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Record Nr. |
UNINA9910299936203321 |
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Autore |
Cinar Ali |
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Titolo |
Advances in Artificial Pancreas Systems : Adaptive and Multivariable Predictive Control / / by Ali Cinar, Kamuran Turksoy |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
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ISBN |
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Edizione |
[1st ed. 2018.] |
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Descrizione fisica |
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1 online resource (xii, 119 pages) : illustrations |
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Collana |
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SpringerBriefs in Bioengineering, , 2193-097X |
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Disciplina |
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Soggetti |
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Biomedical engineering |
Control engineering |
Endocrinology |
Biomedical Engineering and Bioengineering |
Control and Systems Theory |
Endocrinology |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction -- Physiology and Factors Affecting Blood Glucose Concentration -- Components of an Artificial Pancreas -- Modeling Glucose Concentration Dynamics -- Hypoglycemia Alarm Systems -- Hyperglycemia Alarm Systems -- Various Control Philosophies and Algorithms -- Multivariable Control of Glucose Concentration -- Dual Hormone Techniques for AP Systems -- Integrated Hypo-/Hyperglycemia Alarm and Control Systems -- Future Developments. |
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Sommario/riassunto |
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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 |
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