Literature DB >> 25931581

Hypo- and Hyperglycemic Alarms: Devices and Algorithms.

Daniel Howsmon1, B Wayne Bequette2.   

Abstract

Soon after the discovery that insulin regulates blood glucose by Banting and Best in 1922, the symptoms and risks associated with hypoglycemia became widely recognized. This article reviews devices to warn individuals of impending hypo- and hyperglycemia; biosignals used by these devices include electroencephalography, electrocardiography, skin galvanic resistance, diabetes alert dogs, and continuous glucose monitors (CGMs). While systems based on other technology are increasing in performance and decreasing in size, CGM technology remains the best method for both reactive and predictive alarming of hypo- or hyperglycemia.
© 2015 Diabetes Technology Society.

Entities:  

Keywords:  alarm systems; continuous glucose monitoring; hypoglycemia; low glucose suspend

Mesh:

Substances:

Year:  2015        PMID: 25931581      PMCID: PMC4667339          DOI: 10.1177/1932296815583507

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  110 in total

1.  Methodology for hypoglycaemia detection based on the processing, analysis and classification of the electroencephalogram.

Authors:  F Iaione; J L B Marques
Journal:  Med Biol Eng Comput       Date:  2005-07       Impact factor: 2.602

2.  Accuracy of a new real-time continuous glucose monitoring algorithm.

Authors:  D Barry Keenan; Raymond Cartaya; John J Mastrototaro
Journal:  J Diabetes Sci Technol       Date:  2010-01-01

3.  Closed-Loop Control Performance of the Hypoglycemia-Hyperglycemia Minimizer (HHM) System in a Feasibility Study.

Authors:  Daniel A Finan; Thomas W McCann; Linda Mackowiak; Eyal Dassau; Stephen D Patek; Boris P Kovatchev; Francis J Doyle; Howard Zisser; Henry Anhalt; Ramakrishna Venugopalan
Journal:  J Diabetes Sci Technol       Date:  2014-01-01

4.  The PILGRIM study: in silico modeling of a predictive low glucose management system and feasibility in youth with type 1 diabetes during exercise.

Authors:  Thomas Danne; Christiana Tsioli; Olga Kordonouri; Sarah Blaesig; Kerstin Remus; Anirban Roy; Barry Keenan; Scott W Lee; Francine R Kaufman
Journal:  Diabetes Technol Ther       Date:  2014-01-21       Impact factor: 6.118

5.  Detection of EEG patterns related to nocturnal hypoglycemia.

Authors:  J Gade; A Rosenfalck; I Bendtson
Journal:  Methods Inf Med       Date:  1994-03       Impact factor: 2.176

6.  Monitoring set-up for selection of parameters for detection of hypoglycaemia in diabetic patients.

Authors:  G Heger; K Howorka; H Thoma; G Tribl; J Zeitlhofer
Journal:  Med Biol Eng Comput       Date:  1996-01       Impact factor: 2.602

7.  Threshold-based insulin-pump interruption for reduction of hypoglycemia.

Authors:  Richard M Bergenstal; David C Klonoff; Satish K Garg; Bruce W Bode; Melissa Meredith; Robert H Slover; Andrew J Ahmann; John B Welsh; Scott W Lee; Francine R Kaufman
Journal:  N Engl J Med       Date:  2013-06-22       Impact factor: 91.245

8.  Accuracy of the GlucoWatch G2 Biographer and the continuous glucose monitoring system during hypoglycemia: experience of the Diabetes Research in Children Network.

Authors: 
Journal:  Diabetes Care       Date:  2004-03       Impact factor: 19.112

9.  QTc interval prolongation is independently associated with severe hypoglycemic attacks in type 1 diabetes from the EURODIAB IDDM complications study.

Authors:  Gabriella Gruden; Sara Giunti; Federica Barutta; Nish Chaturvedi; Daniel R Witte; Marinella Tricarico; John H Fuller; Paolo Cavallo Perin; Graziella Bruno
Journal:  Diabetes Care       Date:  2011-11-28       Impact factor: 19.112

10.  Antecedent hypoglycemia impairs autonomic cardiovascular function: implications for rigorous glycemic control.

Authors:  Gail K Adler; Istvan Bonyhay; Hannah Failing; Elizabeth Waring; Sarah Dotson; Roy Freeman
Journal:  Diabetes       Date:  2008-12-03       Impact factor: 9.461

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  6 in total

1.  Will the First Approved Automated Insulin Delivery System Be a Game-Changer in Type 1 Diabetes Management?

Authors:  Jessica R Castle
Journal:  Diabetes Technol Ther       Date:  2017-03       Impact factor: 6.118

2.  Hypoglycemia Prevention via Personalized Glucose-Insulin Models Identified in Free-Living Conditions.

Authors:  Chiara Toffanin; Eleonora Maria Aiello; Claudio Cobelli; Lalo Magni
Journal:  J Diabetes Sci Technol       Date:  2019-10-23

3.  Feature-Based Machine Learning Model for Real-Time Hypoglycemia Prediction.

Authors:  Darpit Dave; Daniel J DeSalvo; Balakrishna Haridas; Siripoom McKay; Akhil Shenoy; Chester J Koh; Mark Lawley; Madhav Erraguntla
Journal:  J Diabetes Sci Technol       Date:  2020-06-01

4.  Reliability of Trained Dogs to Alert to Hypoglycemia in Patients With Type 1 Diabetes.

Authors:  Evan A Los; Katrina L Ramsey; Ines Guttmann-Bauman; Andrew J Ahmann
Journal:  J Diabetes Sci Technol       Date:  2016-08-28

5.  Hypoglycemia Detection and Carbohydrate Suggestion in an Artificial Pancreas.

Authors:  Kamuran Turksoy; Jennifer Kilkus; Iman Hajizadeh; Sediqeh Samadi; Jianyuan Feng; Mert Sevil; Caterina Lazaro; Nicole Frantz; Elizabeth Littlejohn; Ali Cinar
Journal:  J Diabetes Sci Technol       Date:  2016-11-01

Review 6.  Fault Tolerant Strategies for Automated Insulin Delivery Considering the Human Component: Current and Future Perspectives.

Authors:  Aleix Beneyto; B Wayne Bequette; Josep Vehi
Journal:  J Diabetes Sci Technol       Date:  2021-07-21
  6 in total

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