Non-invasive glucose monitoring: assessment of technologies and devices according to quantitative criteria

Noninvasive monitoring technologies to identify discomfort and distressing symptoms in persons with limited communication at the end of life: a scoping review

BACKGROUND

Discomfort and distressing symptoms are common at the end of life, while people in this stage are often no longer able to express themselves. Technologies may aid clinicians in detecting and treating these symptoms to improve end-of-life care. This review provides an overview of noninvasive monitoring technologies that may be applied to persons with limited communication at the end of life to identify discomfort.

METHODS

A systematic search was performed in nine databases, and experts were consulted. Manuscripts were included if they were written in English, Dutch, German, French, Japanese or Chinese, if the monitoring technology measured discomfort or distressing symptoms, was noninvasive, could be continuously administered for 4 hours and was potentially applicable for bed-ridden people. The screening was performed by two researchers independently. Information about the technology, its clinimetrics (validity, reliability, sensitivity, specificity, responsiveness), acceptability, and feasibility were extracted.

RESULTS

Of the 3,414 identified manuscripts, 229 met the eligibility criteria. A variety of monitoring technologies were identified, including actigraphy, brain activity monitoring, electrocardiography, electrodermal activity monitoring, surface electromyography, incontinence sensors, multimodal systems, and noncontact monitoring systems. The main indicators of discomfort monitored by these technologies were sleep, level of consciousness, risk of pressure ulcers, urinary incontinence, agitation, and pain. For the end-of-life phase, brain activity monitors could be helpful and acceptable to monitor the level of consciousness during palliative sedation. However, no manuscripts have reported on the clinimetrics, feasibility, and acceptability of the other technologies for the end-of-life phase.

CONCLUSIONS

Noninvasive monitoring technologies are available to measure common symptoms at the end of life. Future research should evaluate the quality of evidence provided by existing studies and investigate the feasibility, acceptability, and usefulness of these technologies in the end-of-life setting. Guidelines for studies on healthcare technologies should be better implemented and further developed.

Noninvasive Glucose Measurements Through Transcutaneous Raman Spectroscopy: A Review

BACKGROUND

People living with diabetes need constant glucose monitoring to avoid health complications. However, they do not monitor their glucose levels as often as recommended, probably because glucose measurement devices can be painful, costly, need testing strips or sensors, require lancing the finger or inserting a sensor with risk of infection, and can be inaccurate or have failures. Therefore, developing new alternatives for noninvasive glucose measurements that overcome these disadvantages is necessary, being Raman spectroscopy (RS) a solution.

OBJECTIVE

This review aims to provide an overview of the current glucose-monitoring technologies and the uses and advantages of RS to improve noninvasive transcutaneously glucose-monitoring devices.

RESULTS

The skin has been used to assess glucose levels noninvasively because it is an accessible tissue where glucose can be measured in the interstitial fluid (ISF) in the epidermis (especially in the stratum corneum). The most selected skin sites to apply RS for noninvasive glucose measurements were the nailfold, finger, and forearm because, in these sites, the penetration depth of the excitation light can reach the stratum corneum (10-20 µm) and the ISF. Studies found that RS is a good optical technique to measure glucose noninvasively by comparing glucose levels obtained by RS with those from invasive methods such as glucose meters with testing strips during an oral glucose tolerance test (OGTT).

CONCLUSIONS

New alternatives for noninvasive glucose measurements that overcome the disadvantages of current devices is necessary, and RS is a possible solution. However, more research is needed to evaluate the stability, accuracy, costs, and acceptance.

Noninvasive Glucose Sensing In Vivo

Blood glucose monitoring is an essential aspect of disease management for individuals with diabetes. Unfortunately, traditional methods require collecting a blood sample and thus are invasive and inconvenient. Recent developments in minimally invasive continuous glucose monitors have provided a more convenient alternative for people with diabetes to track their glucose levels 24/7. Despite this progress, many challenges remain to establish a noninvasive monitoring technique that works accurately and reliably in the wild. This review encompasses the current advancements in noninvasive glucose sensing technology in vivo, delves into the common challenges faced by these systems, and offers an insightful outlook on existing and future solutions.

Non-invasive electrochemical immunosensor for reverse iontophoretic determination of cardiac troponins (cTnT & cTnI) in a simulated artificial skin model. Significance of raw DPV and CV data for chemometric discrimination

Electrochemical immunosensors coupled with reverse iontophoresis (RI) for noninvasive determination of cardiac troponins were developed and validated according to ICH Q2 (R1) guideline. Linearity was in 0.01-10 and 100-500 ng/mL ranges. LODs (ng/mL) were in 6-25 × 10-4, while LOQs (μg/mL) were in 18-7.5 × 10-4 range. Chemometric evaluation was performed on raw data simply by principle component analysis and cluster analysis to discriminate stages of immunosensors. This is the first demonstration of RI determination of cardiac troponins so far. Findings of the current manuscript have great potential to develop point of care diagnostic systems for major cardiac events, where high sensitivity and specificity are required.

