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Type-2 fuzzy sets applied to multivariable self-organizing fuzzy logic controllers for regulating anesthesia

Doctor, F and Syue, C-H and Liu, Y-X and Shieh, J-S and Iqbal, R (2016) 'Type-2 fuzzy sets applied to multivariable self-organizing fuzzy logic controllers for regulating anesthesia.' Applied Soft Computing, 38. 872 - 889. ISSN 1568-4946

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Abstract

In this paper, novel interval and general type-2 self-organizing fuzzy logic controllers (SOFLCs) are proposed for the automatic control of anesthesia during surgical procedures. The type-2 SOFLC is a hierarchical adaptive fuzzy controller able to generate and modify its rule-base in response to the controller's performance. The type-2 SOFLC uses type-2 fuzzy sets derived from real surgical data capturing patient variability in monitored physiological parameters during anesthetic sedation, which are used to define the footprint of uncertainty (FOU) of the type-2 fuzzy sets. Experimental simulations were carried out to evaluate the performance of the type-2 SOFLCs in their ability to control anesthetic delivery rates for maintaining desired physiological set points for anesthesia (muscle relaxation and blood pressure) under signal and patient noise. Results show that the type-2 SOFLCs can perform well and outperform previous type-1 SOFLC and comparative approaches for anesthesia control producing lower performance errors while using better defined rules in regulating anesthesia set points while handling the control uncertainties. The results are further supported by statistical analysis which also show that zSlices general type-2 SOFLCs are able to outperform interval type-2 SOFLC in terms of their steady state performance.

Item Type: Article
Uncontrolled Keywords: Anesthesia, Hierarchical systems, Type-2 fuzzy sets, Self-organizing fuzzy logic controller
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > R Medicine (General)
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 03 Jan 2018 14:46
Last Modified: 03 Jan 2018 14:46
URI: http://repository.essex.ac.uk/id/eprint/20871

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