A hybrid fuzzy-neural control system for management of mean arterial pressure of seriously ill patients

Author

Xu, Z.M. ; Packer, J.S. ; Cade, J.F.

Author_Institution

Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia

Volume

5

fYear

1995

fDate

Nov/Dec 1995

Firstpage

2281

Abstract

In this paper, a fuzzy-neural control system is applied to regulate mean arterial blood pressure in seriously ill patients using sodium nitroprusside. This hybrid system consists of an adaptive fuzzy controller and a network based predictor. Computer simulation results illustrate that the system has ability to learn control rules from off-line training process as well as to adjust the parameters during control process. Clinical trials are being carried out in Intensive Care Unit at the Royal Melbourne Hospital

Keywords

adaptive control; biomedical equipment; computerised control; fuzzy control; fuzzy neural nets; neurocontrollers; patient treatment; predictive control; pressure control; adaptive fuzzy controller; hybrid fuzzy-neural control system; mean arterial pressure management; network based predictor; off-line training process; patient treatment; sodium nitroprusside; Adaptive control; Arterial blood pressure; Clinical trials; Computer simulation; Control systems; Fuzzy control; Fuzzy systems; Pressure control; Process control; Programmable control;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1995. Proceedings., IEEE International Conference on

Conference_Location

Perth, WA

Print_ISBN

0-7803-2768-3

Type

conf

DOI

10.1109/ICNN.1995.487717

Filename

487717