Paper Info
Title
Self-Learning Fuzzy Logic Control in Medicine
Abstract
Self-learning fuzzy logic control has the important property of accommodating uncertain, non-linear and time-varying process characteristics. This intelligent control scheme starts with no fuzzy control rules and learns how to control each process presented to it in real-time without the need for detailed process modelling. Medicine abounds with suitable applications for this technique. Following an outline of the methodology we demonstrate its clinical effectiveness for application in anaesthesia. We have investigated its application to atracurium-induced neuromuscular block during surgery and have observed improved control over complex numerical techniques. This self-learning fuzzy control technique shows much promise for other medical applications such as post-operative blood pressure management, intra-operative control of anaesthetic depth, and multivariable circulatory management of intensive care patients.
Year
DOI
Venue
1997
10.1007/BFb0029463
AIME '87
Keywords
Field
DocType
intelligent control,anaesthesia,: fuzzy logic,self-learning fuzzy logic control,medicine,fuzzy logic,blood pressure,real time,fuzzy control,process modelling
Fuzzy electronics,Intelligent control,Neuro-fuzzy,Fuzzy set operations,Computer science,Fuzzy logic,Artificial intelligence,Adaptive neuro fuzzy inference system,Control system,Fuzzy control system
Conference
Volume
ISSN
ISBN
1211
0302-9743
3-540-62709-X
Citations 
PageRank 
References 
5
0.56
3
Authors
3
Name
Order
Citations
PageRank
D. G. Mason150.56
Derek A. Linkens221525.36
N. D. Edwards350.56