التفاصيل البيبلوغرافية
العنوان: |
A novel model-based estimator for real-time prediction of insulin-on-board. |
المؤلفون: |
Aiello, Eleonora M.1,2 (AUTHOR), Wolkowicz, Kelilah L.3 (AUTHOR), Pinsker, Jordan E.2 (AUTHOR), Dassau, Eyal1,2 (AUTHOR), Doyle III, Francis J.1,2 (AUTHOR) frank_doyle@seas.harvard.edu |
المصدر: |
Chemical Engineering Science. Mar2023, Vol. 267, pN.PAG-N.PAG. 1p. |
مصطلحات موضوعية: |
*KALMAN filtering, *TYPE 1 diabetes, *INSULIN therapy, *INSULIN pumps, *MEASUREMENT errors, *ARTIFICIAL pancreases |
مستخلص: |
• People with Type 1 Diabetes need insulin injections to keep glycemia in a safe range. • A risk can occur if the estimate of active insulin and insulin action time is not accurate. • Current active insulin estimate does not account for physiological conditions • Real-time estimation of active insulin can be enhanced by using an insulin sensor • Patient-tailored active insulin estimates are obtained by an extended Kalman filter. The availability of insulin measurements can improve automated insulin delivery technology for people with type 1 diabetes, who require exogenous insulin delivery. To reduce the risk of hypo- or hyperglycemia, there is a strong need of calculating the amount of insulin that is yet to become active from the previous doses, known as the insulin-on-board. In this work, we propose an approach for the real-time estimation of insulin-on-board by means of an extended Kalman filter based on actual insulin levels measured using a microchip-based immunoassay. Moreover, the availability of further insulin measurements, collected with high accuracy by the laboratory-based ELISA, allows the development of a probabilistic description of the insulin measurement error, which is exploited in the tuning of the extended Kalman filter. The proposed approach for real-time quantification of the insulin-on-board will allow an informed refinement of insulin dosing, especially under varied conditions including stress and exercise. [ABSTRACT FROM AUTHOR] |
قاعدة البيانات: |
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