Search

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.

Recent work has demonstrated that the reflection coefficient of human skin in the frequency range from 95 to 110 GHz (W band) mirrors the temporal relaxation of stress induced by physical exercise. In this work, we extend these findings to show that in the event of a subtle trigger to stress, such as mental activity, a similar picture of response emerges. Furthermore, the findings are extended to cover not only the W band (75-110 GHz), but also the frequency band from 110 to 170 GHz (D band). We demonstrate that mental stress, induced by the Stroop effect and recorded by the galvanic skin response (GSR), can be correlated to the reflection coefficient in the aforementioned frequency bands. Intriguingly, a light physical stress caused by repeated hand gripping clearly showed an elevated stress level in the GSR signal, but was largely unnoted in the reflection coefficient in the D band. The implication of this observation requires further validation.

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 (P0.0001) 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.

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 ( R 2 ) of 0.60 was achieved, whereas the personalized model reached an R 2 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.

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/m2, 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.

A wearable system incorporating sensors for dielectric and optical spectroscopy was used to study skin properties and their dependence on the cutaneous blood content (CBC). Simultaneous measurements with both modalities were carried out on the upper arm during blood perfusion-provoking exercises performed by four subjects in four separate sets of experiments. By relating changes in the attenuation of green (central wavelength λ(c) = 568 nm) and infrared (λ(c) = 798 nm) light, the ratio of mean pathlengths travelled by photons in the skin blood plexus was obtained. The pathlength for infrared light is found to be 3.85 times larger than for green. Combining signals of two wavelengths and accounting for pathlength difference, we quantitatively characterize the CBC as a cumulative optical thickness of red blood cells in the skin plexus. The dielectric spectra of skin in the MHz range were fitted with the Cole-Cole model and the changes of parameters were quantitatively related to the optically derived changes in CBC using a linear regression analysis. The positive correlation with CBC is obtained for the dispersion exponent (R(2) = 0.68), and the negative-for the dispersion time (R(2) = 0.40). Thus dielectric dispersion of the skin gets broader and shifts towards lower frequencies with an increase of CBC.

Changes in morphology of the skin are an important factor that can affect non-invasive measurements performed through this organ, in particular for glucose monitoring in e.g. patients with diabetes mellitus. A characterization technique for non-contact in vivo profiling of the superficial skin layers can be beneficial for evaluation of the performance of such measurement systems. We applied a full-field optical coherence tomography (OCT) system followed by the fully automatic processing for this task. With the developed procedure, non-invasive quantification of the skin morphology can be performed within a few minutes. The dorsal skin of the upper arm of 22 patients with Type 1 Diabetes Mellitus was investigated with an OCT system and with a commercially available dermatological laser scanning confocal microscope (CM) as a reference method. The estimates of epidermal thickness from OCT were compared with the results of expert-assisted analysis of confocal images. The highest correlation with the CM measurements has been obtained for the distance from the entrance peak to the first minimum of the OCT reflection profile (R2 = 0.657, p < 0.0001). In this specific patient group, we have observed a statistically significant correlation of the subjects' body mass index with the distance from the entrance peak to the dermal reflection peak in the OCT profile (p = 0.010). Furthermore, the same OCT parameter is negatively correlated with age with marginal statistical significance (p = 0.062). At the same time, no relation of diabetes-related parameters (duration of disease and concentration of glycated haemoglobin) to the skin morphology observed with the OCT and CM was found.

An optical diffuse reflectance sensor for characterization of cutaneous blood content and optimized for continuous monitoring has been developed as part of a non-invasive multisensor system for glucose monitoring. A Monte Carlo simulation of the light propagation in the multilayered skin model has been performed in order to estimate the optimal geometrical separation of the light source and detector for skin and underlying tissue. We have observed that the pathlength within the upper vascular plexus of the skin which defines the sensor sensitivity initially grows with increasing source-detector distance (SDD) before reaching a maximum at 3.5 mm and starts to decay with further increase. At the same time, for distances above 2.4 mm, the sensor becomes sensitive to muscle blood content, which decreases the specificity to skin perfusion monitoring. Thus, the SDDs in the range from 1.5 mm to 2.4 mm satisfy the requirements of sensor sensitivity and specificity. The hardware implementation of the system has been realized and tested in laboratory experiments with a venous occlusion procedure and in an outpatient clinical study in 16 patients with type 1 diabetes mellitus. For both testing procedures, the optical sensor demonstrated high sensitivity to perfusion change provoking events. The general build-up of cutaneous blood under the sensor has been observed which can be associated with pressure-induced vasodilation as a response to the sensor application.