Non-Invasive Classification of Blood Glucose Level for Early Detection Diabetes Based on Photoplethysmography Signal

Monitoring systems for the early detection of diabetes are essential to avoid potential expensive medical costs. Currently, only invasive monitoring methods are commercially available. These methods have significant disadvantages as patients experience discomfort while obtaining blood samples. A non-invasive method of blood glucose level (BGL) monitoring that is painless and low-cost would address the limitations of invasive techniques. Photoplethysmography (PPG) collects a signal from a finger sensor using a photodiode, and a nearby infrared LED light. The combination of the PPG electronic circuit with artificial intelligence makes it possible to implement the classification of BGL. However, one major constraint of deep learning is the long training phase. We try to overcome this limitation and offer a concept for classifying type 2 diabetes (T2D) using a machine learning algorithm based on PPG. We gathered 400 raw datasets of BGL measured with PPG and divided these points into two classification levels, according to the National Institute for Clinical Excellence, namely, “normal” and “diabetes”. Based on the results for testing between the models, the ensemble bagged trees algorithm achieved the best results with an accuracy of 98%.

Simultaneous monitoring of sweat lactate content and sweat secretion rate by wearable remote biosensors

We report on the simultaneous monitoring of sweat lactate concentration and sweat secretion rate. For this aim lactate oxidase-Prussian Blue enzyme-nanozyme type lactate biosensors were elaborated. The use of siloxane-perfluorosulfonated ionomer composite membrane for enzyme-nanozyme immobilization results in the biosensor displaying flux independence in the whole range of physiological sweat secretion rates (0.025-2 μl cm^-2 min^-1). On the contrary, current response of the biosensor based on solely siloxane membranes becomes saturated at physiological sweat lactate concentration, depending mostly on the flow rate. Accordingly, for simultaneous monitoring of sweat lactate concentration and its secretion rate both flow-through biosensors were integrated with high-accuracy wearable electronic devices allowing real-time remote monitoring. As found, during exhaustive physical exercise sweat secretion rate and lactate content are independent of each other, thus, confirming that this excretory liquid is suitable for non-invasive diagnostics.

Recent advancement in noninvasive glucose monitoring and closed-loop management system for diabetes

Diabetes can cause many complications, which has become one of the most common diseases that may lead to death. Currently, the number of diabetics continues increasing year by year. Thus,...

Optimization of Extraction Parameters of Reverse Iontophoretic Determination of Blood Glucose in an Artificial Skin Model

Background:

Reverse İontophoresis (RI) is one of the promising non-invasive technologies. It relies on the transition of low magnitude current through the skin and thus glucose measurement becomes possible as it is extracted from the surface during this porter current flow.

Objective:

This paper deals with the development and optimization of an RI determination method for glucose. CE dialysis membrane based artificial skin model was developed and the dependence of RI extraction on various experimental parameters was investigated.

Method:

Dependence of RI extraction performance on noble electrodes (platinum, silver, palladium, ruthenium, rhodium) was checked with CA, CV and DPV, in a wide pH and ionic strength range. Optimizations on inter-electrode distance, potential type and magnitude, extraction time, gel type, membrane MWCO, usage frequency, pretreatment, artificial body fluids were performed.

Results:

According to the optimized results, the inter-electrode distance was 7.0 mm and silver was the optimum noble metal. Optimum pH and ionic strength were achieved with 0.05M PBS at pH 7.4. Higher glucose yields were obtained with DPV, while CA and CV achieved almost the same levels. During CA, +0.5V achieved the highest glucose yield and higher potential even caused a decrease. Glucose levels could be monitored for 24 hours. CMC gel was the optimum collection media. Pretreated CE membrane with 12kD MWCO was the artificial skin model. Pretreatment affected the yields while its condition caused no significant difference. Except PBS solution (simulated as artificial plasma), among the various artificial simulated body fluids, intestinal juice formulation (AI) and urine formulation U2 were the optimum extraction media, respectively.

Conclusion:

In this study, various experimental parameters (pretereatment procedure, type and MWCO values of membranes, inter-electrode distance, electrode material, extraction medium solvents, ionic strength and pH, collection medium gel type, extraction potential type and magnitude, extraction time and etc) were optimized for the non-invasive RI determination of glucose in a CE dialysis membrane-based artificial skin model and various simulated artificial body fluids.

