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001 978-3-319-25913-0
003 DE-He213
005 20200421112049.0
007 cr nn 008mamaa
008 151124s2016 gw | s |||| 0|eng d
020 _a9783319259130
_9978-3-319-25913-0
024 7 _a10.1007/978-3-319-25913-0
_2doi
050 4 _aR856-857
072 7 _aMQW
_2bicssc
072 7 _aTEC009000
_2bisacsh
082 0 4 _a610.28
_223
245 1 0 _aPrediction Methods for Blood Glucose Concentration
_h[electronic resource] :
_bDesign, Use and Evaluation /
_cedited by Harald Kirchsteiger, John Bagterp J�rgensen, Eric Renard, Luigi del Re.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXIV, 265 p. 93 illus., 72 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Bioengineering,
_x2195-271X
505 0 _aFrom the Contents : Part I Introduction -- Clinical Relevance of Glucose Prediction: Needs and Goals -- What is the Technical Challenge of Blood Glucose Prediction? -- Part II Possible Solutions -- An Overview of Glucose Prediction Algorithms -- Data-Based Interval Models Employing Continuous-Time System Identification.
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 "artificial pancreas". 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.
650 0 _aEngineering.
650 0 _aDiabetes.
650 0 _aControl engineering.
650 0 _aBiomedical engineering.
650 1 4 _aEngineering.
650 2 4 _aBiomedical Engineering.
650 2 4 _aDiabetes.
650 2 4 _aControl.
650 2 4 _aBiological and Medical Physics, Biophysics.
700 1 _aKirchsteiger, Harald.
_eeditor.
700 1 _aJ�rgensen, John Bagterp.
_eeditor.
700 1 _aRenard, Eric.
_eeditor.
700 1 _adel Re, Luigi.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319259116
830 0 _aLecture Notes in Bioengineering,
_x2195-271X
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-25913-0
912 _aZDB-2-ENG
942 _cEBK
999 _c57082
_d57082