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.

The aim of this work was to evaluate the performance of a novel non-invasive continuous glucose-monitoring system based on impedance spectroscopy (IS) in patients with diabetes. Ten patients with type 1 diabetes (mean+/-S.D., age 28+/-8 years, BMI 24.2+/-3.2 kg/m(2) and HbA(1C) 7.3+/-1.6%) and five with type 2 diabetes (age 61+/-8 years, BMI 27.5+/-3.2 kg/m(2) and HbA(1C) 8.3+/-1.8%) took part in this study, which comprised a glucose clamp experiment followed by a 7-day outpatient evaluation. The measurements obtained by the NI-CGMD and the reference blood glucose-measuring techniques were evaluated using retrospective data evaluation procedures. Under less controlled outpatient conditions a correlation coefficient of r=0.640 and a standard error of prediction (SEP) of 45 mg dl(-1) with a total of 590 paired glucose measurements was found (versus r=0.926 and a SEP of 26 mg dl(-1) under controlled conditions). Clark error grid analyses (EGA) showed 56% of all values in zone A, 37% in B and 7% in C-E. In conclusion, these results indicate that IS in the used technical setting allows retrospective, continuous and truly non-invasive glucose monitoring under defined conditions for patients with diabetes. Technical advances and developments are needed to expand on this concept to bring the results from the outpatient study closer to those in the experimental section of the study. Further studies will not only help to evaluate the performance and limitations of using such a technique for non non-invasive glucose monitoring but also help to verify technical extensions towards a IS-based concept that offers improved performance under real life operating conditions.

Impedance spectroscopy allows for the assessment of changes in the permittivity and conductivity of erythrocyte cell membranes, induced by blood glucose variations. This study was performed to evaluate the potential influence of motion-induced microvascular blood flow variations from different forearm postures on the PENDRA (Pendragon Medical AG, Zürich, Switzerland) signal. Fifteen volunteers without diabetes were included (seven female, eight male, mean +/- SD age 33.3 +/- 9.9 years, body mass index 24.8 +/- 3.0 kg/m(2)). PENDRA devices were fixed at both upper extremities with different fixation techniques (bracelet and adhesive tape). Standardized position changes of the upper extremities were performed to induce variations in cutaneous microcirculation, which were assessed by laser-Doppler-fluxmetry with different probe temperatures on the forearm. Changes in microcirculation were seen in some of the different motion procedures: supine to hanging, 61.1 +/- 29.9 arbitrary units (AU) to 46.2 +/- 24.8 AU at 37 degrees C and 15.9 +/- 13.0 AU to 13.4 +/- 10.1 at skin temperature (P0.01 for both probes); supine to upright, 80.5 +/- 55.4 AU to 74.9 +/- 43.8 AU (not significant) at 37 degrees C and 18.7 +/- 16.8 AU to 20.9 +/- 16.1 AU at skin temperature (P0.01). An initially observed subtle influence of microcirculation variations on the impedance signal was minimized when the device was fixed by both bracelet and tape. Other influencing factors (such as temperature, local anatomy, etc.) are addressed in the complex calibration procedure. Well-educated patients might be the best candidates for first using the device for continuous glucose monitoring. They may especially benefit from the trend indication and the hypoglycemia/hyperglycemia threshold and alarm functions.

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.