Influence of Raman Spectrometer Collection Efficiency on Performance of Noninvasive Blood Glucose Detection for Device Miniaturization

Recently the world population with diabetes has increased significantly, and the market demand for noninvasive blood glucose monitoring has increased accordingly. Our previous study demonstrated the capability to detect glucose through the direct observation of glucose Raman fingerprint peaks from in vivo skin but using a benchtop device. From the perspective of commercialization, miniaturized devices are expected to make more impact on the market than bulky benchtop devices. In this study, as an effort for commercialization of noninvasive glucose sensing technology, we investigate the relationship between Raman spectrometer specification, especially collection efficiency, and glucose prediction performance. Raman spectra were synthesized at given spectrometer collection efficiencies in computer simulation, in which spectra are designed to contain glucose signal at specific concentrations. Then, we estimated glucose concentrations back using regression analysis and evaluated prediction performances. Finally, the relationship was analyzed between the collection efficiencies and glucose prediction performances. In order to mimic actual conditions with skin tissue, Monte-Carlo simulations were conducted to count the number of Raman photons escaping from the skin surface in a multi-layered skin model. As the collection efficiency decreased from 3.2 % to 0.2 %, the correlation coefficient between the actual and predicted glucose concentrations dropped from 0.91 to 0.35. The glucose Raman peaks at 1125 cm^-1 was identified as the most important wavelength for glucose sensing. This study may help identify optimal Raman spectrometer specifications for transcutaneous blood glucose sensing in miniaturized devices and commercialize noninvasive blood glucose sensors in Raman spectroscopy.

A Noninvasive Glucose Monitoring SoC Based on Single Wavelength Photoplethysmography

Conventional glucose monitoring methods for the growing numbers of diabetic patients around the world are invasive, painful, costly and, time-consuming. Complications aroused due to the abnormal blood sugar levels in diabetic patients have created the necessity for continuous noninvasive glucose monitoring. This article presents a wearable system for glucose monitoring based on a single wavelength near-infrared (NIR) Photoplethysmography (PPG) combined with machine-learning regression (MLR). The PPG readout circuit consists of a switched capacitor Transimpedance amplifier with 1 MΩ gain and a 10-Hz switched capacitor LPF. It allows a DC bias current rejection up to 20 μA with an input-referred current noise of 7.3 pA/√Hz. The proposed digital processor eliminates motion artifacts, and baseline drifts from PPG signal, extracts six distinct features and finally predicts the blood glucose level using Support Vector Regression with Fine Gaussian kernel (FGSVR) MLR. A novel piece-wise linear (PWL) approach for the exponential function is proposed to realize the FGSVR on-chip. The overall system is implemented using a 180 nm CMOS process with a chip area of 4.0 mm² while consuming 1.62 mW. The glucose measurements are performed for 200 subjects with R² of 0.937. The proposed system accurately predicts the sugar level with a mean absolute relative difference (mARD) of 7.62%.

Classification before regression for improving the accuracy of glucose quantification using absorption spectroscopy

This work contributes to the improvement of glucose quantification using near-infrared (NIR), mid-infrared (MIR), and combination of NIR and MIR absorbance spectroscopy by classifying the spectral data prior to the application of regression models. Both manual and automated classification are presented based on three homogeneous classes defined following the clinical definition of the glycaemic ranges (hypoglycaemia, euglycaemia, and hyperglycaemia). For the manual classification, partial least squares and principal component regressions are applied to each class separately and shown to lead to improved quantification results compared to when applying the same regression models for the whole dataset. For the automatic classification, linear discriminant analysis coupled with principal component analysis is deployed, and regressions are applied to each class separately. The results obtained are shown to outperform those of regressions for the entire dataset.

Novel Assessment of Urinary Albumin Excretion in Type 2 Diabetes Patients by Raman Spectroscopy

Urinary albumin excretion remains the key biomarker to detect renal complications in type 2 diabetes. As diabetes epidemy increases, particularly in low-income countries, efficient and low-cost methods to measure urinary albumin are needed. In this pilot study, we evaluated the performance of Raman spectroscopy in the assessment of urinary albumin in patients with type 2 diabetes. The spectral Raman analysis of albumin was performed using artificial urine, at five concentrations of albumin and 24 h collection urine samples from ten patients with Type 2 Diabetes. The spectra were obtained after removing the background fluorescence and fitting Gaussian curves to spectral regions containing features of such metabolites. In the samples from patients with type 2 diabetes, we identified the presence of albumin in the peaks of the spectrum located at 663.07, 993.43, 1021.43, 1235.28, 1429.91 and 1633.91 cm⁻¹. In artificial urine, there was an increase in the intensity of the Raman signal at 1450 cm⁻¹, which corresponds to the increment of the concentrations of albumin. The highest concentration of albumin was located at 1630 cm⁻¹. The capability of Raman spectroscopy for detection of small concentrations of urinary albumin suggests the feasibility of this method for the screening of type 2 diabetes renal complications.

