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| 001 | 102582 | ||
| 003 | DE-He213 | ||
| 005 | 20230102113049.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 180301s2018 gw | s |||| 0|eng d | ||
| 020 | _a9783319722450 | ||
| 024 | 7 |
_a10.1007/978-3-319-72245-0 _2doi |
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| 040 | _aES-MaUEC | ||
| 050 | 4 | _aR856.A6 2018 EB | |
| 100 | 1 |
_aCinar, Ali _0http://id.loc.gov/authorities/names/nb2003052417 _1http://viaf.org/viaf/66582205/ |
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| 245 | 1 | 0 |
_aAdvances in Artificial Pancreas Systems _bAdaptive and Multivariable Predictive Control _cby Ali Cinar, Kamuran Turksoy. |
| 264 | 1 |
_aCham _bSpringer International Publishing _c2018 |
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| 300 | _a1 recurso en línea (XII, 119 páginas 22 ilustraciones, 9 ilustraciones a color) | ||
| 347 |
_atext file _bPDF |
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| 490 | 0 |
_aSpringerBriefs in Bioengineering _x2193-097X |
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| 505 | 0 | _aIntroduction -- 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. | |
| 520 | 3 | _aThis 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. | |
| 650 | 7 |
_aIngeniería biomédica _9143820 _2embne |
|
| 650 | 7 |
_aEndocrinología _2embne _9139372 |
|
| 700 | 1 |
_aTurksoy, Kamuran _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 776 | 0 | 8 |
_iEdición impresa: _z9783319722443 |
| 776 | 0 | 8 |
_iEdición impresa: _z9783319722467 |
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-72245-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 490 | 0 | _aEngineering (Springer-11647) | |
| 988 | _aEBSPRINGER_2018 | ||
| 998 |
_b01/2019 _dz _ek _feng _ggw _h0 |
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| 999 |
_c102582 _d102582 _x1 |
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