000			03109nam a22003495c 4500
001			85142
003			ES-MaUEC
005			20230207040457.0
008			151124s2016 gw | s |||| 0|eng d
020			_a9783319259130
040			_aES-MaUEC
050		4	_aRC660 _b.P743 2016 EB
082	0	4	_a610.28
245	0	0	_aPrediction Methods for Blood Glucose Concentration : _bDesign, Use and Evaluation _cedited by Harald Kirchsteiger... [et al.]
250			_a1st ed.
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XIV, 265 p.) _b93 ilustraciones
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	1		_aLecture Notes in Bioengineering _x2195-271X
520			_aThis book tackles the problem of overshoot and undershoot in blood glucose levels caused by delay in the effects of carbohydrate consumption and insulin administration. The ideas presented here will be very important in maintaining the welfare of insulin-dependent diabetics and avoiding the damaging effects of unpredicted swings in blood glucose - accurate prediction enables the implementation of counter-measures. The glucose prediction algorithms described are also a key and critical ingredient of automated insulin delivery systems, the so-called 2artificial pancreas3. The authors address the topic of blood-glucose prediction from medical, scientific and technological points of view. Simulation studies are utilized for complementary analysis but the primary focus of this book is on real applications, using clinical data from diabetic subjects. The text details the current state of the art by surveying prediction algorithms, and then moves beyond it with the most recent advances in data-based modeling of glucose metabolism. The topic of performance evaluation is discussed and the relationship of clinical and technological needs and goals examined with regard to their implications for medical devices employing prediction algorithms. Practical and theoretical questions associated with such devices and their solutions are highlighted. This book shows researchers interested in biomedical device technology and control researchers working with predictive algorithms how incorporation of predictive algorithms into the next generation of portable glucose measurement can make treatment of diabetes safer and more efficient.
942			_2lcc _cLE
988			_aEBOOK, EBSPRINGER
650		7	_aDiabetes _9138582 _0comprobar BNE19900961602 _2embne
700	1		_aKirchsteiger, Harald _eeditor literario _997874 _0Local
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-25913-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319259130
907			_a.b12944208 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b28-04-17 _cm _dz _ef _feng _ggw _h0
945			_aRC660 .P743 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11588329 _z06-04-17
999			_c85142 _d85142 _x1