AnesthesiaGUIDE: a MATLAB tool to control the anesthesia

Abstract The goals of this paper are: (a) to investigate adaptive and fractional-order adaptive control algorithms for an automatic anesthesia process, using a closed-loop system, and (b) to develop an easy-to-use tool for MATLAB/Simulink to facilitate simulations for users with less knowledge about...

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Autores principales:	Simona Coman, Diana Iosif
Formato:	article
Lenguaje:	EN
Publicado:	Springer 2021
Materias:	AnesthesiaGUIDE tool PI adaptive control PIλ fractional-order adaptive control, Patient model Science Q Technology T
Acceso en línea:	https://doaj.org/article/d559f7e663954425bbbd1064bd372c16
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spelling	oai:doaj.org-article:d559f7e663954425bbbd1064bd372c162021-12-05T12:10:02ZAnesthesiaGUIDE: a MATLAB tool to control the anesthesia10.1007/s42452-021-04885-x2523-39632523-3971https://doaj.org/article/d559f7e663954425bbbd1064bd372c162021-12-01T00:00:00Zhttps://doi.org/10.1007/s42452-021-04885-xhttps://doaj.org/toc/2523-3963https://doaj.org/toc/2523-3971Abstract The goals of this paper are: (a) to investigate adaptive and fractional-order adaptive control algorithms for an automatic anesthesia process, using a closed-loop system, and (b) to develop an easy-to-use tool for MATLAB/Simulink to facilitate simulations for users with less knowledge about anesthesia and adaptive control. A model reference adaptive control structure was chosen for the entire system. First of all, to control the patient’s state during the surgery process, the patient mathematical model is useful, or even required for simulation studies. The pharmacokinetic/pharmacodynamics (PK/PD) model was determined using MATLAB’s SimBiology tool, starting from a previously available block diagram, and validated through simulation. Then, to achieve the desired control performances, two controllers are designed: a PI adaptive controller and a PIλ (PI-fractional) adaptive controller, using the MIT algorithm. The time response during anesthetic drug infusion for each patient can be plotted with the AnesthesiaGUIDE tool, which is also designed in MATLAB/Simulink. The tool was tested on data from 12 patients, subjected to general anesthesia, with successful results. Through this tool, the article provides a good opportunity for any user to experience with adaptive control for the anesthesia process.Simona ComanDiana IosifSpringerarticleAnesthesiaGUIDE toolPI adaptive controlPIλ fractional-order adaptive control,Patient modelScienceQTechnologyTENSN Applied Sciences, Vol 4, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	AnesthesiaGUIDE tool PI adaptive control PIλ fractional-order adaptive control, Patient model Science Q Technology T
spellingShingle	AnesthesiaGUIDE tool PI adaptive control PIλ fractional-order adaptive control, Patient model Science Q Technology T Simona Coman Diana Iosif AnesthesiaGUIDE: a MATLAB tool to control the anesthesia
description	Abstract The goals of this paper are: (a) to investigate adaptive and fractional-order adaptive control algorithms for an automatic anesthesia process, using a closed-loop system, and (b) to develop an easy-to-use tool for MATLAB/Simulink to facilitate simulations for users with less knowledge about anesthesia and adaptive control. A model reference adaptive control structure was chosen for the entire system. First of all, to control the patient’s state during the surgery process, the patient mathematical model is useful, or even required for simulation studies. The pharmacokinetic/pharmacodynamics (PK/PD) model was determined using MATLAB’s SimBiology tool, starting from a previously available block diagram, and validated through simulation. Then, to achieve the desired control performances, two controllers are designed: a PI adaptive controller and a PIλ (PI-fractional) adaptive controller, using the MIT algorithm. The time response during anesthetic drug infusion for each patient can be plotted with the AnesthesiaGUIDE tool, which is also designed in MATLAB/Simulink. The tool was tested on data from 12 patients, subjected to general anesthesia, with successful results. Through this tool, the article provides a good opportunity for any user to experience with adaptive control for the anesthesia process.
format	article
author	Simona Coman Diana Iosif
author_facet	Simona Coman Diana Iosif
author_sort	Simona Coman
title	AnesthesiaGUIDE: a MATLAB tool to control the anesthesia
title_short	AnesthesiaGUIDE: a MATLAB tool to control the anesthesia
title_full	AnesthesiaGUIDE: a MATLAB tool to control the anesthesia
title_fullStr	AnesthesiaGUIDE: a MATLAB tool to control the anesthesia
title_full_unstemmed	AnesthesiaGUIDE: a MATLAB tool to control the anesthesia
title_sort	anesthesiaguide: a matlab tool to control the anesthesia
publisher	Springer
publishDate	2021
url	https://doaj.org/article/d559f7e663954425bbbd1064bd372c16
work_keys_str_mv	AT simonacoman anesthesiaguideamatlabtooltocontroltheanesthesia AT dianaiosif anesthesiaguideamatlabtooltocontroltheanesthesia
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AnesthesiaGUIDE: a MATLAB tool to control the anesthesia

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