LMI-Based Approaches for the Calibration of Continuous Glucose Measurement Sensors.

The problem of online calibration and recalibration of continuous glucose monitoring (CGM) devices is considered. Two different parametric relations between interstitial and blood glucose are investigated and constructive algorithms to adaptively estimate the parameters within those relations are proposed. One characteristic is the explicit consideration of measurement uncertainty of the device used to collect the calibration measurements. Another feature is the automatic detection of fingerstick measurements that are not suitable to be used for calibration. Since the methods rely on the solution of linear matrix inequalities resulting in convex optimization problems, the algorithms are of moderate computational complexity and could be implemented on a CGM device. The methods were assessed on clinical data from 17 diabetic patients and the improvements with respect to the current state of the art is shown.

A novel online recalibration strategy for continuous glucose measurement sensors employing LMI techniques.

This paper considers the problem of online calibration and recalibration of continuous glucose monitoring devices. A parametric relation between interstitial and blood glucose is investigated and a constructive algorithm to adaptively estimate the parameters within this relation is proposed. The algorithm explicitly considers measurement uncertainty of the device used to collect the calibration measurements and enables automatic detection of measurements which are not suitable to be used for calibration. The method was assessed on clinical data from 17 diabetic patients and the improvements with respect to the current state of the art is shown.