Electrolyte disturbances are well-known consequences of the diabetic pathology. However, less is known about the cumulative effects of repeated changes in glycaemia, a characteristic of diabetes, on the electrolyte balance. We therefore investigated the ionic profiles of patients with type 1 diabetes during consecutive hyper- and/or hypoglycaemic events using the glucose clamp. In protocol 1, two successive hyperglycaemic excursions to 18 mmol/l were induced; in protocol 2, a hypoglycaemic excursion (2.5 mmol/l) was followed by a hyperglycaemic excursion (12 mmol/l) and another hypoglycaemic episode (3.0 mmol/l). Blood osmolarity increased during hyperglycaemia and was unaffected by hypoglycaemia. Hyperglycaemia induced decreases in plasma Na+ Cl− and Ca2+ concentrations and increases in K+ concentrations. These changes were faithfully reproduced during a second hyperglycaemia. Hypoglycaemia provoked rapid and rapidly reversible increases in Na+, Cl− and Ca2+. In sharp contrast, K+ levels displayed a rapid and substantial fall from which they did not fully recover even 2 h after the re-establishment of euglycaemia. A second hypoglycaemia caused an additional fall. Repeated hyperglycaemia events do not lead to any cumulative effects on blood electrolytes. However, repeated hypoglycaemias are cumulative with respect to K+ levels due to a very slow recovery following hypoglycaemia. These results suggest that recurring hypoglycaemic events may lead to progressively lower K+ levels despite rapid re-establishment of euglycaemia. This warrants close monitoring of plasma K+ levels combined with continuous glucose monitoring particularly in patients under intensive insulin therapy who are subject to repeated hypoglycaemic episodes. Clinicaltrial.gov NCT01060917. Pendragon Medical AG, Solianis Monitoring AG

Recent studies of the minute morphology of the skin by optical coherence tomography revealed that the sweat ducts in human skin are helically shaped tubes, filled with a conductive aqueous solution. This, together with the fact that the dielectric permittivity of the dermis is higher than that of the epidermis, brings forward the supposition that as electromagnetic entities, the sweat ducts could be regarded as low Q helical antennas. The implications of this statement were further investigated by electromagnetic simulation and experiment of the in vivo reflectivity of the skin of subjects under varying physiological conditions (Feldman et al 2008 Phys. Rev. Lett. 100 128102). The simulation and experimental results are in a good agreement and both demonstrate that sweat ducts in the skin could indeed behave as low Q antennas. Thus, the skin spectral response in the sub-Terahertz region is governed by the level of activity of the perspiration system and shows the minimum of reflectivity at some frequencies in the frequency band of 75-110 GHz. It is also correlated to physiological stress as manifested by the pulse rate and the systolic blood pressure. As such, it has the potential to become the underlying principle for remote sensing of the physiological parameters and the mental state of the examined subject.

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.

Glucose measurement from different skin areas might be influenced by changes in skin texture due to several environmental confounders. Our study was performed to investigate the effect of changes in ambient temperature on skin thickness and microvascular skin blood flow in subjects with and without diabetes at the lower forearm.Thirteen subjects with diabetes and seven without diabetes participated in the study. The investigations were performed in a temperature- and humidity-controlled climatic chamber (EMPA, St. Gallen, Switzerland). Starting at 25 degrees C, the environmental temperature was changed in 4 degrees C steps every 40 min. Skin thickness was measured by an ultrasonic reflection technique, and microcirculation was measured by laser Doppler fluxmetry at the lower forearm. Study participants underwent the entire procedure on up to four separate study trials.Our study revealed a significantly reduced skin thickness (P0.05) and microvascular blood flow (P0.05) in patients with diabetes mellitus compared with controls without diabetes during the entire investigation. During declining ambient temperature a significant reduction in skin thickness (with diabetes, -0.09+/-0.13 mm; without diabetes, -0.06+/-0.11 mm; P0.05) and microvascular blood flow (with diabetes, -41+/-49 arbitrary units; without diabetes, -46+/-51 arbitrary units; P0.05) could be observed in both groups without significant differences between the two.Although skin thickness and microvascular skin blood flow at the lower forearm were found to be reduced in patients with diabetes compared with controls without diabetes, both groups revealed comparable dynamics in skin thickness and microvascular blood flow during changes in environmental temperature.