Review of Non-invasive Glucose Sensing Techniques: Optical, Electrical and Breath Acetone

Annual deaths in the U.S. attributed to diabetes are expected to increase from 280,210 in 2015 to 385,840 in 2030. The increase in the number of people affected by diabetes has made it one of the major public health challenges around the world. Better management of diabetes has the potential to decrease yearly medical costs and deaths associated with the disease. Non-invasive methods are in high demand to take the place of the traditional finger prick method as they can facilitate continuous glucose monitoring. Research groups have been trying for decades to develop functional commercial non-invasive glucose measurement devices. The challenges associated with non-invasive glucose monitoring are the many factors that contribute to inaccurate readings. We identify and address the experimental and physiological challenges and provide recommendations to pave the way for a systematic pathway to a solution. We have reviewed and categorized non-invasive glucose measurement methods based on: (1) the intrinsic properties of glucose, (2) blood/tissue properties and (3) breath acetone analysis. This approach highlights potential critical commonalities among the challenges that act as barriers to future progress. The focus here is on the pertinent physiological aspects, remaining challenges, recent advancements and the sensors that have reached acceptable clinical accuracy.

Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal.

An IoT-Based Non-Invasive Glucose Level Monitoring System Using Raspberry Pi

Patients diagnosed with diabetes mellitus must monitor their blood glucose levels in order to control the glycaemia. Consequently, they must perform a capillary test at least three times per day and, besides that, a laboratory test once or twice per month. These standard methods pose difficulty for patients since they need to prick their finger in order to determine the glucose concentration, yielding discomfort and distress. In this paper, an Internet of Things (IoT)-based framework for non-invasive blood glucose monitoring is described. The system is based on Raspberry Pi Zero (RPi) energised with a power bank, using a visible laser beam and a Raspberry Pi Camera, all implemented in a glove. Data for the non-invasive monitoring is acquired by the RPi Zero taking a set of pictures of the user fingertip and computing their histograms. Generated data is processed by an artificial neural network (ANN) implemented on a Flask microservice using the Tensorflow libraries. In this paper, all measurements were performed in vivo and the obtained data was validated against laboratory blood tests by means of the mean absolute error (10.37%) and Clarke grid error (90.32% in zone A). Estimated glucose values can be harvested by an end device such as a smartphone for monitoring purposes.

Noninvasive Self-diagnostic Device for Tear Collection and Glucose Measurement

We propose a noninvasive, self-diagnostic device that enables safe tear collection and glucose measurement. The device described herein was manufactured by tight assembly of a lid for tear collection in conjunction with a strip-type glucose sensor. The lid was designed to be in contact with the inferior palpebral conjunctiva for tear collection and was thus designed to possess a proper contact area and rounded boundaries to avoid eye tissue damage. For the strip-type glucose sensor, we employed a commercially available electrochemical sensor (Accu-Chek test strips), which was modified to reduce the volume of the reaction chamber (0.4 μl) for a small amount of collected tear fluid. When tested with in vivo animal models, the device was able to collect tear fluid in a relatively short time (<2 s) without causing eye tissue damage, and the device allowed the collected tear fluid to be delivered to the sensor for measurement of tear glucose concentrations. The blood glucose concentrations estimated with the tear glucose concentrations obtained with the device exhibited a high correlation with those actually measured with a clinically available glucometer (R² = 0.9617).

The Progress of Glucose Monitoring-A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors

Current glucose monitoring methods for the ever-increasing number of diabetic people around the world are invasive, painful, time-consuming, and a constant burden for the household budget. The non-invasive glucose monitoring technology overcomes these limitations, for which this topic is significantly being researched and represents an exciting and highly sought after market for many companies. This review aims to offer an up-to-date report on the leading technologies for non-invasive (NI) and minimally-invasive (MI) glucose monitoring sensors, devices currently available in the market, regulatory framework for accuracy assessment, new approaches currently under study by representative groups and developers, and algorithm types for signal enhancement and value prediction. The review also discusses the future trend of glucose detection by analyzing the usage of the different bands in the electromagnetic spectrum. The review concludes that the adoption and use of new technologies for glucose detection is unavoidable and closer to become a reality.

Non-invasive blood glucose measurement of 95% certainty by pressure regulated Mid-IR

To fight against diabetes mellitus, from which more than 400 million people suffer in the world, the patients have to puncture their fingers 4-5 times a day for the blood glucose level checks when using a glucometer, causing invasive pain and the risk of infection. Therefore, non-invasive method has been urged for blood glucose monitoring, among which the mid-infrared spectroscopy (Mid-IR) response of interstitial fluid was found to be promising. However, despite the prolonged effort, the accuracy still falls below the FDA's requirement. To break this barrier which lasted for almost three decades, we discovered the finger contact pressure playing a critical role during the measurement, where the Mid-IR reading could be affected significantly by a small change of the finger posture. In addition, the Mid-IR absorption level was also found to be highly associated with individual, revealing the necessity of adjusting the calibration correlation for each patient. By imposing a certain contact pressure monitored by a pressure transducer, we were able to achieve over 95% certainty from the Mid-IR measurement of glucose concentration and 100% comparability to the "true" glucose concentration for the first time, which was mainly attributed to the morphological change of finger tissue under pressure. The previous works resulted in only about 70% accuracy on average, barely hitting 80 + %, whereas ours reaches 95%, finally exceeding the requirement of FDA.

