Evidence map›Paper›PMID 37237595›Full record

ArticleBioengineering (Basel, Switzerland)2023

Using Contactless Facial Image Recognition Technology to Detect Blood Oxygen Saturation.

Jui-Chuan Cheng, Tzung-Shiarn Pan, Wei-Cheng Hsiao, Wei-Hong Lin, Yan-Liang Liu, Te-Jen Su, Shih-Ming Wang

Open access · goldAbstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 31% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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

7 authors at 3 institutions in 1 country.

Jui-Chuan ChengDepartment of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80782, Taiwan.
Tzung-Shiarn PanDepartment of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80782, Taiwan.
Wei-Cheng HsiaoDivision of Gastroenterology (General Medicine), Department of Internal Medicine, Yuan's General Hospital, No. 162, Cheng Kung 1st Rd., Lingya District, Kaohsiung 80249, Taiwan.
Wei-Hong LinDepartment of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80782, Taiwan.
Yan-Liang LiuDepartment of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80782, Taiwan.
Te-Jen SuDepartment of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80782, Taiwan.ORCID 0000-0001-7241-0576
Shih-Ming WangDepartment of Computer Science and Information Engineering, Cheng Shiu University, Kaohsiung 833, Taiwan.ORCID 0000-0002-8666-7687
National Kaohsiung University of Science and TechnologyCheng Shiu University · TWYuan's General Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the outbreak of COVID-19, as of January 2023, there have been over 670 million cases and more than 6.8 million deaths worldwide. Infections can cause inflammation in the lungs and decrease blood oxygen levels, which can lead to breathing difficulties and endanger life. As the situation continues to escalate, non-contact machines are used to assist patients at home to monitor their blood oxygen levels without encountering others. This paper uses a general network camera to capture the forehead area of a person's face, using the RPPG (remote photoplethysmography) principle. Then, image signal processing of red and blue light waves is carried out. By utilizing the principle of light reflection, the standard deviation and mean are calculated, and the blood oxygen saturation is computed. Finally, the effect of illuminance on the experimental values is discussed. The experimental results of this paper were compared with a blood oxygen meter certified by the Ministry of Health and Welfare in Taiwan, and the experimental results had only a maximum error of 2%, which is better than the 3% to 5% error rates in other studies The measurement time was only 30 s, which is better than the one minute reported using similar equipment in other studies. Therefore, this paper not only saves equipment expenses but also provides convenience and safety for those who need to monitor their blood oxygen levels at home. Future applications can combine the SpO2 detection software with camera-equipped devices such as smartphones and laptops. The public can detect SpO2 on their own mobile devices, providing a convenient and effective tool for personal health management.

Indexed as

blood oxygen saturationfacial recognitionnon-contact detection

Identifiers

PMID37237595
PMCPMC10215142
OpenAlexW4367051301

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.