DocumentCode :
3628442
Title :
Identification of empirical dynamic models from type 1 diabetes subject data
Author :
Daniel A. Finan;Cesar C. Palerm;Francis J. Doyle;Howard Zisser;Lois Jovanovic;Wendy C. Bevier;Dale E. Seborg
Author_Institution :
Dept. of Chemical Engineering, University of California, Santa Barbara, 93106-5080, USA
fYear :
2008
Firstpage :
2099
Lastpage :
2104
Abstract :
Empirical linear dynamic models have been identified from ambulatory data from two type 1 diabetes subjects in order to determine approximately how far into the future the models could be expected to make reasonably accurate predictions. For a prediction horizon of 30 minutes, FIT values (related to R2 values) of the model predictions for validation data were 46% for one subject and 60% for the other subject. These FIT values correspond to root mean square errors of 14 and 24 mg/dL, respectively. Longer prediction horizons resulted in substantially worse predictions for these ambulatory subject data.
Keywords :
"Diabetes","Predictive models","Sugar","Insulin","Automatic control","Accuracy","Cardiovascular diseases","Pi control","Proportional control","Biomedical monitoring"
Publisher :
ieee
Conference_Titel :
American Control Conference, 2008
ISSN :
0743-1619
Print_ISBN :
978-1-4244-2078-0
Electronic_ISBN :
2378-5861
Type :
conf
DOI :
10.1109/ACC.2008.4586802
Filename :
4586802
Link To Document :
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