Evidence map›Paper›PMID 34833650›Full record

ArticleSensors (Basel, Switzerland)2021

Non-Contact Spirometry Using a Mobile Thermal Camera and AI Regression.

Luay Fraiwan, Natheer Khasawneh, Khaldon Lweesy, Mennatalla Elbalki, Amna Almarzooqi, Nada Abu Hamra

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Special Issue "Computer Aided Diagnosis Sensors".Sensors (Basel, Switzerland) · 2022
    Article
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

6 authors.

Luay FraiwanDepartment of Electrical, Computer and Biomedical Engineering, Abu Dhabi University, Abu Dhabi 55991, United Arab Emirates.
Natheer KhasawnehDepartment of Software Engineering, Jordan University of Science and Technology, Irbid 2210, Jordan.
Khaldon LweesyDepartment of Biomedical Engineering, Jordan University of Science and Technology, Irbid 2210, Jordan.
Mennatalla ElbalkiDepartment of Electrical, Computer and Biomedical Engineering, Abu Dhabi University, Abu Dhabi 55991, United Arab Emirates.
Amna AlmarzooqiDepartment of Electrical, Computer and Biomedical Engineering, Abu Dhabi University, Abu Dhabi 55991, United Arab Emirates.
Nada Abu HamraDepartment of Electrical, Computer and Biomedical Engineering, Abu Dhabi University, Abu Dhabi 55991, United Arab Emirates.

Funding

Abu Dhabi University 19300518
6 · The paper itself

Abstract

Non-contact physiological measurements have been under investigation for many years, and among these measurements is non-contact spirometry, which could provide acute and chronic pulmonary disease monitoring and diagnosis. This work presents a feasibility study for non-contact spirometry measurements using a mobile thermal imaging system. Thermal images were acquired from 19 subjects for measuring the respiration rate and the volume of inhaled and exhaled air. A mobile application was built to measure the respiration rate and export the respiration signal to a personal computer. The mobile application acquired thermal video images at a rate of nine frames/second and the OpenCV library was used for localization of the area of interest (nose and mouth). Artificial intelligence regressors were used to predict the inhalation and exhalation air volume. Several regressors were tested and four of them showed excellent performance: random forest, adaptive boosting, gradient boosting, and decision trees. The latter showed the best regression results, with an R-square value of 0.9998 and a mean square error of 0.0023. The results of this study showed that non-contact spirometry based on a thermal imaging system is feasible and provides all the basic measurements that the conventional spirometers support.

Indexed as

Artificial IntelligenceRespirationExhalationHumansRespiratory RateSpirometryartificial intelligence regressionnon-contact spirometryrespiration rate mobile applicationrespiration signalthermal camera

Identifiers

PMID34833650
PMCPMC8624693

What OpenQuestion holds

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LicenceCC BY
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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.