Statements in which the resource exists.
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pubmed-article:10356301pubmed:abstractTextSelf-learning fuzzy logic control has the important property of accommodating uncertain, nonlinear, 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 modeling. In this study we utilize temporal knowledge of generated rules to improve control performance. A suitable medical application to investigate this control strategy is atracurium-induced neuromuscular block of patients in the operating theater where the patient response exhibits high nonlinearity and individual patient dose requirements may vary fivefold during an operating procedure. We developed a computer control system utilizing Relaxograph (Datex) measurements to assess the clinical performance of a self-learning fuzzy controller in this application. Using a T1 setpoint of 10% of baseline in 10 patients undergoing general surgery, we found a mean T1 error of 0.28% (SD = 0.39%) while accommodating a 0.25 to 0.38 mg/kg/h range in the mean atracurium infusion rate. This result compares favorably with more complex and computationally intensive model-based control strategies for atracurium infusion.lld:pubmed
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pubmed-article:10356301pubmed:authorpubmed-author:RossJ JJJlld:pubmed
pubmed-article:10356301pubmed:authorpubmed-author:MasonD GDGlld:pubmed
pubmed-article:10356301pubmed:authorpubmed-author:EdwardsN DNDlld:pubmed
pubmed-article:10356301pubmed:copyrightInfoCopyright 1999 Academic Press.lld:pubmed
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pubmed-article:10356301pubmed:volume32lld:pubmed
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pubmed-article:10356301pubmed:pagination187-97lld:pubmed
pubmed-article:10356301pubmed:dateRevised2006-11-15lld:pubmed
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pubmed-article:10356301pubmed:articleTitleSelf-learning fuzzy control with temporal knowledge for atracurium-induced neuromuscular block during surgery.lld:pubmed
pubmed-article:10356301pubmed:affiliationDepartment of Automatic Control and Systems Engineering, University of Sheffield, South Yorkshire S1 3JD, Sheffield, United Kingdom.lld:pubmed
pubmed-article:10356301pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:10356301pubmed:publicationTypeComparative Studylld:pubmed
pubmed-article:10356301pubmed:publicationTypeResearch Support, Non-U.S. Gov'tlld:pubmed
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