First Experiences With a Wearable Multisensor Device in a Noninvasive Continuous Glucose Monitoring Study at Home, Part II: The Investigators' View.

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.

The Effect of a Global, Subject, and Device-Specific Model on a Noninvasive Glucose Monitoring Multisensor System.

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.

Non-invasive continuous glucose monitoring with multi-sensor systems: a Monte Carlo-based methodology for assessing calibration robustness.

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.

Dielectric spectra broadening as a signature for dipole-matrix interaction. III. Water in adenosine monophosphate/adenosine-5'-triphosphate solutions.

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)] and II [E. Levy et al., J. Chem. Phys. 136, 114503 (2012)], 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.

Non-invasive continuous glucose monitoring: improved accuracy of point and trend estimates of the Multisensor system.

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.

A 4-h hyperglycaemic excursion induces rapid and slow changes in major electrolytes in blood in healthy human subjects.

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(-), Mg(2+) and Ca(2+) 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/m(2)). 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, Ca(2+) from 1.98 ± 0.04 to 1.89 ± 0.02 and Mg(2+) 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(-), Mg(2+) and Ca(2+) 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 Mg(2+) and Ca(2+) levels may lead to an altered excitability, which is particularly relevant for diabetic patients with heart disease.

Sensitivity and specificity analysis of fringing-field dielectric spectroscopy applied to a multi-layer system modelling the human skin.

The sensitivity and specificity of dielectric spectroscopy for the detection of dielectric changes inside a multi-layered structure is investigated. We focus on providing a base for sensing physiological changes in the human skin, i.e. in the epidermal and dermal layers. The correlation between changes of the human skin's effective permittivity and changes of dielectric parameters and layer thickness of the epidermal and dermal layers is assessed using numerical simulations. Numerical models include fringing-field probes placed directly on a multi-layer model of the skin. The resulting dielectric spectra in the range from 100 kHz up to 100 MHz for different layer parameters and sensor geometries are used for a sensitivity and specificity analysis of this multi-layer system. First, employing a coaxial probe, a sensitivity analysis is performed for specific variations of the parameters of the epidermal and dermal layers. Second, the specificity of this system is analysed based on the roots and corresponding sign changes of the computed dielectric spectra and their first and second derivatives. The transferability of the derived results is shown by a comparison of the dielectric spectra of a coplanar probe and a scaled coaxial probe. Additionally, a comparison of the sensitivity of a coaxial probe and an interdigitated probe as a function of electrode distance is performed. It is found that the sensitivity for detecting changes of dielectric properties in the epidermal and dermal layers strongly depends on frequency. Based on an analysis of the dielectric spectra, changes in the effective dielectric parameters can theoretically be uniquely assigned to specific changes in permittivity and conductivity. However, in practice, measurement uncertainties may degrade the performance of the system.

Data processing for noninvasive continuous glucose monitoring with a multisensor device.

BACKGROUND: Impedance spectroscopy has been shown to be a candidate for noninvasive continuous glucose monitoring in humans. However, in addition to glucose, other factors also have effects on impedance characteristics of the skin and underlying tissue. METHOD: Impedance spectra were summarized through a principal component analysis and relevant variables were identified with Akaike's information criterion. In order to model blood glucose, a linear least-squares model was used. A Monte Carlo simulation was applied to examine the effects of personalizing models. RESULTS: The principal component analysis was able to identify two major effects in the impedance spectra: a blood glucose-related process and an equilibration process related to moisturization of the skin and underlying tissue. With a global linear least-squares model, a coefficient of determination (R²) of 0.60 was achieved, whereas the personalized model reached an R² of 0.71. The Monte Carlo simulation proved a significant advantage of personalized models over global models. CONCLUSION: A principal component analysis is useful for extracting glucose-related effects in the impedance spectra of human skin. A linear global model based on Solianis Multisensor data yields a good predictive power for blood glucose estimation. However, a personalized linear model still has greater predictive power.

Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation.

