Self-Regulating Adaptive Controller for Oxygen Support to Severe Respiratory Distress Patients and Human Respiratory System Modeling

Uncontrolled breathing is the most critical and challenging situation for a healthcare person to patients. It may be due to simple cough/cold/critical disease to severe respiratory infection of the patients and resulting directly impacts the lungs and damages the alveoli which leads to shortness of...

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Main Authors: Indrajit Naskar, Arabinda Kumar Pal, Nandan Kumar Jana
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Diagnostics
Subjects:
Online Access:https://www.mdpi.com/2075-4418/13/5/967
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author Indrajit Naskar
Arabinda Kumar Pal
Nandan Kumar Jana
author_facet Indrajit Naskar
Arabinda Kumar Pal
Nandan Kumar Jana
author_sort Indrajit Naskar
collection DOAJ
description Uncontrolled breathing is the most critical and challenging situation for a healthcare person to patients. It may be due to simple cough/cold/critical disease to severe respiratory infection of the patients and resulting directly impacts the lungs and damages the alveoli which leads to shortness of breath and also impairs the oxygen exchange. The prolonged respiratory failure in such patients may cause death. In this condition, supportive care of the patients by medicine and a controlled oxygen supply is only the emergency treatment. In this paper, as a part of emergency support, the intelligent set-point modulated fuzzy PI-based model reference adaptive controller (SFPIMRAC) is delineated to control the oxygen supply to uncomforted breathing or respiratory infected patients. The effectiveness of the model reference adaptive controller (MRAC) is enhanced by assimilating the worthiness of fuzzy-based tuning and set-point modulation strategies. Since then, different conventional and intelligent controllers have attempted to regulate the supply of oxygen to respiratory distress patients. To overcome the limitations of previous techniques, researchers created the set-point modulated fuzzy PI-based model reference adaptive controller, which can react instantly to changes in oxygen demand in patients. Nonlinear mathematical formulations of the respiratory system and the exchange of oxygen with time delay are modeled and simulated for study. The efficacy of the proposed SFPIMRAC is tested, with transport delay and set-point variations in the devised respiratory model.
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spelling doaj.art-e1274eb50e584a4faf70441d20d0aaf12023-11-17T07:30:38ZengMDPI AGDiagnostics2075-44182023-03-0113596710.3390/diagnostics13050967Self-Regulating Adaptive Controller for Oxygen Support to Severe Respiratory Distress Patients and Human Respiratory System ModelingIndrajit Naskar0Arabinda Kumar Pal1Nandan Kumar Jana2Heritage Institute of Technology, Kolkata 700107, WB, IndiaHeritage Institute of Technology, Kolkata 700107, WB, IndiaHeritage Institute of Technology, Kolkata 700107, WB, IndiaUncontrolled breathing is the most critical and challenging situation for a healthcare person to patients. It may be due to simple cough/cold/critical disease to severe respiratory infection of the patients and resulting directly impacts the lungs and damages the alveoli which leads to shortness of breath and also impairs the oxygen exchange. The prolonged respiratory failure in such patients may cause death. In this condition, supportive care of the patients by medicine and a controlled oxygen supply is only the emergency treatment. In this paper, as a part of emergency support, the intelligent set-point modulated fuzzy PI-based model reference adaptive controller (SFPIMRAC) is delineated to control the oxygen supply to uncomforted breathing or respiratory infected patients. The effectiveness of the model reference adaptive controller (MRAC) is enhanced by assimilating the worthiness of fuzzy-based tuning and set-point modulation strategies. Since then, different conventional and intelligent controllers have attempted to regulate the supply of oxygen to respiratory distress patients. To overcome the limitations of previous techniques, researchers created the set-point modulated fuzzy PI-based model reference adaptive controller, which can react instantly to changes in oxygen demand in patients. Nonlinear mathematical formulations of the respiratory system and the exchange of oxygen with time delay are modeled and simulated for study. The efficacy of the proposed SFPIMRAC is tested, with transport delay and set-point variations in the devised respiratory model.https://www.mdpi.com/2075-4418/13/5/967respiratory distress patientrespiratory failuremodel reference adaptive controlset-point modulated fuzzy-based controlmathematical modeling of the human respiratory system with exchange of oxygen
spellingShingle Indrajit Naskar
Arabinda Kumar Pal
Nandan Kumar Jana
Self-Regulating Adaptive Controller for Oxygen Support to Severe Respiratory Distress Patients and Human Respiratory System Modeling
Diagnostics
respiratory distress patient
respiratory failure
model reference adaptive control
set-point modulated fuzzy-based control
mathematical modeling of the human respiratory system with exchange of oxygen
title Self-Regulating Adaptive Controller for Oxygen Support to Severe Respiratory Distress Patients and Human Respiratory System Modeling
title_full Self-Regulating Adaptive Controller for Oxygen Support to Severe Respiratory Distress Patients and Human Respiratory System Modeling
title_fullStr Self-Regulating Adaptive Controller for Oxygen Support to Severe Respiratory Distress Patients and Human Respiratory System Modeling
title_full_unstemmed Self-Regulating Adaptive Controller for Oxygen Support to Severe Respiratory Distress Patients and Human Respiratory System Modeling
title_short Self-Regulating Adaptive Controller for Oxygen Support to Severe Respiratory Distress Patients and Human Respiratory System Modeling
title_sort self regulating adaptive controller for oxygen support to severe respiratory distress patients and human respiratory system modeling
topic respiratory distress patient
respiratory failure
model reference adaptive control
set-point modulated fuzzy-based control
mathematical modeling of the human respiratory system with exchange of oxygen
url https://www.mdpi.com/2075-4418/13/5/967
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