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
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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1774624
- author
- Ståhl, Fredrik
LU
and Johansson, Rolf
LU
- organization
- publishing date
- 2010
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proc. 2010 IEEE Multi-conference on Systems and Control (MSC2010), September 8-10, 2010, Yokohama, Japan.
- pages
- 1620 - 1625
- conference name
- 2010 IEEE Multi-Conference on Systems and Control
- conference location
- Yokohama, Japan
- conference dates
- 2010-09-08
- external identifiers
-
- wos:000286943900213
- scopus:78649434120
- DOI
- 10.1109/CCA.2010.5611242
- project
- DIAdvisor
- language
- English
- LU publication?
- yes
- id
- 162d011a-3c44-4841-a313-66a6765f10d8 (old id 1774624)
- date added to LUP
- 2016-04-04 12:54:42
- date last changed
- 2022-01-29 23:30:26
@inproceedings{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}},
booktitle = {{Proc. 2010 IEEE Multi-conference on Systems and Control (MSC2010), September 8-10, 2010, Yokohama, Japan.}},
language = {{eng}},
pages = {{1620--1625}},
title = {{Observer-Based Plasma Glucose Prediction in Type I Diabetes}},
url = {{http://dx.doi.org/10.1109/CCA.2010.5611242}},
doi = {{10.1109/CCA.2010.5611242}},
year = {{2010}},
}