The Multisensor Glucose Monitoring System (MGMS) features non invasive sensors for dielectric characterisation of the skin and underlying tissue in a wide frequency range (1 kHz-100 MHz, 1 and 2 GHz) as well as optical characterisation. In this paper we describe the results of using an MGMS in a miniaturised housing with fully integrated sensors and battery. Six patients with Type I Diabetes Mellitus (age 44±16 y; BMI 24.1±1.3 kg/m(2), duration of diabetes 27±12 y; HbA1c 7.3±1.0%) wore a single Multisensor at the upper arm position and performed a total of 45 in-clinic study days with 7 study days per patient on average (min. 5 and max. 10). Glucose changes were induced either orally or by i.v. glucose administration and the blood glucose was measured routinely. Several prospective data evaluation routines were applied to evaluate the data. The results are shown using one of the restrictive data evaluation routines, where measurements from the first 22 study days were used to train a linear regression model. The global model was then prospectively applied to the data of the remaining 23 study days to allow for an external validation of glucose prediction. The model application yielded a Mean Absolute Relative Difference of 40.8%, a Mean Absolute Difference of 51.9 mg dL(-1), and a correlation of 0.84 on average per study day. The Clarke error grid analyses showed 89.0% in A+B, 4.5% in C, 4.6% in D and 1.9% in the E region. Prospective application of a global, purely statistical model, demonstrates that glucose variations can be tracked non invasively by the MGMS in most cases under these conditions.

Assessment of linear regression techniques for modeling multisensor data for non-invasive continuous glucose monitoring.

New scenarios in diabetes treatment have been opened in the last ten years by continuous glucose monitoring (CGM) sensors. In particular, Non-Invasive CGM sensors are particularly appealing, even though they are still at an early stage of development. Solianis Monitoring AG (Zürich, Switzerland) has proposed an approach based on a multisensor concept, embedding primarily dielectric spectroscopy and optical sensors. This concept requires a mathematical model able to reconstruct the glucose concentration from the 150 channels measured with the device. Assuming a multivariate linear regression model (valid and usable for different individuals), the aim of this paper is the assessment of some techniques usable for determining such a model, namely Ordinary Least Squares (OLS), Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO). Once the model is identified on a training set, the accuracy of prospective glucose profiles estimated from "unseen" multisensor data is assessed. Preliminary results obtained from 18 in-clinic study days show that sufficiently accurate reconstruction of glucose levels can be achieved if suitable model identification techniques, such as LASSO, are considered.

Cutaneous blood perfusion as a perturbing factor for noninvasive glucose monitoring.

It is widely accepted that noninvasive glucose monitoring (NIGM) has the potential to revolutionize diabetes therapy. However, current approaches to NIGM studied to date have not yet demonstrated a level of acceptable functionality to allow real-time use, beyond restricted fields of application. A number of reviews have been devoted to the subject of NIGM with different focuses related to challenges and a description of the respective underlying problems. This review is aimed at addressing a fundamental topic in the application of NIGM that seems to have received less attention, by describing the perturbations that result in a reduced functionality of NIGM in daily use. Here we provide a short general introduction to glucose monitoring and a basic illustration of the electromagnetic spectrum with a description of the respective physical mechanisms underlying the measurement techniques. This allows for a better understanding of how these perturbing factors affect the measured properties. Cutaneous blood perfusion is one of the major perturbing factors to NIGM, along with variations in temperature, migration of water, and the effect of attachment of the sensor to the skin. An understanding of the mechanisms underlying perfusion variation over time and within the measured human skin tissue matrix is required to enable a discrimination between glucose-induced effects within the tissue and various biophysical impacts to be made. It is suggested that a plurality of probing frequencies is required to discriminate glucose-related changes from the perturbations. A system designed to perform the measurements in different regions of the electromagnetic spectrum with dedicated sensors (multisensor approach) has the potential to more efficiently and reliably discriminate glucose-related information from perturbations. This can be achieved by combining signals related to measurements with different physical underlying mechanisms of the interaction between the probing field propagation and the tissue to help account for the different sources of perturbations.

Validation of human skin models in the MHz region.

