A fuzzy logic-based decision support system on anesthetic depth control for helping anesthetists in surgeries

Journal of Medical Systems

Volumn 31, Issue 6, 2007, Pages 511-519

  Saraoğlu, Hamdi Melih ^a   Şanlı, Sibel ^b  

^a DUMLUPINAR UNIVERSITY   (Turkey)

^b Kutahya Evliya Celebi State Hospital   (Turkey)

Author keywords

Anesthetic depth control; Anesthetic dose level; Decision support system; Fuzzy logic; General anesthesia; Sevoflurane

Indexed keywords

ANESTHETIC AGENT; SEVOFLURANE;

ANESTHESIA LEVEL; ANESTHESIST; ARTICLE; HUMAN; INHALATION ANESTHESIA; PULSE RATE; SYSTOLIC BLOOD PRESSURE;

EID: 35348847831     PISSN: 01485598     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10916-007-9092-x     Document Type: Article

References (18)

1. Marshall, B. E., and Lockenfger, D. E., General anaesthetics, Goodman and Gilman's, the pharmocological basis of therapeutics. 8th Edition. Oxford: Permagon Press, 1990, pp. 285-311.
2. Snow J. C., Anestezi El Kitabi: Izmir Guven Kitapevi, Izmir, 1986.
3. Saraoglu, H. M., and SanlI, S., Fuzzy logic based anesthetic depth control, 2003 ICIS International Conference on signal processing (ICSP 2003), September 24-26. Çanakkale, Turkey, 2003.
4. Mahfouf, M., Asbury, A. J., and Likens, D. A., Unconstrained and constrained generalized predictive control of depth of anesthesia during surgery. Control. Eng. Pract. 11:1501-1515, 2003.
5. Becker, K., Thull, B., Kasmacher-Leidinger, H., Stemmer, J., Rau, G., Kalf, G., and Zimmermann, H., Design and validation of an intelligent patient monitoring and alarm system based on fuzzy logic process model. Artif. Intell. Med. 11:33-53, 1997.
6. Vefghi, L., and Linkens, D. A., Internal representation in neural networks used for classification of patient anesthetic states and dosage. Comput. Methods Programs Biomed. 59, 1999 pp. 75-89.
7. Pis P., and Mesiar,R., Fuzzy model of inexact reasoning in medicine. Comput. Methods Programs Biomed. 30:1-8, 1989.
8. Greenhow, S. G., Linkens, D. A., and Asbury, A., Pilot study of an expert system adviser for controlling general anesthesia. Br. J. Anaesth. 71:359-365, 1993.
9. Zbinden, A. M., Feigenwinter, P., and Hutmacher, M., Fresh gas utilization of eight circle system. Br. J. Anaesth. 67:492-499, 1991.
10. Bengstone, J. P., Sonader, H., and Stenquvist, O., Comparison of cost of different anesthetic techniques. Acta Anaesthesiol. Scand. 32:33-35, 1998.
11. Linkens, D. A. Adaptive and intelligent control in anaesthesia. IEEE Control Syst. Mag. 12(6):6-11, 1992.
12. Vickers, M. D., Schniede, H., and Wood-Smith, F. G., Drugs in anaesthetic practice. 6th Edition. London: Butterworths, 1984.
13. Merer, R., Nieuwland J., Zbinden, A. M., and Hacisalihzade, S. S., Fuzzy logic control of blood pressure during anesthesia. IEEE Control Syst. Mag. 12(9):12-17, 1992.
14. Zadeh, L. A., Fuzzy sets. Inf. Control. 8:38-53, 1967.
15. Temurtas, F., Fast detection of the hazardous organic gases in the ambient air using adaptive neuro-fuzzy inference systems. Int. J. Environ. Pollut. 28(3/4), 2006.
16. Yea, B., Osaki, T., Sugahara, K., and Konishi, R., Improvement of concentration estimation algorithm for inflammable gases utilizing fuzzy rule based neural networks. Sens. Actuators B Chem. 56:181-188, 1999.
17. Mamdani, E. H., and Assilian, S., An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man-Mach. Stud. 7(1):1-13, 1975.
18. MATLAB® Documentation (2002) Neural Network Toolbox Help, Version 6.5, Release 13, MathWorks, 3 Apple Hill Drive Natick, MA.