Evidence map›Paper›PMID 35582520›Full record

ArticleIEEE internet of things journal2022

Internet of Things Framework for Oxygen Saturation Monitoring in COVID-19 Environment.

Rahul Saha, Gulshan Kumar, Neeraj Kumar, Tai-Hoon Kim, Tannishtha Devgun, Reji Thomas, Ahmed Barnawi

Open access · greenAbstract read
In one paragraph

Article in IEEE internet of things journal, 2022. 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
2.2field-weighted citation impact, top 12% 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, 20 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 5 institutions in 5 countries.

Rahul SahaSchool of Computer Science and EngineeringLovely Professional University Phagwara 144411 India.ORCID https://orcid.org/0000-0003-3921-9512
Gulshan KumarSchool of Computer Science and EngineeringLovely Professional University Phagwara 144411 India.ORCID https://orcid.org/0000-0003-0026-149X
Neeraj KumarDepartment of Computer Science and EngineeringThapar University Patiala 147004 India.ORCID https://orcid.org/0000-0002-3020-3947
Tai-Hoon KimKonkuk University (Glocal Campus) Seoul 27478 South Korea.ORCID https://orcid.org/0000-0003-0117-8102
Tannishtha DevgunNokia Solutions and Networks Private Ltd. Karnal 132001 India.
Reji ThomasSchool of Chemical Engineering and Physical SciencesLovely Professional University Phagwara 144411 India.ORCID https://orcid.org/0000-0003-3588-2317
Ahmed BarnawiFaculty of Computing and Information TechnologyKing Abdulaziz University Jeddah 21589 Saudi Arabia.ORCID https://orcid.org/0000-0003-0516-8331
Lovely Professional University · INAsia University · TWDNA Solutions (United States) · USKing Abdulaziz University · SAKonkuk University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pandemic/epidemic of COVID-19 has affected people worldwide. A huge number of lives succumbed to death due to the sudden outbreak of this corona virus infection. The specified symptoms of COVID-19 detection are very common like normal flu; asymptomatic version of COVID-19 has become a critical issue. Therefore, as a precautionary measurement, the oxygen level needs to be monitored by every individual if no other critical condition is found. It is not the only parameter for COVID-19 detection but, as per the suggestions by different medical organizations such as the World Health Organization, it is better to use oximeter to monitor the oxygen level in probable patients as a precaution. People are using the oximeters personally; however, not having any clue or guidance regarding the measurements obtained. Therefore, in this article, we have shown a framework of oxygen level monitoring and severity calculation and probabilistic decision of being a COVID-19 patient. This framework is also able to maintain the privacy of patient information and uses probabilistic classification to measure the severity. Results are measured based on latency of blockchain creation and overall response, throughput, detection, and severity accuracy. The analysis finds the solution efficient and significant in the Internet of Things framework for the present health hazard in our world.

Indexed as

CovidfoghealthcareInternetInternet of Things (IoT)medicalmonitoringprivacy

Identifiers

PMID35582520
PMCPMC8956365
OpenAlexW3189814983

What OpenQuestion holds

Textmetadata
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.