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Observer Based Plasma Glucose Prediction in Type I Diabetes

Ståhl, Fredrik LU and Johansson, Rolf LU (2010) 2010 IEEE Multi-Conference on Systems and Control In [Host publication title missing] p.1620-1625
Abstract
Recent years’ progress in the development of Continuous Glucose Monitors (CGM) has made rich well-sampled glucose data readily available. Reliable, frequent measurements are of outmost importance for the emerging closed-loop control of diabetic plasma glucose. However, these sensors do not measure the variable of primary interest - plasma glucose, but a delayed signal - the interstitial glucose. To overcome this difficulty this paper presents a novel model, merging a black-box model of the glucose dynamics together with a CGM sensor model. Using an observer the plasma glucose level is estimated and predicted. The outlined scheme was evaluated on one patient, with a significant sensor delay, from a clinical trial of the DIAdvisor European... (More)
Recent years’ progress in the development of Continuous Glucose Monitors (CGM) has made rich well-sampled glucose data readily available. Reliable, frequent measurements are of outmost importance for the emerging closed-loop control of diabetic plasma glucose. However, these sensors do not measure the variable of primary interest - plasma glucose, but a delayed signal - the interstitial glucose. To overcome this difficulty this paper presents a novel model, merging a black-box model of the glucose dynamics together with a CGM sensor model. Using an observer the plasma glucose level is estimated and predicted. The outlined scheme was evaluated on one patient, with a significant sensor delay, from a clinical trial of the DIAdvisor European FP7-project. Using the raw signal from the CGM device together with meal and insulin infusion data predictions for 20, 40 and 60 min were produced for a breakfast meal. Results: RMSE of the prediction error was smaller than 26 mg/dl for validation data even for the longest prediction horizon and no points in the C/D/E zones in the pCGA evaluation. The model clearly outperformed the CGMS and the results indicate that the method could be used successfully. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
[Host publication title missing]
pages
1620 - 1625
conference name
2010 IEEE Multi-Conference on Systems and Control
external identifiers
  • WOS:000286943900213
  • Scopus:78649434120
DOI
10.1109/CCA.2010.5611242
language
English
LU publication?
yes
id
162d011a-3c44-4841-a313-66a6765f10d8 (old id 1774624)
date added to LUP
2011-01-28 10:02:56
date last changed
2016-10-13 04:52:00
@misc{162d011a-3c44-4841-a313-66a6765f10d8,
  abstract     = {Recent years’ progress in the development of Continuous Glucose Monitors (CGM) has made rich well-sampled glucose data readily available. Reliable, frequent measurements are of outmost importance for the emerging closed-loop control of diabetic plasma glucose. However, these sensors do not measure the variable of primary interest - plasma glucose, but a delayed signal - the interstitial glucose. To overcome this difficulty this paper presents a novel model, merging a black-box model of the glucose dynamics together with a CGM sensor model. Using an observer the plasma glucose level is estimated and predicted. The outlined scheme was evaluated on one patient, with a significant sensor delay, from a clinical trial of the DIAdvisor European FP7-project. Using the raw signal from the CGM device together with meal and insulin infusion data predictions for 20, 40 and 60 min were produced for a breakfast meal. Results: RMSE of the prediction error was smaller than 26 mg/dl for validation data even for the longest prediction horizon and no points in the C/D/E zones in the pCGA evaluation. The model clearly outperformed the CGMS and the results indicate that the method could be used successfully.},
  author       = {Ståhl, Fredrik and Johansson, Rolf},
  language     = {eng},
  pages        = {1620--1625},
  series       = {[Host publication title missing]},
  title        = {Observer Based Plasma Glucose Prediction in Type I Diabetes},
  url          = {http://dx.doi.org/10.1109/CCA.2010.5611242},
  year         = {2010},
}