient and Bland-Altman plot to analyze the accuracy and precision of the rPPG algorithm readings. Measurements of RR, using the two methods, have been realized on 963 patients. Comparison of the two techniques showed excellent agreement (96.0%), with most of the patients (n = 924-standard patients) being in the confidence interval of 95% in Bland-Altman plotting. There were no significant differences between standard patients and outlier patients for demographic and clinical characteristics. This study indicates a good agreement between the rPPG system and the control, thus allowing clinical use of this remote assessment of the respiratory rate.
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Registered trials
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.