The human skin consists of several layers with distinct dielectric properties. Resolving the impact of changes in dielectric parameters of skin layers and predicting them allows for non-invasive sensing in medical diagnosis. So far no complete skin and underlying tissue model is available for this purpose in the MHz range. Focusing on this dispersiondominated frequency region multilayer skin models are investigated: First, containing homogeneous non-dispersive sublayers and second, with sublayers obtained from a three-phase Maxwell-Garnett mixture of shelled cell-like ellipsoids. Both models are numerically simulated using the Finite Element Method, a fringing field sensor on the top of the multilayer system serving as a probe. Furthermore, measurements with the sensor probing skin in vivo are performed. In order to validate the models the uppermost skin layer, the stratum corneum was i) included and ii) removed in models and measurements. It is found that only the Maxwell-Garnett mixture model can qualitatively reproduce the measured dispersion which still occurs without the stratum corneum and consequently, structural features of tissue have to be part of the model.

Non-invasive glucose monitoring in patients with Type 1 diabetes: a Multisensor system combining sensors for dielectric and optical characterisation of skin.

In vivo variations of blood glucose (BG) are affecting the biophysical characteristics (e.g. dielectric and optical) of skin and underlying tissue (SAUT) at various frequencies. However, the skin impedance spectra for instance can also be affected by other factors, perturbing the glucose related information, factors such as temperature, skin moisture and sweat, blood perfusion as well as body movements affecting the sensor-skin contact. In order to be able to correct for such perturbing factors, a Multisensor system was developed including sensors to measure the identified factors. To evaluate the quality of glucose monitoring, the Multisensor was applied in 10 patients with Type 1 diabetes. Glucose was administered orally to induce hyperglycaemic excursions at two different study visits. For analysis of the sensor signals, a global multiple linear regression model was derived. The respective coefficients of the variables were determined from the sensor signals of this first study visit (R(2)=0.74, MARD=18.0%--mean absolute relative difference). The identical set of modelling coefficients of the first study visit was re-applied to the test data of the second study visit to evaluate the predictive power of the model (R(2)=0.68, MARD=27.3%). It appears as if the Multisensor together with the global linear regression model applied, allows for tracking glucose changes non-invasively in patients with diabetes without requiring new model coefficients for each visit. Confirmation of these findings in a larger study group and under less experimentally controlled conditions is required for understanding whether a global parameterisation routine is feasible.

The role of GLUT1 in the sugar-induced dielectric response of human erythrocytes.

We propose a key role for the glucose transporter 1 (GLUT1) in mediating the observed changes in the dielectric properties of human erythrocyte membranes as determined by dielectric spectroscopy. Cytochalasin B, a GLUT1 transport inhibitor, abolished the membrane capacitance changes in glucose-exposed red cells. Surprisingly, D-fructose, known to be transported primarily by GLUT5, exerted similar membrane capacitance changes at increasing D-fructose concentrations. In order to evaluate whether the glucose-mediated membrane capacitance changes originated directly from intracellularly bound adenosine triphosphate (ATP) or other components of the glycolysis process, we studied the dielectric responses of swollen erythrocytes with a decreased ATP content and of nucleotide-filled ghosts. Resealed ghosts containing physiological concentrations of ATP yielded the same glucose-dependent capacitance changes as biconcave intact red blood cells, further supporting the finding that ATP is the effector of the glucose-mediated dielectric response where the ATP concentration is also the mediating factor in swollen red blood cells. The results suggest that ATP binding to GLUT1 elicits a membrane capacitance change that increases with the applied concentration gradient of D-glucose. A simplified model of the membrane capacitance alteration with glucose uptake is proposed.

Dielectrophoretic studies of the activation of human T lymphocytes using a newly developed cell profiling system.

Human T lymphocytes were stimulated using phorbol myristate acetate and ionomycin. Twenty-four hours post-activation the cells were harvested for DNA content and for measurements using a newly developed cell profiling system employing dielectrophoresis. This system provides individual cell size and dielectrophoresis data for statistically relevant numbers of control and activated cells. From this it was determined that the mean membrane specific capacitance decreased from 13.49 (+/- 4.72) mF/m(2) to 10.62 (+/- 5.13) mF/m(2). This can be related to a 21.3% reduction in the effective membrane surface area associated with membrane topography (e.g. reduction of membrane associated microvilli, blebs and folding), or to other changes of membrane architecture, following cell activation. From cytometric determinations of DNA content, it was concluded that these effects were related to a 3.0-fold decrease of cells in S-phase, and a 1.5-fold increase in G1 cells. This work demonstrates the powerful potential of using dielectrophoresis as a noninvasive tool to follow physiological changes that accompany transmembrane signaling events.