Intelligent Control in Biomedicine

Intelligent Control in Biomedicine

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Intelligent control is a rapidly growing subject in systems engineering, with several different techniques being developed and exploited in recent years. These range from fuzzy logic control which has been utilized widely by the Japanese in the high-volume consumer market (cameras, washing machines, cars) to genetically-based design algorithms. All of these modern techniques are described in the book under the unifying theme of their application to clinical medicine. Intelligent control is intended to deal with uncertain, nonlinear, time-varying situations, and these are common-place in the life sciences. The major application here is that of on-line drug-infusion control for anaesthesia in operating theatres.
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Product details

  • Hardback | 424 pages
  • 172.72 x 248.92 x 30.48mm | 997.9g
  • Taylor & Francis Ltd
  • London, United Kingdom
  • English
  • 0748401156
  • 9780748401154

Table of contents

Introduction to Intelligent Control Paradigms and System Modelling, D.A. Linkens; A Real-Time Expert System for Anaesthesia Validated in Clinical Trials, S.G. Greenhow; Generalized Predicitve Control GPC in the Operating Theatre, M. Mahfouf; A Comparative Study of Generalized Predictve Control GPC and Intelligent Self-Organising Fuzzy Logic Control SOFLC for Multivariable Anaesthesia, M. Mahfouf and M.E. Abbod; Hierarchical Supervisory Self-Organizing Fuzzy Control for Muscle Relaxation Anaesthesia, M.E. Abbod; Hierarchical Fuzzy Modelling and Fault Detection for Muscle Relaxation Anaesthesia, J.S. Shieh; Unified Fuzzy Reasoning and Blood Pressure Management, Junhong Nie; Learning- Based Fuzzy and Neural Control for Blood Pressure Management, Junhong Nie; Self-Organising Fuzzy-Neural Control for Blood Pressure Management, Junhong Nie; Neural Network Control for Unconsciousness Anaesthesia, H.U. Rehman; Genetic Algorithms in the Control of Anaesthesia, H. Okla Nyongesa; Multifaceted Knowledge Representation and Acquisition Applied to the Modelling of the Cardiovascular System, E. Tanyi; Automated Qualitative Model Abduction Based on Bond Graphs, S. Xia.
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