ArticleBiomedical optics express2022
Rational selection of RGB channels for disease classification based on IPPG technology.
Article in Biomedical optics express, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Non-Contact Vision-Based Techniques of Vital Sign Monitoring: Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Early Osseointegration in a Sheep Tibia Model: Correlating Digital Periapical Radiograph Gray-Level and RGB-Derived Metrics with Histologic Tissue Composition.Journal of functional biomaterials · 2025Article
- A comprehensive review of heart rate measurement using remote photoplethysmography and deep learning.Biomedical engineering online · 2025Review
- Non-contact measurement of neck pulses achieved by imaging micro-motions in the neck skin.Biomedical optics express · 2023Article
- Biological Cells as Natural Biophotonic Devices: Fundamental and Applications-introduction to the feature issue.Biomedical optics express · 2022Article
- State-dependent facial pulsation asymmetry and phase asynchrony measured by imaging photoplethysmography and their coupling with contingent negative variation in migraine.Frontiers in neurologyArticle
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The green channel is usually selected as the optimal channel for vital signs monitoring in image photoplethysmography (IPPG) technology. However, some controversies arising from the different penetrability of skin tissue in visible light remain unresolved, i.e., making the optical and physiological information carried by the IPPG signals of the RGB channels inconsistent. This study clarifies that the optimal channels for different diseases are different when IPPG technology is used for disease classification. We further verified this conclusion in the classification model of heart disease and diabetes mellitus based on the random forest classification algorithm. The experimental results indicate that the green channel has a considerably excellent performance in classifying heart disease patients and the healthy with an average
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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.