BACKGROUND:Extensive past work showed that noninvasive continuous glucose monitoring with a wearable Multisensor device worn on the upper arm provides useful information about glucose trends to improve diabetes therapy in controlled and semicontrolled conditions.METHODS:To test previous findings also in uncontrolled in-clinic and outpatient conditions, a long-term study has been conducted to collect Multisensor and reference glucose data in a population of 20 type 1 diabetes subjects. A total of 1072 study days were collected and a fully on-line compatible algorithmic routine linking Multisensor data to glucose applied to estimate glucose trends noninvasively. The operation of a digital log book, daily semiautomated data transfer and at least 10 daily SMBG values were requested from the patient.RESULTS:Results showed that the Multisensor is capable of indicating glucose trends. It can do so in 9 out of 10 cases either correctly or with one level of discrepancy. This means that in 90% of all cases the Multisensor shows the glucose dynamic to rapidly increase or at least increase.CONCLUSIONS:The Multisensor and the algorithmic routine used in controlled conditions can track glucose trends in all patients, also in uncontrolled conditions. Training of the patient proved to be essential. The workload imposed on patients was significant and should be reduced in the next step with further automation. The feature of glucose trend indication was welcomed and very much appreciated by patients; this value creation makes a strong case for the justification of wearing a wearable.

Background: Extensive past work showed that noninvasive continuous glucose monitoring with a wearable multisensor device worn on the upper arm provides useful information about glucose trends to improve diabetes therapy in controlled and semicontrolled conditions. Method: To test previous findings also in uncontrolled conditions, a long term at home study has been organized to collect multisensor and reference glucose data in a population of 20 type 1 diabetes subjects. A total of 1072 study days were collected and a fully on-line compatible algorithmic routine linking multisensor data to glucose applied to estimate glucose levels noninvasively. Results: The algorithm used here calculates glucose values from sensor data and adds a constant obtained by a daily calibration. It provides point inaccuracy measured by a MARD of 35.4 mg/dL on test data. This is higher than current state-of-the-art minimally invasive devices, but still 86.9% of glucose rate points fall within the zone AR+BR. Conclusions: The multisensor device and the algorithmic routine used earlier in controlled conditions tracks glucose changes also in uncontrolled conditions, although with lower accuracy. The examination of learning curves suggests that obtaining more data would not improve the results. Therefore, further efforts would focus on the development of more complex algorithmic routines able to compensate for environmental and physiological confounders better.

BACKGROUND:We study here the influence of different patients and the influence of different devices with the same patients on the signals and modeling of data from measurements from a noninvasive Multisensor glucose monitoring system in patients with type 1 diabetes. The Multisensor includes several sensors for biophysical monitoring of skin and underlying tissue integrated on a single substrate.METHOD:Two Multisensors were worn simultaneously, 1 on the upper left and 1 on the upper right arm by 4 patients during 16 study visits. Glucose was administered orally to induce 2 consecutive hyperglycemic excursions. For the analysis, global (valid for a population of patients), personal (tailored to a specific patient), and device-specific multiple linear regression models were derived.RESULTS:We find that adjustments of the model to the patients improves the performance of the glucose estimation with an MARD of 17.8% for personalized model versus a MARD of 21.1% for the global model. At the same time the effect of the measurement side is negligible. The device can equally well measure on the left or right arm. We also see that devices are equal in the linear modeling. Thus hardware calibration of the sensors is seen to be sufficient to eliminate interdevice differences in the measured signals.CONCLUSIONS:We demonstrate that the hardware of the 2 devices worn on the left and right arms are consistent yielding similar measured signals and thus glucose estimation results with a global model. The 2 devices also return similar values of glucose errors. These errors are mainly due to nonstationarities in the measured signals that are not solved by the linear model, thus suggesting for more sophisticated modeling approaches.

A general simulation framework has been developed for characterising eye motion artefacts in the ophthalmic imaging of ocular media. The optimisation of the scanning strategy for an optical coherence tomography of the anterior eye chamber has been presented as the first example of an application for the simulator.

Demographic development in the past years has shown that populations are growing older. This leads to more patients with chronic diseases. Chronic Obstructive Pulmonary Disease (COPD) is one such chronic disease and is the fourth leading cause of death worldwide [1]. To mitigate the effects of COPD, fast detection of exacerbation episodes is essential. This project will combine the expertise of Biovotion in multi-sensor development for healthcare applications with those of HES-SO in the integration and evaluation of multi-variate data. The results of this collaboration will be a Swiss telemedicine eHealth environment to monitor patients affected with COPD and be able to recognise or even predict episodes of exacerbation.

