Title :
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
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;
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
DOI :
10.1109/ICNN.1995.487717
