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Digitization and Analysis of Capnography Using Image Processing Technique
The study of carbon dioxide expiration is called capnometry. The graphical representation of capnometry is called capnography. There is a growing interest in the usage of capnography as the usage has expanded toward the study of metabolism, circulation, lung perfusion and diffusion, quality of spont...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8585923/ https://www.ncbi.nlm.nih.gov/pubmed/34778867 http://dx.doi.org/10.3389/fdgth.2021.723204 |
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author | Vijayam, Bhuwaneswaran Supriyanto, Eko Malarvili, M. B. |
author_facet | Vijayam, Bhuwaneswaran Supriyanto, Eko Malarvili, M. B. |
author_sort | Vijayam, Bhuwaneswaran |
collection | PubMed |
description | The study of carbon dioxide expiration is called capnometry. The graphical representation of capnometry is called capnography. There is a growing interest in the usage of capnography as the usage has expanded toward the study of metabolism, circulation, lung perfusion and diffusion, quality of spontaneous respiration, and patency of airways outside of its typical usage in the anesthetic and emergency medicine field. The parameters of the capnograph could be classified as carbon dioxide (CO(2)) concentration and time points and coordinates, slopes angle, volumetric studies, and functional transformation of wave data. Up to date, there is no gold standard device for the calculation of the capnographic parameters. Capnography digitization using the image processing technique could serve as an option. From the algorithm we developed, eight identical breath waves were tested by four investigators. The values of the parameters chosen showed no significant difference between investigators. Although there were no significant differences between any of the parameters tested, there were a few related parameters that were not calculable. Further testing after refinement of the algorithm could be done. As more capnographic parameters are being derived and rediscovered by clinicians and researchers alike for both lung and non-lung-related diseases, there is a dire need for data analysis and interpretation. Although the proposed algorithm still needs minor refinements and further large-scale testing, we proposed that the digitization of the capnograph via image processing technique could serve as an intellectual option as it is fast, convenient, easy to use, and efficient. |
format | Online Article Text |
id | pubmed-8585923 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85859232021-11-13 Digitization and Analysis of Capnography Using Image Processing Technique Vijayam, Bhuwaneswaran Supriyanto, Eko Malarvili, M. B. Front Digit Health Digital Health The study of carbon dioxide expiration is called capnometry. The graphical representation of capnometry is called capnography. There is a growing interest in the usage of capnography as the usage has expanded toward the study of metabolism, circulation, lung perfusion and diffusion, quality of spontaneous respiration, and patency of airways outside of its typical usage in the anesthetic and emergency medicine field. The parameters of the capnograph could be classified as carbon dioxide (CO(2)) concentration and time points and coordinates, slopes angle, volumetric studies, and functional transformation of wave data. Up to date, there is no gold standard device for the calculation of the capnographic parameters. Capnography digitization using the image processing technique could serve as an option. From the algorithm we developed, eight identical breath waves were tested by four investigators. The values of the parameters chosen showed no significant difference between investigators. Although there were no significant differences between any of the parameters tested, there were a few related parameters that were not calculable. Further testing after refinement of the algorithm could be done. As more capnographic parameters are being derived and rediscovered by clinicians and researchers alike for both lung and non-lung-related diseases, there is a dire need for data analysis and interpretation. Although the proposed algorithm still needs minor refinements and further large-scale testing, we proposed that the digitization of the capnograph via image processing technique could serve as an intellectual option as it is fast, convenient, easy to use, and efficient. Frontiers Media S.A. 2021-10-29 /pmc/articles/PMC8585923/ /pubmed/34778867 http://dx.doi.org/10.3389/fdgth.2021.723204 Text en Copyright © 2021 Vijayam, Supriyanto and Malarvili. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Digital Health Vijayam, Bhuwaneswaran Supriyanto, Eko Malarvili, M. B. Digitization and Analysis of Capnography Using Image Processing Technique |
title | Digitization and Analysis of Capnography Using Image Processing Technique |
title_full | Digitization and Analysis of Capnography Using Image Processing Technique |
title_fullStr | Digitization and Analysis of Capnography Using Image Processing Technique |
title_full_unstemmed | Digitization and Analysis of Capnography Using Image Processing Technique |
title_short | Digitization and Analysis of Capnography Using Image Processing Technique |
title_sort | digitization and analysis of capnography using image processing technique |
topic | Digital Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8585923/ https://www.ncbi.nlm.nih.gov/pubmed/34778867 http://dx.doi.org/10.3389/fdgth.2021.723204 |
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