DocumentCode :
2706393
Title :
Fuzzy logic knowledge elicitation for model-based ventilator management in the ICU
Author :
Kwok, H.F. ; Linkens, D.A. ; Mahfouf, M. ; Mills, G.H. ; Simpson, C.L. ; Goode, K.M.
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Sheffield Univ., UK
fYear :
2000
fDate :
2000
Firstpage :
9
Lastpage :
13
Abstract :
Ventilator control in the intensive care unit has been an important feedback control problem in critical care. Although attempts have been made in the past using model based or knowledge based techniques, automation is not widely used. We propose a method which combines the quantitative approach in most model based methods and a qualitative approach using fuzzy logic. The paper presents two methods of fuzzy membership function derivation. The fuzzy sets will be used for the model based expert advisory system for the ventilators. The two methods are compared and one of them will be used to derive fuzzy membership functions for other variables and parameters in this project
Keywords :
fuzzy logic; fuzzy set theory; knowledge acquisition; medical expert systems; ICU; critical care; feedback control problem; fuzzy logic knowledge elicitation; fuzzy membership function derivation; fuzzy membership functions; fuzzy sets; intensive care unit; knowledge based techniques; model based expert advisory system; model based methods; model based ventilator management; qualitative approach; quantitative approach; ventilator control;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Advances in Medical Signal and Information Processing, 2000. First International Conference on (IEE Conf. Publ. No. 476)
Conference_Location :
Bristol
ISSN :
0537-9989
Print_ISBN :
0-85296-728-4
Type :
conf
DOI :
10.1049/cp:20000310
Filename :
889944
Link To Document :
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