Prediction methods for blood glucose concentration : design, use and evaluation /: design, use and evaluation. ([2016])

• Record Type: Book
• Further Information: Note: Harald Kirchsteiger, John Bagterp Jørgensen, Eric Renard, Luigi del Re editors.
• Editors: Kirchsteiger, Harald; Jørgensen, John Bagterp; Renard, Eric; Del Re, Luigi
• Contents: Preface; Contents; Alternative Frameworks for Personalized Insulin -- Glucose Models; 1 Introduction; 2 Alternatives for Modeling; 3 Model Structures; 4 Interval Models; 4.1 Continuous Time System Identification; 4.2 Interval Model Results; 5 A Probabilistic Approach; 5.1 Gaussian and Generalized Gaussian Mixture Models; 5.2 Modeling Method and Model Structure; 5.3 Modeling Results; 6 Conclusion and Outlook; References; Accuracy of BG Meters and CGM Systems: Possible Influence Factors for the Glucose Prediction Based on Tissue Glucose Concentrations; 1 Introduction. 2 SMBG Accuracy and CGM Calibration with SMBG Results2.1 SMBG Accuracy; 2.2 CGM Calibration with SMBG Results; 3 Accuracy of CGM Systems; 3.1 Mean Absolute Relative Difference; 3.2 Precision Absolute Relative Difference; 4 Glucose Prediction Based on Tissue Glucose Concentrations; References; CGM -- How Good Is Good Enough?; 1 Background; 2 CGM Performance Assessment; 2.1 Sensor Signal; 2.2 Reference Methodology; 2.3 Accuracy and Precision; 3 State of the Art; 4 Unresolved Issues; 4.1 Transient Sensor Signal Disruption; 4.2 Transient Significant CGM Inaccuracies. 5 Next Steps in CGM Development6 Conclusion; References; Can We Use Measurements to Classify Patients Suffering from Type 1 Diabetes into Subcategories and Does It Make Sense?; 1 Introduction; 2 Database of CGMS Recordings; 3 Modelling Using a Simple Transfer Function Model; 3.1 Description of the Model and System Identification; 3.2 Trends and Correlations; 3.3 Clustering and Classification; 3.4 Discussion of Results and Further Outlook; 4 Analysis of the High Frequency Content of CGMS Signals; 4.1 Filtering of CGMS Signals; 4.2 Trends and Classification. 4.3 Discussion of Results and Further OutlookReferences; Prevention of Severe Hypoglycemia by Continuous EEG Monitoring; 1 Background; 2 Clinical Studies -- Proof of Concept; 3 The Device; 4 Quantitative Evaluation of EEG Recorded with the Partly Implanted EEG Recorder; 5 Development of an Algorithm for Detection and Warning of Severe Hypoglycaemia in Type 1 Diabetes; 6 Clinical Studies -- Preliminary Results with Implanted Device; 7 Discussion and Perspectives; 8 Conclusion; References; Meta-Learning Based Blood Glucose Predictor for Diabetic Smartphone App; 1 Introduction. 2 Fully Adaptive Regularized Learning Algorithm for the Blood Glucose Prediction3 Android Version of the FARL Algorithm; 3.1 Translation of the Algorithm from Matlab to Android System; 3.2 Microprocessor and Power Consumption Analysis; 4 Performance Assessment; 4.1 Clinical Accuracy Metrics; 4.2 Performance Assessment; 4.3 Comparison of the Matlab and Android Versions; 5 Conclusions and Discussion; References; Predicting Glycemia in Type 1 Diabetes Mellitus with Subspace-Based Linear Multistep Predictors; 1 Introduction; 2 Subspace-Based Linear Multistep Predictors; 2.1 Notation.
• Publisher Details: Cham : Springer
• Publication Date: 2016
• Copyright Date: 2016
• Extent: 1 online resource
• Subjects: 616.4/62; Engineering; Blood sugar monitoring -- Equipment and supplies; Blood sugar -- Analysis; HEALTH & FITNESS -- Diseases -- General; MEDICAL -- Clinical Medicine; MEDICAL -- Diseases; MEDICAL -- Evidence-Based Medicine; MEDICAL -- Internal Medicine; Blood sugar -- Analysis; Engineering; Biomedical Engineering; Diabetes; Control; Biological and Medical Physics, Biophysics; Blood Glucose Self-Monitoring; Blood Glucose -- analysis; Medical -- Endocrinology & Metabolism; Technology & Engineering -- Automation; Science -- Life Sciences -- Biophysics; Diabetes; Automatic control engineering; Biophysics; Biomedical engineering; Diabetes; Technology & Engineering -- Engineering (General); Biomedical engineering; Electronic books
• Languages: English
• ISBNs: 9783319259130
• Related ISBNs: 331925913X; 9783319259116; 3319259113; 9783319259116
• Notes: Note: Includes bibliographical references.; Note: Vendor-supplied metadata.
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