In diabetes research, non-invasive continuous glucose monitoring (NI-CGM) devices represent a new and appealing frontier. In the last years, some multi-sensor devices for NI-CGM have been proposed, which exploit several sensors measuring phenomena of different nature, not only for measuring glucose related signals, but also signals reflecting some possible perturbing processes (temperature, blood perfusion). Estimation of glucose levels is then obtained combining these signals through a mathematical model which requires an initial calibration step exploiting one reference blood glucose (RBG) sample. Even if promising results have been obtained, especially in hospitalized volunteers, at present the temporal accuracy of NI-CGM sensors may suffer because of environmental and physiological interferences. The aim of this work is to develop a general methodology, based on Monte Carlo (MC) simulation, to assess the robustness of the calibration step used by NI-CGM devices against these disturbances. The proposed methodology is illustrated considering two examples: the first concerns the possible detrimental influence of sweat events, while the second deals with calibration scheduling. For implementing both examples, 45 datasets collected by the Solianis Multisensor system are considered. In the first example, the MC methodology suggests that no further calibration adjustments are needed after the occurrence of sweat events, because the "Multisensor+model" system is able to deal with the disturbance. The second case study shows how to identify the best time interval to update the model's calibration for improving the accuracy of the estimated glucose. The methodology proposed in this work is of general applicability and can be helpful in making those incremental steps in NI-CGM devices development needed to further improve their performance.

Continuous glucose monitoring (CGM) by suitable portable sensors plays a central role in the treatment of diabetes, a disease currently affecting more than 350 million people worldwide. Noninvasive CGM (NI-CGM), in particular, is appealing for reasons related to patient comfort (no needles are used) but challenging. NI-CGM prototypes exploiting multisensor approaches have been recently proposed to deal with physiological and environmental disturbances. In these prototypes, signals measured noninvasively (e.g., skin impedance, temperature, optical skin properties, etc.) are combined through a static multivariate linear model for estimating glucose levels. In this work, by exploiting a dataset of 45 experimental sessions acquired in diabetic subjects, we show that regularisation-based techniques for the identification of the model, such as the least absolute shrinkage and selection operator (better known as LASSO), Ridge regression, and Elastic-Net regression, improve the accuracy of glucose estimates with respect to techniques, such as partial least squares regression, previously used in the literature. More specifically, the Elastic-Net model (i.e., the model identified using a combination of and norms) has the best results, according to the metrics widely accepted in the diabetes community. This model represents an important incremental step toward the development of NI-CGM devices effectively usable by patients.

In this review, we present an overview of the state of the art concerning the fundamental properties of electrode polarization (EP) of interest in the measurement of high conductivity samples and its implications for both dielectric (DS) and impedance spectroscopy (IS). Initially a detailed description of what constitutes EP is provided and the problems that it induces. Then, we review some of the more popular models that have been used to describe the physical phenomena behind the formation of the ionic double layer. Following this we shall enumerate the common strategies used historically to correct its influence on the measured signals in DS or in IS. Finally we also review recent attempts to employ fractal electrodes to bypass the effects of EP and to offer some physical explanation as to the limitations of their use.

In this, the third part of our series on the dielectric spectrum symmetrical broadening of water, we consider the nucleotide aqueous solutions. Where in Parts I [E. Levy et al., J. Chem. Phys. 136, 114502 (2012)10.1063/1.3687914] and II [E. Levy et al., J. Chem. Phys. 136, 114503 (2012)10.1063/1.3691183], the dipole–dipole or ion–dipole interaction had a dominant feature, now the interplay between these two types of dipole–matrix interactions will be considered. We present the results of high frequency dielectric measurements of different concentrations of adenosine monophosphate/adenosine-5′-triphosphate aqueous solutions. We observed the Cole-Cole broadening of the main relaxation peak of the solvent in the solutions. Moreover, depending on the nucleotide concentration, we observed both types of dipole–matrix interaction. The 3D trajectory approach (described in detail in Part I) is applied in order to highlight the differences between the two types of interaction.

The dielectric response of biconcave erythrocytes exposed to d-glucose and l-glucose has been investigated using a double array of planar interdigitated microelectrodes on a glass microchip. Erythrocytes are analyzed under physiological conditions suspended in hypo-osmolar balanced solutions containing different glucose concentrations (0–20 mM). The glucose effect on the cellular dielectric properties is evaluated by analyzing the spectra using two different approaches, the equivalent circuit model and a modified model for ellipsoidal particles. The results show that at elevated glucose concentration (15 mM) the membrane capacitance increases by 36%, whereas the cytosol conductivity slightly decreases with a variation of about 15%. On the contrary, no variation has been registered with l-glucose, a biologically inactive enantiomer of d-glucose. The paper discusses the possible mechanism controlling the membrane dielectric response. As the external d-glucose increases, the number of activated glucose transporter in the erythrocyte membrane raises and the transition from sugar-free state to sugar-bounded state induces a change in the dipole moments and in the membrane capacitance.

