Josep Vehí

Estimating Plasma Glucose from Interstitial Glucose: The Issue of Calibration Algorithms in Commercial Continuous Glucose Monitoring Devices

Evaluation of metabolic control of diabetic people has been classically performed measuring glucose concentrations in blood samples. Due to the potential improvement it offers in diabetes care, continuous glucose monitoring (CGM) in the subcutaneous tissue is gaining popularity among both patients and physicians. However, devices for CGM measure glucose concentration in compartments other than blood, usually the interstitial space. This means that CGM need calibration against blood glucose values, and the accuracy of the estimation of blood glucose will also depend on the calibration algorithm. The complexity of the relationship between glucose dynamics in blood and the interstitial space, contrasts with the simplistic approach of calibration algorithms currently implemented in commercial CGM devices, translating in suboptimal accuracy. The present review will analyze the issue of calibration algorithms for CGM, focusing exclusively on the commercially available glucose sensors.

A Survey on Interval Model Simulators and their Properties Related to Fault Detection

Abstract The imprecision and the uncertainty of many systems can be expressed with interval models. The results of the simulation of these models can be represented by envelopes. These envelopes can be characterised by several properties such as completeness or soundness that lead to the concepts of overbounded and underbounded envelopes. The simulation of such interval models can be performed by several means including qualitative and semiqualitative methods as well as quantitative simulation based ones. A brief description of the different types of simulators is presented and their respective properties are outlined and compared in relation to model-based fault detection.

Output feedback sliding mode control of base isolated structures

Abstract The paper addresses the problem of designing stabilizing output feedback controllers for a class of nonlinear seismically excited base isolated structures with unknown parametrical uncertainties. Two types (non-adaptive and adaptive) of sliding mode controllers are presented. In both schemes, only the information on the displacements and velocities of the base and the first floor is used in the controller design. A numerical example is given to illustrate the effectiveness of the proposed strategy to a 10-storey frictional base isolated structure being subject to the El Centro earthquake.

Fault detection and isolation of the three-tank system using the modal interval analysis

Abstract Analytical redundancy is a widely used technique for fault detection. It consists of comparing the behaviour of a real system with a reference obtained by simulation of its model. The main problem is that there are always imprecisions and uncertainties which are not represented in the model so the behaviour of the real system and the behaviour of the model are not exactly the same. One way to represent these uncertainties in the model is using interval models. The results of the simulation of these types of models may be represented by envelopes. This paper proposes an approach to generate envelopes based on interval techniques of the modal interval analysis. As an example, this approach is used to detect and isolate faults in a physical system formed by three interconnected tanks.

Composite semiactive control of a class of seismically excited structures

Abstract The paper deals with the formulation of semiactive controllers for a class of nonlinear seismically excited base-isolated structures in order to reduce the absolute motion of the base and the inter-story drifts of the building structure. The advantage of the proposed control scheme is that semiactive control devices are only required at the base and the first floor to adjust on-line the damping and stiffness using their displacements and velocities as feedback information. The feedback control law is derived and analyzed via Lyapunov stability techniques. A numerical example is given to illustrate the effectiveness of the control scheme for a 10-story frictional base-isolated structure subject to seismic actions.

Quantified Set Inversion Algorithm with Applications to Control

In this paper, a new algorithm based on Set Inversion techniques and Modal Interval Analysis is presented. This algorithm allows one to solve problems involving quantified constraints over the reals through the characterization of their solution sets. The presented methodology can be applied to a wide range of problems involving uncertain (non)linear systems. Finally, an advanced application is solved.

Real-Time Continuous Glucose Monitoring in an Intensive Care Unit: Better Accuracy in Patients with Septic Shock

OBJECTIVE This study assessed the accuracy of real-time continuous glucose monitoring system (RTCGMS) devices in an intensive care unit (ICU) to determine whether the septic status of the patient has any influence on the accuracy of the RTCGMS. SUBJECTS AND METHODS In total, 41 patients on insulin therapy were included. Patients were monitored for 72 h using RTCGMS. Arterial blood glucose (ABG) samples were obtained following the protocol established in the ICU. The results were evaluated using paired values (excluding those used for calibration) with the performance assessed using numerical accuracy. Nonparametric tests were used to determine statistically significant differences in accuracy. RESULTS In total, 956 ABG/RTCGMS pairs were analyzed. The overall median relative absolute difference (RAD) was 13.5%, and the International Organization for Standardization (ISO) criteria were 68.1%. The median RADs reported for patients with septic shock, with sepsis, and without sepsis were 11.2%, 14.3%, and 16.3%, respectively (P<0.05). Measurements meeting the ISO criteria were 74.5%, 65.6%, and 63.7% for patients with septic shock, with sepsis, and without sepsis, respectively (P<0.05). CONCLUSIONS The results showed that the septic status of patients influenced the accuracy of the RTCGMS in the ICU. Accuracy was significantly better in patients with septic shock in comparison with the other patient cohorts.

