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Intelligent Systems Modelling and Decision Support in BioEngineering

Intelligent Systems Modelling and Decision Support in BioEngineering

By (author): Mahdi Mahfouf
Copyright: 2006
Pages: 356
ISBN: 9781580539999

eBook $139.00 Qty:
Helping to bridge the gap between medicine and engineering, this groundbreaking resource provides a detailed understanding of the analysis, design, and application of new intelligent systems in the biomedical industry. The book covers the three major areas of application in biomedicine, including the modeling and control in human anaesthesia, decision support for critically ill patients in intensive care units, and modeling of humans who are subjected to physical workload stress. You'll find expert guidance on signal processing in Anaesthesia; systems modeling and feedback adaptive control of Anaesthesia; model reduction of physiological modeling using systems engineering; design of intelligent-systems-based decision support systems in critical and life-threatening environments; and hybrid modeling - combining intelligent systems structures with physical models. This cutting-edge reference also describes the monitoring and closed-loop control of anaesthesia via blood pressure measurements during surgery. Additionally, you learn a new systems engineering approach to the modeling of human physiology via pharmacokinetics/pharmacodynamics studies relating to anaesthetic drugs.
Part 1: Aneasthesia Therapy; Multivariable Feedback Control of Muscle Relaxation and Unconsciousness Using Model-Based Predictive Control - Physiological Background Relating to the Muscle Relaxation Process. Compartmental Modeling of Muscle Relaxants. Adaptive Predictive Control of Muscle Relaxation. A Multivariable Model for Anaesthesia. A Review of the Multivariable Control System.; A New Generic Approach to Model Reduction for Complex Physiologically-Based Drug Models - Pharmacokinetics Associated with Fentanyl and Pethidine. Dynamic Representation of the Mapleson-Higgins Models. Model Parameters Sensitivity Study. Model Fitting for Drug Concentrations in Tissues and Blood Pools. Model Reduction Analysis Using Balanced Realization Techniques. Model Extension to Pharmacodynamics. Closed-Loop Control of Drug Administration.; A Hybrid Systems Approach to Modeling and Control of Unconsciousness Via Blood Pressure Measurements - Mean Arterial Pressure (MAP) Physiological Model Associated with Isoflurane. Unconstrained and Constrained Predictive Control Using the Quadratic Programming (QP) Approach.Simulation Results. Real Time Experiments. A Review of Faults Associated with the Anaesthesia Control System. The Intelligent Hierarchical Supervisory Level: Structure and Algorithm. Results of Experiments. ; Advanced Signal Processing and Control in Anaesthesia - Alternative Assessment Tools of Depth of Anaesthesia (DOA). Auditory Evoked Potential (AEP). Development of a New Fuzzy Relational Classifier for DOA. Patients and Drug Pharmacology of Propofol and Remifentanil. A Hybrid Patient Model. Fuzzy Control of DOA.; Part 2: Patient/Ventilator Modeling in Intensive Care Units (ICU); Intelligent Modeling of Patient-Ventilator Interactions in GeneralICU - Artificial Ventilation in ICU. The Simulation of Patient Ventilation (SOPAVENT) Model and Its Extensions.; An Intelligent Advisory System for Intensive Care Ventilators ‑ Development of the Top-Level Knowledge-Based Module. Development of the Lower-Level Model-Based Module. System Integration and Validation. Part 3: Modeling Subjects Under Physical Stress; A Generic Grey-Box Model for the Cardio-Vascular System of Subjects Experiencing Physical Stress - Background Relating to Human Physiology. Experimental Set-Up. The Luczak-Based Closed-Loop Model. ; Model Extension Including Thermoregulation and Brain Activity via EEG and Feedback Control - First Extension of the Model. Second Extension of the Model. A Generic Model. Exploitation of the Model to Include Feedback Control.; Conclusions.;
  • Mahdi Mahfouf Mahdi Mahfouf is a professor of intelligent systems engineering in the Department of Automatic Control and Systems Engineering at The University of Sheffield. He earned both his M.Phil. and Ph.D. in control systems engineering from the same university.
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