Non-invasive continuous glucose monitoring (NI-CGM) sensors are still at an early stage of development, but, in the near future, they could become particularly appealing in diabetes management. Solianis Monitoring AG (Zurich, Switzerland) has proposed an approach for NI-CGM based on a multi-sensor concept, embedding primarily dielectric spectroscopy and optical sensors. This concept requires a mathematical model able to estimate glucose levels from the 150 channels directly measured through the Multisensor. A static multivariate linear regression model (with order and parameters common to the entire population of subjects) was proposed for such a scope (Caduff et al., Biosens Bioelectron 26:3794–3800, 2011). The aim of this work is to evaluate the accuracy in the estimation of glucose levels and trends that the NI-CGM Multisensor platform can achieve by exploiting different techniques for model identification, namely, ordinary least squares, subset variable selection, partial least squares and least absolute shrinkage and selection operator (LASSO). Data collected in human beings monitored for a total of 45 study days were used for model identification and model test. Several metrics of standard use in the diabetes scientific community to measure point and clinical accuracy of glucose sensors were used to assess the models. Results indicate that the LASSO technique is superior to the others shrinking many channel weights to zero thus leading to smoother glucose profiles and resulting in a more robust model to possible artifacts in the Multisensor data. Although, as expected, the performance of the NI-CGM system with the LASSO model is not yet comparable with that of enzyme-based needle glucose sensors, glucose trends are satisfactorily estimated. Considering the non-invasive nature of the multi-sensor platform, this result can have an immediate impact in the current clinical practice, e.g., to integrate sparse self-monitoring of blood glucose data with an indication of the glucose trend to aid the diabetic patient in dealing with, or even preventing in the short time scale, the threats of critical events such as hypoglycaemia.

Hyperglycaemia is well known to cause reductions in plasma Na+ levels or even hyponatraemia due to an osmotically induced dilution of the interstitium and blood. It is, however, unclear whether this dilution is significantly counteracted by ion regulatory homeostatic mechanism(s) or not. Furthermore, the effects of moderate hyperglycaemia on other major ions are less well known. To further clarify these questions, we measured the changes in blood osmolarity and concentrations of Na+, K+, Cl−, Mg2+ and Ca2+ during a 4-h-long experimental hyperglycaemia in healthy subjects rendered temporarily insulin deficient using the hyperglycaemic clamp. Hyperglycaemia, 16.8 mM, was rapidly imposed from a baseline of 4.4 mM by intravenous somatostatin and glucose infusions in 19 healthy subjects (10 m, 9 f; age 36 ± 5 years (mean ± SD); BMI 22.7 ± 2.9 kg/m²). Subsequently, glycaemia was returned to basal and measurements continued until all dynamic changes had stopped (at ~8 h). Osmolarity increased from 281.8 ± 0.7 to 287.9 ± 0.7, while Na+ decreased from 143.9 ± 0.3 to 138.7 ± 0.2, Cl− from 101.7 ± 0.2 to 99.5 ± 0.1, Ca2+ from 1.98 ± 0.04 to 1.89 ± 0.02 and Mg2+ from 0.84 ± 0.01 to 0.80 ± 0.00 mM. All these changes were rapidly reaching stable levels. K+ increased from 4.02 ± 0.02 to 4.59 ± 0.02 mM (P < 0.0001) also reaching stable levels but with some delay. Na+, Cl−, Mg2+ and Ca2+ are essentially determined by blood dilution, and their values will remain diminished as long as the hyperglycaemia lasts. Partial suppression of insulin-stimulated Na+/K+ pumping lead to increased K+ levels. The combination of elevated K+ and decreased Mg2+ and Ca2+ levels may lead to an altered excitability, which is particularly relevant for diabetic patients with heart disease.

Background: Insulin jet injectors use a high-velocity jet to deliver insulin into the subcutaneous region without penetrating the skin with a needle. The pharmacodynamic and pharmacokinetic profile of rapid-acting insulin using this method of insulin administration is unknown.Methods: Euglycaemic glucose clamp tests were performed in 18 healthy volunteers (M/F 5/13; age 27±9 years, BMI 23.6±2.8 kg/m 2) after subcutaneous administration of 0.2 U/kg aspart insulin, either by jet injection or by conventional pen injection, using a double-blind, double-dummy cross-over study design.Results: The time to maximal exogenous glucose infusion rate (GIR) was 51±3 min with the jet injector versus 105±11 min with the insulin pen (P= 0.0001). There was no difference in the maximal GIR between the two modes of insulin administration (6.49±0.58 versus 6.09±0.56 mg/kg/min, P= 0.50), but the duration of the glucose …

A fringing field capacitive sensor has been used to measure the dielectric properties of human skin and underlying tissue in the MHz frequency range. It has recently been shown in clinical experimental studies that these dielectric properties can be related to the effects of in vivo glucose variations of the test subject. Previously, the relationship between electrical impedance and the glucose level has been established via statistical methods, such as the regression method. In this work, we explored a different approach, namely the resolution of the so-called inverse problem. First we applied the method on an artificial two-layer lossy system in order to test the sensitivity of the solution to forced changes in the layer properties and its stability to a constant setting. After validation of this method on artificial systems, a similar inverse problem was set and solved for dielectric measurements on human skin during an induced glucose excursion, where the skin is also modelled as a double-layer system. The changes of the measured permittivity and conductivity of the second layer versus the glucose changes are calculated for 22 study days. The statistical distribution shows that the median slopes of both dielectric properties are negative. These results can be used to test our hypothesis and to continue building potential explanations for the phenomena induced by the glucose changes on the skin layer dielectric parameters.