Blood pressure regulation by means of a neuro-fuzzy control system

Author

Chen, Chin-Te ; Lin, Win-Li ; Kuo, Te-Sou ; Wang, Cheng-Yi

Author_Institution

Dept. of Electr. Eng., Taiwan Univ., Taiwan

Volume

4

fYear

1996

fDate

31 Oct-3 Nov 1996

Firstpage

1725

Abstract

A two-model multilayered neural networks (MNN) controller with modified back-propagation training algorithm is designed to adaptively control the mean arterial blood pressure. The controller is also associated with a fuzzy logic unit (LGU) to determine an incremental value and update the output weighting factor of the parallel two-model MNN controller for adequate control action. Extensive computer simulations indicate satisfactory performance and robustness of the proposed controller in the presence of much noise, over the full range of plant parameters, uncertainties and large variations of parameters

Keywords

adaptive control; digital simulation; fuzzy control; fuzzy neural nets; haemodynamics; neurocontrollers; patient treatment; pressure control; blood pressure regulation; computer simulations; incremental value; mean arterial blood pressure; modified back-propagation training algorithm; neuro-fuzzy control system; output weighting factor; parameter variations; plant parameters; sodium nitroprusside drug; two-model multilayered neural networks controller; uncertainties; Algorithm design and analysis; Arterial blood pressure; Blood pressure; Computer simulation; Control systems; Fuzzy logic; Multi-layer neural network; Neural networks; Noise robustness; Pressure control;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE

Conference_Location

Amsterdam

Print_ISBN

0-7803-3811-1

Type

conf

DOI

10.1109/IEMBS.1996.647632

Filename

647632