Functionalized microneedles for continuous glucose monitoring

Microneedles (MNs) have been established as promising medical devices as they are minimally invasive, cause less pain, and can be utilized for self-administration of drugs by patients. There has been rapid development in MNs for transdermal monitoring and diagnostic systems, following the active research on fabrication methods and applications for drug delivery. In this paper, recent investigations on bio-sensing using MNs are reviewed in terms of the applicability to continuous glucose monitoring system (CGMS), which is one of the main research focuses of medical engineering technologies. The trend of the functionalized MNs can be categorized as follows: (i) as a sensing probe, and (ii) as a biological fluid collector. MNs as in vivo sensors are mainly integrated or coated with conductive materials to have the function as electrodes. MNs as fluid collectors are given a certain geometrical design, such as a hollow and porous structure aided by a capillary action or negative pressure, to extract the interstitial fluids or blood for ex vivo analysis. For realization of CGMS with MNs, a long-term accurate measurement by the MN-based sensing probe or a fluidic connection between the MN-based fluid collector and the existing microfluidic measurement systems should be investigated.

Noninvasive Optical Diagnostic Techniques for Mobile Blood Glucose and Bilirubin Monitoring

Background

People with diabetes need to monitor their blood sugar levels constantly and attend health centers regularly for checkups. The aim of this study is to provide a healthcare system for mobile blood glucose and bilirubin monitoring.

Methods

It includes a sensor for noninvasive blood glucose and bilirubin measurement using near-infrared spectroscopy and optical method, respectively, communicating with a smartphone.

Results

It was observed that by increasing the glucose concentration, the output voltage of the sensor increases in transmittance mode and decreases in reflectance mode. Moreover, it was observed that by increasing the bilirubin concentration, the output voltage of sensor decreases in transmittance mode and increases in reflectance mode. In the collected data there was good correlations between voltage and concentration and their relationship were approximately linear. Therefore, it is possible to use noninvasive methods to predict the glucose or bilirubin concentration. In vivo experiments for glucose were carried out with 19 persons in training phase, and five persons were used for testing the model. The glucose behavior model was built into the mobile application. The average glucose concentrations from the transmittance and reflectance mode were obtained. The average percentage error was 8.27 and root mean square error was 18.52 mg/dL.

Conclusions

From this research, it can be inferred that the noninvasive optical methods implemented on wireless sensors and smartphones could form a system that can be used at any time and any place in the future as an alternative to traditional invasive blood glucose and bilirubin measurement methods.

3-Stage Miller Cross-Coupled Load based Photodiode Readout for Glucose Monitoring

An innovative 3-stage miller compensted, cross-coupled load, based photodiode front end readout is designed for glucose monitoring. The Near Infrared Spectroscopy (NIRS) technique is used for the optical sensing of glucose non-invasively. The stable 3-stage open loop amplifier is designed for a gain of 68.3 dB, phase margin of 65°, GBW of 12.6 MHz and has a power consumption of 0.26 mW. The transimpedance amplifier achieves a gain of 84.46 dB, phase margin of 65°, has an input referred noise of 20.4 pAHz and consumes 0.55 mW of power from a 3.3 V supply using a 0.18 $\mu \mathrm{m}$ CMOS technology node.

Critical-depth Raman spectroscopy enables home-use non-invasive glucose monitoring

One of the most ambitious endeavors in the field of diabetes technology is non-invasive glucose sensing. In the past decades, a number of different technologies have been assessed, but none of these have found its entry into general clinical use. We report on the development of a table-top confocal Raman spectrometer that was used in the home of patients with diabetes and operated for extended periods of time unsupervised and without recalibration. The system is based on measurement of glucose levels at a ‘critical depth’ in the skin, specifically in the interstitial fluid located below the stratum corneum but above the underlying adipose tissue layer. The region chosen for routine glucose measurements was the base of the thumb (the thenar). In a small clinical study, 35 patients with diabetes analyzed their interstitial fluid glucose for a period of 60 days using the new critical-depth Raman (CD-Raman) method and levels were correlated to reference capillary blood glucose values using a standard finger-stick and test strip product. The calibration of the CD-Raman system was stable for > 10 days. Measurement performance for glucose levels present at, or below, a depth of ~250μm below the skin surface was comparable to that reported for currently available invasive continuous glucose monitors. In summary, using the CD-Raman technology we have demonstrated the first successful use of a non-invasive glucose monitor in the home.

