By Topic

Predicting human subcutaneous glucose concentration in real time: A universal data-driven approach

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Yinghui Lu ; Bioinf. Cell (BIC), USAMRMC, Fort Detrick, MD, USA ; Rajaraman, S. ; Ward, W.Kenneth ; Vigersky, R.A.
more authors

Continuous glucose monitoring (CGM) devices measure and record a patient's subcutaneous glucose concentration as frequently as every minute for up to several days. When coupled with data-driven mathematical models, CGM data can be used for short-term prediction of glucose concentrations in diabetic patients. In this study, we present a real-time implementation of a previously developed offline data-driven algorithm. The implementation consists of a Kalman filter for real-time filtering of CGM data and a data-driven autoregressive model for prediction. Results based on CGM data from 3 different studies involving 34 type 1 and 2 diabetic patients suggest that the proposed real-time approach can yield ~10-min-ahead predictions with clinically acceptable accuracy and, hence, could be useful as a tool for warning against impending glucose deregulation episodes. The results further support the feasibility of “universal” glucose prediction models, where an offline-developed model based on one individual's data can be used to predict the glucose levels of any other individual in real time.

Published in:

Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE

Date of Conference:

Aug. 30 2011-Sept. 3 2011