DocumentCode :
1202304
Title :
Fuzzy logic approaches to intelligent alarms
Author :
Becker, Kurt ; Rau, Güunter ; Kaesmacher, Horst ; Petermeyer, Michael ; Kalff, Güunter ; Zimmermann, Hans-Jüurgen
Author_Institution :
Helmholtz-Inst. for Biomed. Eng., Aachen, Germany
Volume :
13
Issue :
5
fYear :
1994
Firstpage :
710
Lastpage :
716
Abstract :
The application of fuzzy methods as presented in the examples shows that the fuzzy logic approach has a great potential in biomedical engineering, where the difficulty of highly nonlinear and complicated dynamic properties are dramatic. The main advantage of utilising fuzzy methods is based on the nature of the model: the problems occurring can not and need not be modelled in a conventional mathematical manner. In the field of decision support systems, vague, redundant, and partly incomplete expert knowledge of complex biological systems can be handled by computers using a fuzzy logic approach by avoiding unnecessary accuracy. In the field of technical assist devices or systems, which will replace organs, the adaptation to the physiological requirements can be improved by the application of fuzzy control. The main properties of fuzzy control are: (a) reduction of effort on the sensor side, and (b) high dynamic stability in control, which is essential in controlling processes with a long dead- or transition time to a step response. In addition, powerful tools are available, allowing in short development times and high cost efficiency for the design and test of adequate fuzzy controllers. The expert knowledge of both the experienced physician and the biomedical engineer is an important source of information for the design of medical decision support systems and control systems for biomechanic devices. These attractive features will open new fields of application in the future.<>
Keywords :
alarm systems; biomedical engineering; fuzzy control; fuzzy logic; biomechanic devices control systems; dead-time; development time; experienced physician; expert knowledge; fuzzy controllers; fuzzy logic approaches; highly nonlinear complicated dynamic properties; intelligent alarms; medical decision support systems; processes control; step response; technical assist devices; transition time; Application software; Biological system modeling; Biological systems; Biology computing; Biomedical engineering; Decision support systems; Fuzzy control; Fuzzy logic; Mathematical model; Medical control systems;
fLanguage :
English
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
Publisher :
ieee
ISSN :
0739-5175
Type :
jour
DOI :
10.1109/51.334634
Filename :
334634
Link To Document :
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