Noninvasive, continuous, real-time glucose measurements compared to reference laboratory venous plasma glucose values

Purpose: Current modalities for glucose monitoring are invasive and inconvenient. The search for a noninvasive technique is still ongoing, without a clinically viable product. The aim of our study was to evaluate the safety and accuracy of a novel non-invasive continuous glucometer - the Wizmi™ device. Methods: Prospective, observational, controlled clinical trial. We included healthy pregnant women designated to undergo a 3-hour oral glucose tolerance test. Each participant underwent synchronous and simultaneous glucose measurement by venous sampling of plasma glucose and non-invasive glucose by Wizmi device. Primary outcome was the accuracy of the Wizmi device as assessed by comparing between paired measurements, i.e. non-invasive glucose measurements by Wizmi versus standard plasma glucose levels, which were taken at the exact same time. Results: Thirty-two women underwent oral glucose tolerance test (OGTT), contributing 224 paired glucose measurements. Of the 224 paired measurements, all were within the clinically appropriate zones of the Clarke error grid analysis zones -208 (93%) in Zone A and 16 (7%) in zone B. Mean absolute relative difference of the Wizmi non-invasive glucose versus plasma glucose laboratory reference was 7.23% or 9.66 mg/dl. Overall, for all 224 paired measurements, across all Wizmi glucose ranges, the agreement was 86.6, 92.0, 97.8 and 99.5% for deviations within ±15, 20, 30, 40% (if glucose >80 mg/dl) or mg/dl (if glucose ≤80 mg/dl). Conclusions: Wizmi device is novel non-invasive continuous glucose monitor, safe to use, with overall high accuracy compared to a gold standard reference of plasma glucose.

Design of non-invasive glucose meter using near-infrared technique

Diabetics need to keep track of their blood glucose level and measure it regularly to determine their insulin dose intake and to ensure that glucose level is always within the normal range. In this article, a system that enables the measurement of blood glucose level non-invasively is designed. This article uses a near infra-red (NIR) transmittance spectroscopy, without drawing blood, puncturing the skin, or causing pain. It involves a light source and light detector circuits positioned on a certain region of the body. The attenuated received infra-red signal by the detector is a measure of the blood glucose level of that region. Data are collected from the receiving circuit and sent to a microcontroller using CoolTerm application, then exporting it to Excel Sheet, in which mean values and graphs are obtained. The performance of the circuit with and without Filtering is examined. A downward pattern was noticed, as the glucose concentration in the solution increased, the voltage output decreased, meaning that a less intensity light was detected by the receiving circuit. An improvement in the accuracy of measurements by 17% was achieved, when a notch filter is implemented to cut the voltage components corresponding to the power line noisy signals.

Noninvasive Optical Diagnostic Techniques for Mobile Blood Glucose and Bilirubin Monitoring

Background:

People with diabetes need to monitor their blood sugar levels constantly and attend health centers regularly for checkups. The aim of this study is to provide a healthcare system for mobile blood glucose and bilirubin monitoring.

Methods:

It includes a sensor for noninvasive blood glucose and bilirubin measurement using near-infrared spectroscopy and optical method, respectively, communicating with a smartphone.

Results:

It was observed that by increasing the glucose concentration, the output voltage of the sensor increases in transmittance mode and decreases in reflectance mode. Moreover, it was observed that by increasing the bilirubin concentration, the output voltage of sensor decreases in transmittance mode and increases in reflectance mode. In the collected data there was good correlations between voltage and concentration and their relationship were approximately linear. Therefore, it is possible to use noninvasive methods to predict the glucose or bilirubin concentration. In vivo experiments for glucose were carried out with 19 persons in training phase, and five persons were used for testing the model. The glucose behavior model was built into the mobile application. The average glucose concentrations from the transmittance and reflectance mode were obtained. The average percentage error was 8.27 and root mean square error was 18.52 mg/dL.

Conclusions:

From this research, it can be inferred that the noninvasive optical methods implemented on wireless sensors and smartphones could form a system that can be used at any time and any place in the future as an alternative to traditional invasive blood glucose and bilirubin measurement methods.

