In the last decades, mathematical models have become of great importance in the context of diabetes treatment planning. Several modeling approaches, based on first principles or input-output techniques, have been proposed. However, a relevant open problem common to all these approaches is that they are not able to recover or to systematically account for the various unmeasured signals which affect a diabetic patient (e.g. food, physical activity, emotions, etc.). A novel blind identification approach is introduced in this paper, allowing us to model type 1 diabetic patients and to effectively recover the unmeasured input signals. The approach is applied to an experimental study regarding identification and prediction of the blood glucose concentration in five type 1 diabetic patients.

A nonlinear blind identification approach to modeling of diabetic patients / Novara, Carlo; Mohammad Pour, N.; Vincent, T.; Grassi, G.. - In: IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY. - ISSN 1063-6536. - 24:3(2016), pp. 1092-1100. [10.1109/TCST.2015.2462734]

A nonlinear blind identification approach to modeling of diabetic patients

NOVARA, Carlo;
2016

Abstract

In the last decades, mathematical models have become of great importance in the context of diabetes treatment planning. Several modeling approaches, based on first principles or input-output techniques, have been proposed. However, a relevant open problem common to all these approaches is that they are not able to recover or to systematically account for the various unmeasured signals which affect a diabetic patient (e.g. food, physical activity, emotions, etc.). A novel blind identification approach is introduced in this paper, allowing us to model type 1 diabetic patients and to effectively recover the unmeasured input signals. The approach is applied to an experimental study regarding identification and prediction of the blood glucose concentration in five type 1 diabetic patients.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2615648