Robust Fault Detection System for Insulin Pump Therapy Using Continuous Glucose Monitoring

Background: The popularity of continuous subcutaneous insulin infusion (CSII), or insulin pump therapy, as a way to deliver insulin more physiologically and achieve better glycemic control in diabetes patients has increased. Despite the substantiated therapeutic advantages of using CSII, its use has also been associated with an increased risk of technical malfunctioning of the device, which leads to an increased risk of acute metabolic complications, such as diabetic ketoacidosis. Current insulin pumps already incorporate systems to detect some types of faults, such as obstructions in the infusion set, but are not able to detect other types of fault such as the disconnection or leakage of the infusion set. Methods: In this article, we propose utilizing a validated robust model-based fault detection technique, based on interval analysis, for detecting disconnections of the insulin infusion set. For this purpose, a previously validated metabolic model of glucose regulation in type 1 diabetes mellitus (T1DM) and a continuous glucose monitoring device were used. As a first step to assess the performance of the presented fault detection system, a Food and Drug Administration-accepted T1DM simulator was employed. Results: Of the 100 in silico tests (10 scenarios on 10 subjects), only two false negatives and one false positive occurred. All faults were detected before plasma glucose concentration reached 300 mg/dl, with a mean plasma glucose detection value of 163 mg/dl and a mean detection time of 200 min. Conclusions: Interval model-based fault detection has been proven (in silico) to be an effective tool for detecting disconnection faults in sensor-augmented CSII systems. Proper quantification of the uncertainty associated with the employed model has been observed to be crucial for the good performance of the proposed approach.

Robust Sliding Mode Closed-loop Glucose Control with Meal Compensation in Type 1 Diabetes Mellitus

Abstract This work addresses the design of a robust closed-loop plasma glucose controller for Type 1 Diabetes Mellitus patients. The feedback controller is based on Sliding Mode Control (SMC) while robust feedforward boluses to compensate food intake are calculated in a robust way by means of an interval glucose predictor that minimizes the risk of hypoglycaemia. The designed controller has been validated in a virtual environment following standard protocols. The resulting control algorithm shows a considerable robustness regarding intra-patient variability in insulin sensitivity as well as an enhanced ability to handle disturbance rejection. The International Diabetes Federation guidelines for glycaemia targets in Diabetes Mellitus are fulfilled by the designed control strategy.

Real-Time Glucose Estimation Algorithm for Continuous Glucose Monitoring Using Autoregressive Models

Background: Continuous glucose monitors (CGMs) present a problem of lack of accuracy, especially in the lower range, sometimes leading to missed or false hypoglycemia. A new algorithm is presented here aimed at improving the measurement accuracy and hypoglycemia detection. Its core is the estimation of blood glucose (BG) in real time (RT) from CGM intensity readings using autoregressive (AR) models. Methods: Eighteen patients with type 1 diabetes were monitored for three days (one at the hospital and two at home) using the CGMS® Gold. For these patients, BG samples were taken every 15 min for 2 h after meals and every half hour otherwise during the first day. The relationship between the current measured by the CGMS Gold and BG was learned by an AR model, allowing its RT estimation. New capillary glucose measurements were used to correct the model BG estimations. Results: A total of 563 paired points were obtained from BG and monitor readings to validate the new algorithm. 98.5% of paired points fell in zones A+B of the Clarke error grid analysis with the proposed algorithm. The overall mean and median relative absolute differences (RADs) were 9.6% and 6.7%. Measurements meeting International Organization for Standardization (ISO) criteria were 88.7%. In the hypoglycemic range, the mean and median RADs were 8.1% and 6.0%, and measurements meeting ISO criteria were 86.7%. The sensitivity and specificity with respect to hypoglycemia detection were 91.5% and 95.0%. Conclusions: The performance measured with both clinical and numerical accuracy metrics illustrates the improved accuracy of the proposed algorithm compared with values presented in the literature. A significant improvement in hypoglycemia detection was also observed.