Skin-like biosensor system via electrochemical channels for noninvasive blood glucose monitoring

Currently, noninvasive glucose monitoring is not widely appreciated because of its uncertain measurement accuracy, weak blood glucose correlation, and inability to detect hyperglycemia/hypoglycemia during sleep. We present a strategy to design and fabricate a skin-like biosensor system for noninvasive, in situ, and highly accurate intravascular blood glucose monitoring. The system integrates an ultrathin skin-like biosensor with paper battery-powered electrochemical twin channels (ETCs). The designed subcutaneous ETCs drive intravascular blood glucose out of the vessel and transport it to the skin surface. The ultrathin (~3 μm) nanostructured biosensor, with high sensitivity (130.4 μA/mM), fully absorbs and measures the glucose, owing to its extreme conformability. We conducted in vivo human clinical trials. The noninvasive measurement results for intravascular blood glucose showed a high correlation (>0.9) with clinically measured blood glucose levels. The system opens up new prospects for clinical-grade noninvasive continuous glucose monitoring.

A technology roadmap of smart biosensors from conventional glucose monitoring systems

The objective of this review article is to focus on technology roadmap of smart biosensors from a conventional glucose monitoring system. The estimation of glucose with commercially available devices involves analysis of blood samples that are obtained by pricking finger or extracting blood from the forearm. Since pain and discomfort are associated with invasive methods, the non-invasive measurement techniques have been investigated. The non-invasive methods show advantages like non-exposure to sharp objects such as needles and syringes, due to which there is an increase in testing frequency, improved control of glucose concentration and absence of pain and biohazard materials. This review study is aimed to describe recent invasive techniques and major noninvasive techniques, viz. biosensors, optical techniques and sensor-embedded contact lenses for glucose estimation.

Noninvasive and fast measurement of blood glucose in vivo by near infrared (NIR) spectroscopy

This research was to develop a method for noninvasive and fast blood glucose assay in vivo. Near-infrared (NIR) spectroscopy, a more promising technique compared to other methods, was investigated in rats with diabetes and normal rats. Calibration models are generated by two different multivariate strategies: partial least squares (PLS) as linear regression method and artificial neural networks (ANN) as non-linear regression method. The PLS model was optimized individually by considering spectral range, spectral pretreatment methods and number of model factors, while the ANN model was studied individually by selecting spectral pretreatment methods, parameters of network topology, number of hidden neurons, and times of epoch. The results of the validation showed the two models were robust, accurate and repeatable. Compared to the ANN model, the performance of the PLS model was much better, with lower root mean square error of validation (RMSEP) of 0.419 and higher correlation coefficients (R) of 96.22%.

A rat model for determining the postprandial response to foods

BACKGROUND

The use of small animal models for studying postprandial changes in circulating nutrients, hormones and metabolic biomarkers is hampered by the limited quantity of blood that can be withdrawn for analysis. Here, we describe the development of an unrestrained, meal-fed rat model, having a permanent or temporary vascular cannula that permits repeated blood sampling. The applicability and performance of the model were evaluated in a series of experiments on acute glycaemic and insulinaemic responses to carbohydrate-based test meals.

RESULTS

A test food containing 0.4 g carbohydrate raised blood glucose by 1.5 mmol L^-1 . Postprandial blood glucose levels peaked at 15 min and returned to baseline at 180 min, whereas they remained elevated for longer when the test meal contained 1.25 g carbohydrate. The glycaemic response tended (P = 0.063) to be higher when the meal tolerance test was conducted at the start rather than the end of the dark period, but the insulinaemic response was unaffected. The magnitude of the glycaemic response was less for blood collected from the caudal vein compared to that from the jugular vein. Both cannulation strategies were equally effective in enabling return of red blood cells, thus preserving blood volume.

CONCLUSION

This improved small animal model affords new opportunities to screen foods for nutrient bioavailability and explore metabolic mechanisms mediating responses to food consumption. © 2016 Society of Chemical Industry.

Aminosilane-Assisted Electrodeposition of Gold Nanodendrites and Their Catalytic Properties

A promising alternative route for the synthesis of three-dimensional Au dendrites was developed by direct electrodeposition from a solution of HAuCl4 containing 3-aminopropyltriethoxysilane (APTS). Ultraviolet-visible spectroscopy, fourier transform infrared spectroscopy and isothermal titration calorimetry were used to study the interaction of APTS in electrolyte. The effect of APTS on the formation of the hierarchical structure of Au dendrites was investigated by cyclic voltammetry, rotating disk electrode, electrochemical impedance spectroscopy and quartz crystal microbalance. The growth directions of the trunks and branches of the Au dendrites can be controlled by sweep-potential electrodeposition to obtain more regular structures. The efficacy of as-synthesised Au dendrites was demonstrated in the enhanced electro-catalytic activity to methanol electro-oxidation and the high sensitivity of glucose detection, which have potential applications in direct-methanol fuel cells and non-enzymatic electrochemical glucose biosensors, respectively.

