NDLI: Peak Blood Glucose Prediction Algorithm Following a Meal Intake

Content Provider	IEEE Xplore Digital Library
Author	Islam, M.S. Leech, J. Lin, C.C.Y. Chrostowski, L.
Copyright Year	2007
Description	Author affiliation: Univ. of British Columbia, Vancouver (Islam, M.S.; Leech, J.; Lin, C.C.Y.; Chrostowski, L.)
Abstract	Motivated by the increasing number of diabetes patients around the globe, we have created an algorithm that predicts blood glucose trends and levels for the period of time after a meal intake. This information will help both type-I and type-II diabetic patients properly predict their bodies' effect to food intake and avoid dangerous hypoglycemic and hyperglycemic states. Most of the long-term health problems (e.g. nephropathy, retinopathy, and neuropathy) result from sustained hyperglycemia and frequent blood glucose excursions in time due to inaccurate insulin infusions; this is a direct result of a misjudgement of dosage or from poor patient compliance. Some devices already developed, such as one time glucose meters and continuous glucose monitors, lack information diabetics need to fully understand glucose level trends, such as an increasing or decreasing glucose pattern and the rate of change. Patients must therefore estimate their insulin dose based on their present glucose reading and estimated food intake, which cumbersome and inaccurate. This is where our algorithm will help diabetic patients. Our algorithm differs from other developed devices and models (Lehman and Deutsch, 1992) in that it predicts insulin dosage based on the predicted peak blood glucose level just after the meal-intake. Since we are dealing with human body, it is quite difficult to model how each organ will behave, thus a number of parameters need to be collected to calibrate the model for each individual. In the future, this predictive system could be integrated with an insulin pump that will automatically inject insulin into the body as prescribed by our algorithm.
Starting Page	579
Ending Page	582
File Size	166016
Page Count	4
File Format	PDF
ISBN	1424410207
ISSN	08407789
DOI	10.1109/CCECE.2007.149
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-04-22
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Blood Sugar Prediction algorithms Insulin Diabetes Biological system modeling Medical treatment Predictive models Humans Steady-state
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Hardware and Architecture

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Libarray of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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