This brief introduces recursive modeling techniques that take account of variations in blood glucose concentration within and between individuals. It describes their use in developing multivariable models in early-warning systems for hypo- and hyperglycemia; these models are more accurate than those solely reliant on glucose and insulin concentrations because they can accommodate other relevant influences like physical activity, stress and sleep.
Such factors also contribute to the accuracy of the adaptive control systems present in the artificial pancreas which is the focus of the brief, as their presence is indicated before they have an apparent effect on the glucose concentration and so can be more easily compensated. The adaptive controller is based on generalized predictive control techniques and also includes rules for changing controller parameters or structure based on the values of physiological variables. Simulation studies and clinical studies are reported to illustrate the performance of the techniques presented.Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Ali Cinar is Professor of Chemical Engineering at the Illinois Institute of Technology. His research concentrates on three areas: modeling, simulation and control of biomedical systems, complex adaptive agent-based systems, and supervision of process operations. His research activities focus on the development of theory, methods, and tools to use in these application areas. He is a Fellow of the AIChE and the author of books on batch fermentation and chemical process performance evaluation.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This brief introduces recursive modeling techniques that take account of variations in blood glucose concentration within and between individuals. It describes their use in developing multivariable models in early-warning systems for hypo- and hyperglycemia; these models are more accurate than those solely reliant on glucose and insulin concentrations because they can accommodate other relevant influences like physical activity, stress and sleep. Such factors also contribute to the accuracy of the adaptive control systems present in the artificial pancreas which is the focus of the brief, as their presence is indicated before they have an apparent effect on the glucose concentration and so can be more easily compensated. The adaptive controller is based on generalized predictive control techniques and also includes rules for changing controller parameters or structure based on the values of physiological variables. Simulation studies and clinical studies are reported to illustrate the performance of the techniques presented. 132 pp. Englisch. N° de réf. du vendeur 9783319722443
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This brief introduces recursive modeling techniques that take account of variations in blood glucose concentration within and between individuals. It describes their use in developing multivariable models in early-warning systems for hypo- and hyperglycemia; these models are more accurate than those solely reliant on glucose and insulin concentrations because they can accommodate other relevant influences like physical activity, stress and sleep. Such factors also contribute to the accuracy of the adaptive control systems present in the artificial pancreas which is the focus of the brief, as their presence is indicated before they have an apparent effect on the glucose concentration and so can be more easily compensated. The adaptive controller is based on generalized predictive control techniques and also includes rules for changing controller parameters or structure based on the values of physiological variables. Simulation studies and clinical studies are reported to illustrate the performance of the techniques presented. N° de réf. du vendeur 9783319722443
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This brief introduces recursive modeling techniques that take account of variations in blood glucose concentration within and between individuals. It describes their use in developing multivariable models in early-warning systems for hypo- and hyperglycemia; these models are more accurate than those solely reliant on glucose and insulin concentrations because they can accommodate other relevant influences like physical activity, stress and sleep. Such factors also contribute to the accuracy of the adaptive control systems present in the artificial pancreas which is the focus of the brief, as their presence is indicated before they have an apparent effect on the glucose concentration and so can be more easily compensated. The adaptive controller is based on generalized predictive control techniques and also includes rules for changing controller parameters or structure based on the values of physiological variables. Simulation studies and clinical studies are reported to illustrate the performance of the techniques presented.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 132 pp. Englisch. N° de réf. du vendeur 9783319722443
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Taschenbuch. Etat : Neu. Advances in Artificial Pancreas Systems | Adaptive and Multivariable Predictive Control | Ali Cinar (u. a.) | Taschenbuch | SpringerBriefs in Bioengineering | xii | Englisch | 2018 | Springer | EAN 9783319722443 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 111073662
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