Abstract
We propose a method to identify diurnal changes in insulin action in patients suffering from type 1 diabetes mellitus (T1DM) based on data recorded by continuous glucose monitoring systems (CGMS). In order to do so the data is fitted using a continuous time transfer function including time dependent terms. The identified values for the insulin needs per gram of carbohydrate were compared with the patient-specific carbohydrate-to-insulin-ratios used for the calculation of the bolus insulin needs. A good agreement between the identified parameters and values determined by diabetologists were found. Furthermore, the diurnal variations in insulin action (as inferred from the changes in the patient-specific carbohydrate-to-insulin-ratios) could be reproduced. The identified models, including the diurnal changes in insulin action and the information on the intra-patient variability, have the potential to be used in future studies for managing the blood glucose level of patients, e.g. in a smart bolus calculator.
| Original language | English |
|---|---|
| Title of host publication | 2015 European Control Conference, ECC 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1-6 |
| Number of pages | 6 |
| ISBN (Electronic) | 9783952426937 |
| DOIs | |
| Publication status | Published - 16 Nov 2015 |
| Externally published | Yes |
| Event | European Control Conference, ECC 2015 - Linz, Austria Duration: 15 Jul 2015 → 17 Jul 2015 |
Publication series
| Name | 2015 European Control Conference, ECC 2015 |
|---|
Conference
| Conference | European Control Conference, ECC 2015 |
|---|---|
| Country/Territory | Austria |
| City | Linz |
| Period | 15.07.2015 → 17.07.2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Keywords
- Biomedical Systems
- Blood Glucose Control
- System Identification
- Type 1 Diabetes
Fingerprint
Dive into the research topics of 'Identification of diurnal patterns in insulin action from measured CGM data for patients with T1DM'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver