Szalay, Péter and Benyó, Zoltán and Kovács, Levente (2016) Long-Term Prediction for T1DM Model During State-Feedback Control. In: 12th IEEE International Conference on Control & Automation. IEEE, [Piscataway, NJ], pp. 311-316.
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Abstract
Avoiding low glucose concentration is critically important in type-1 diabetes treatment. Predicting the future plasma glucose levels could ensure the safety of the patient. However, such estimation is no trivial task. The current paper proposes a predictor framework which stems from Unscented Kalman filter and works during closed-loop control, that can predict hazardous glucose levels in advance. Once the blood glucose concentration starts to rise, the predictor activates and estimates future glucose levels up to 3 hours, confirming whether the controller can endanger the patient. The capabilities of the framework is presented through simulations based on the SimEdu validated in-silico simulator.
| Item Type: | Book Section |
|---|---|
| Additional Information: | MTMT: 3166809 Konferencia helye, ideje: Kathmandu, Nepál, 2016.06. |
| Subjects: | T Technology / alkalmazott, műszaki tudományok > T2 Technology (General) / műszaki tudományok általában T Technology / alkalmazott, műszaki tudományok > TA Engineering (General). Civil engineering (General) / általános mérnöki tudományok |
| SWORD Depositor: | MTMT SWORD |
| Depositing User: | MTMT SWORD |
| Date Deposited: | 15 Jan 2017 11:10 |
| Last Modified: | 15 Jan 2017 11:10 |
| URI: | http://real.mtak.hu/id/eprint/45552 |
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