Identification of empirical dynamic models from type 1 diabetes subject data

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...

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Bibliographic Details
Main Authors: Finan, D.A., Palerm, C.C., Doyle, F.J., Zisser, H., Jovanovic, L., Bevier, W.C., Seborg, D.E.
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Automatic control
Biomedical monitoring
Cardiovascular diseases
Diabetes
Insulin
Pi control
Predictive models
Proportional control
Sugar
Online Access:Request full text
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Summary: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 R 2 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.
ISSN:0743-1619
2378-5861
DOI:10.1109/ACC.2008.4586802