Analysis of parameters affecting blood oxygen saturation and modeling of fuzzy logic system for inspired oxygen prediction.
Data collection
Fuzzy logic
Mechanical ventilation
Oxygen saturation
Journal
Computer methods and programs in biomedicine
ISSN: 1872-7565
Titre abrégé: Comput Methods Programs Biomed
Pays: Ireland
ID NLM: 8506513
Informations de publication
Date de publication:
Jul 2019
Jul 2019
Historique:
received:
11
12
2018
revised:
21
03
2019
accepted:
12
04
2019
entrez:
16
6
2019
pubmed:
16
6
2019
medline:
8
1
2020
Statut:
ppublish
Résumé
Fraction of Inspired Oxygen is one of the arbitrary set ventilator parameters which has critical influence on the concentration of blood oxygen. Normally mechanical ventilators providing respiratory assistance are tuned manually to supply required inspired oxygen to keep the oxygen saturation at the desired level. Maintaining oxygen saturation in the desired limit is so vital since excess supply of inspired oxygen leads to hypercapnia and respiratory acidosis which lead to increased risk in cell damage and death. On the other side a sudden drop in oxygen saturation will lead to severe cardiac arrest and seizure. Hence intelligent real time control of blood oxygen level saturation is highly significant for patients in intensive care units. This paper gives statistical pair wise analysis for finding out deeply correlated physiological parameters from clinical data for fixing fuzzy variables. An advisory fuzzy controller using Mamdani model is developed with R programming to predict FiO Fuzzy variables for the fuzzy model is fixed using 75% of the clinical data collected. Remaining 25% of the data is used for checking the system. Compared the predictive output of the system with physicians' decisions and found to be accurate with less than five percentage error. Based on the comparison the system is proved to be effective and can be used as assist mode for physicians for effective decision making.
Sections du résumé
BACKGROUND AND OBJECTIVE
OBJECTIVE
Fraction of Inspired Oxygen is one of the arbitrary set ventilator parameters which has critical influence on the concentration of blood oxygen. Normally mechanical ventilators providing respiratory assistance are tuned manually to supply required inspired oxygen to keep the oxygen saturation at the desired level. Maintaining oxygen saturation in the desired limit is so vital since excess supply of inspired oxygen leads to hypercapnia and respiratory acidosis which lead to increased risk in cell damage and death. On the other side a sudden drop in oxygen saturation will lead to severe cardiac arrest and seizure. Hence intelligent real time control of blood oxygen level saturation is highly significant for patients in intensive care units.
METHODS
METHODS
This paper gives statistical pair wise analysis for finding out deeply correlated physiological parameters from clinical data for fixing fuzzy variables. An advisory fuzzy controller using Mamdani model is developed with R programming to predict FiO
RESULTS
RESULTS
Fuzzy variables for the fuzzy model is fixed using 75% of the clinical data collected. Remaining 25% of the data is used for checking the system. Compared the predictive output of the system with physicians' decisions and found to be accurate with less than five percentage error.
CONCLUSIONS
CONCLUSIONS
Based on the comparison the system is proved to be effective and can be used as assist mode for physicians for effective decision making.
Identifiants
pubmed: 31200910
pii: S0169-2607(18)31783-8
doi: 10.1016/j.cmpb.2019.04.014
pii:
doi:
Substances chimiques
Oxygen
S88TT14065
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
43-49Informations de copyright
Copyright © 2019 Elsevier B.V. All rights reserved.