Air–Oxygen Blenders for Mechanical Ventilators: A Literature Review
Respiratory diseases are one of the most common causes of death in the world and this recent COVID-19 pandemic is a key example. Problems such as infections, in general, affect many people and depending on the form of transmission they can spread throughout the world and weaken thousands of people....
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Format: | Article |
Language: | English |
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MDPI AG
2022-03-01
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Series: | Sensors |
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Online Access: | https://www.mdpi.com/1424-8220/22/6/2182 |
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author | Gabryel F. Soares Otacílio M. Almeida José W. M. Menezes Sergei S. A. Kozlov Joel J. P. C. Rodrigues |
author_facet | Gabryel F. Soares Otacílio M. Almeida José W. M. Menezes Sergei S. A. Kozlov Joel J. P. C. Rodrigues |
author_sort | Gabryel F. Soares |
collection | DOAJ |
description | Respiratory diseases are one of the most common causes of death in the world and this recent COVID-19 pandemic is a key example. Problems such as infections, in general, affect many people and depending on the form of transmission they can spread throughout the world and weaken thousands of people. Two examples are severe acute respiratory syndrome and the recent coronavirus disease. These diseases have mild and severe forms, in which patients gravely affected need ventilatory support. The equipment that serves as a basis for operation of the mechanical ventilator is the air–oxygen blender, responsible for carrying out the air–oxygen mixture in the proper proportions ensuring constant supply. New blender models are described in the literature together with applications of control techniques, such as Proportional, Integrative and Derivative (PID); Fuzzy; and Adaptive. The results obtained from the literature show a significant improvement in patient care when using automatic controls instead of manual adjustment, increasing the safety and accuracy of the treatment. This study presents a deep review of the state of the art in air–oxygen benders, identifies the most relevant characteristics, performs a comparison study considering the most relevant available solutions, and identifies open research directions in the topic. |
first_indexed | 2024-03-09T12:42:08Z |
format | Article |
id | doaj.art-b1362b2e4dfb4994bc88b87419b2b9ec |
institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-03-09T12:42:08Z |
publishDate | 2022-03-01 |
publisher | MDPI AG |
record_format | Article |
series | Sensors |
spelling | doaj.art-b1362b2e4dfb4994bc88b87419b2b9ec2023-11-30T22:17:22ZengMDPI AGSensors1424-82202022-03-01226218210.3390/s22062182Air–Oxygen Blenders for Mechanical Ventilators: A Literature ReviewGabryel F. Soares0Otacílio M. Almeida1José W. M. Menezes2Sergei S. A. Kozlov3Joel J. P. C. Rodrigues4Department of Electrical Engineering, Universidade Federal do Piauí, Teresina 64049-550, BrazilDepartment of Electrical Engineering, Universidade Federal do Piauí, Teresina 64049-550, BrazilDepartament of Telematics, Federal Institute of Ceará, Fortaleza 60040-531, BrazilPhotonics and Optoinformatics Faculty, ITMO University, 191002 St. Petersburg, RussiaPhotonics and Optoinformatics Faculty, ITMO University, 191002 St. Petersburg, RussiaRespiratory diseases are one of the most common causes of death in the world and this recent COVID-19 pandemic is a key example. Problems such as infections, in general, affect many people and depending on the form of transmission they can spread throughout the world and weaken thousands of people. Two examples are severe acute respiratory syndrome and the recent coronavirus disease. These diseases have mild and severe forms, in which patients gravely affected need ventilatory support. The equipment that serves as a basis for operation of the mechanical ventilator is the air–oxygen blender, responsible for carrying out the air–oxygen mixture in the proper proportions ensuring constant supply. New blender models are described in the literature together with applications of control techniques, such as Proportional, Integrative and Derivative (PID); Fuzzy; and Adaptive. The results obtained from the literature show a significant improvement in patient care when using automatic controls instead of manual adjustment, increasing the safety and accuracy of the treatment. This study presents a deep review of the state of the art in air–oxygen benders, identifies the most relevant characteristics, performs a comparison study considering the most relevant available solutions, and identifies open research directions in the topic.https://www.mdpi.com/1424-8220/22/6/2182blenderrespiratory diseasescontrolInternet of Things (IoT)fraction of inspired oxygenoxygen saturation |
spellingShingle | Gabryel F. Soares Otacílio M. Almeida José W. M. Menezes Sergei S. A. Kozlov Joel J. P. C. Rodrigues Air–Oxygen Blenders for Mechanical Ventilators: A Literature Review Sensors blender respiratory diseases control Internet of Things (IoT) fraction of inspired oxygen oxygen saturation |
title | Air–Oxygen Blenders for Mechanical Ventilators: A Literature Review |
title_full | Air–Oxygen Blenders for Mechanical Ventilators: A Literature Review |
title_fullStr | Air–Oxygen Blenders for Mechanical Ventilators: A Literature Review |
title_full_unstemmed | Air–Oxygen Blenders for Mechanical Ventilators: A Literature Review |
title_short | Air–Oxygen Blenders for Mechanical Ventilators: A Literature Review |
title_sort | air oxygen blenders for mechanical ventilators a literature review |
topic | blender respiratory diseases control Internet of Things (IoT) fraction of inspired oxygen oxygen saturation |
url | https://www.mdpi.com/1424-8220/22/6/2182 |
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