Dual-modulation, dual-wavelength, optical polarimetry system for glucose monitoring

A dual modulation optical polarimetry system utilizing both laser intensity and polarization modulation was designed, built, and tested. The system was designed to reduce complexity and enhance the speed in order to facilitate the reduction of motion-induced time-varying birefringence, which is one of the major limitations to the realization of polarimetry for glucose monitoring in the eye. The high-speed less complex technique was tested using in vitro phantom studies with and without motion artifact introduced. The glucose concentration ranged from 0 to 600  mg/dl and the glucose measurements demonstrated a standard error of prediction to within 8.1  mg/dl without motion and to within 13.9  mg/dl with motion. Our feedback control systems took less than 10 ms to reach stabilization, which is adequately fast to eliminate the effect of time-varying birefringence. The results indicate that this new optical polarimetric approach has improved the speed and reduced the complexity, showing the potential for it to be used for noninvasive glucose measurements.

Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review

Diabetic individuals need to tightly control their blood glucose concentration. Several methods have been developed for this purpose, such as the finger-prick or continuous glucose monitoring systems (CGMs). However, these methods present the disadvantage of being invasive. Moreover, CGMs have limited accuracy, notably to detect hypoglycemia. It is also known that physical exercise, and even daily activity, disrupt glucose dynamics and can generate problems with blood glucose regulation during and after exercise. In order to deal with these challenges, devices for monitoring patients’ physical activity are currently under development. This review focuses on non-invasive sensors using physiological parameters related to physical exercise that were used to improve glucose monitoring in type 1 diabetes (T1DM) patients. These devices are promising for diabetes management. Indeed they permit to estimate glucose concentration either based solely on physical activity parameters or in conjunction with CGM or non-invasive CGM (NI-CGM) systems. In these last cases, the vital signals are used to modulate glucose estimations provided by the CGM and NI-CGM devices. Finally, this review indicates possible limitations of these new biosensors and outlines directions for future technologic developments.

Hydrogel-forming microneedle arrays: Potential for use in minimally-invasive lithium monitoring

We describe, for the first time, hydrogel-forming microneedle (s) (MN) arrays for minimally-invasive extraction and quantification of lithium in vitro and in vivo. MN arrays, prepared from aqueous blends of hydrolysed poly(methyl-vinylether-co-maleic anhydride) and crosslinked by poly(ethyleneglycol), imbibed interstitial fluid (ISF) upon skin insertion. Such MN were always removed intact. In vitro, mean detected lithium concentrations showed no significant difference following 30min MN application to excised neonatal porcine skin for lithium citrate concentrations of 0.9 and 2mmol/l. However, after 1h application, the mean lithium concentrations extracted were significantly different, being appropriately concentration-dependent. In vivo, rats were orally dosed with lithium citrate equivalent to 15mg/kg and 30mg/kg lithium carbonate, respectively. MN arrays were applied 1h after dosing and removed 1h later. The two groups, having received different doses, showed no significant difference between lithium concentrations in serum or MN. However, the higher dosed rats demonstrated a lithium concentration extracted from MN arrays equivalent to a mean increase of 22.5% compared to rats which received the lower dose. Hydrogel-forming MN clearly have potential as a minimally-invasive tool for lithium monitoring in outpatient settings. We will now focus on correlation between serum and MN lithium concentrations.

Mouthguard biosensor with telemetry system for monitoring of saliva glucose: A novel cavitas sensor

We develop detachable "Cavitas sensors" to apply to the human oral cavity for non-invasive monitoring of saliva glucose. A salivary biosensor incorporating Pt and Ag/AgCl electrodes on a mouthguard support with an enzyme membrane is developed and tested. Electrodes are formed on the polyethylene terephthalate glycol (PETG) surface of the mouthguard. The Pt working electrode is coated with a glucose oxidase (GOD) membrane. The biosensor seamlessly is integrated with a glucose sensor and a wireless measurement system. When investigating in-vitro performance, the biosensor exhibits a robust relationship between output current and glucose concentration. In artificial saliva composed of salts and proteins, the glucose sensor is capable of highly sensitive detection over a range of 5-1000µmol/L of glucose, which encompasses the range of glucose concentrations found in human saliva. We demonstrate the ability of the sensor and wireless communication module to monitor saliva glucose in a phantom jaw imitating the structure of the human oral cavity. Stable and long-term real-time monitoring (exceeding 5h) with the telemetry system is achieved. The mouthguard biosensor will be useful as a novel method for real-time non-invasive saliva glucose monitoring for better management of dental patients.

Phase Difference Optimization of Dual-Wavelength Excitation for the CW-Photoacoustic-Based Noninvasive and Selective Investigation of Aqueous Solutions of Glucose

Towards the noninvasive and continuous monitoring of blood glucose levels, we chose the continuous-wave photoacoustic (CW-PA) technique and developed the optical power balance shift (OPBS) method. However, operating with optical wavelengths in the near-infrared (NIR) region ensures deep penetration inside human soft-tissue, but also leads to two serious issues: strong background level noise from water molecules in this wavelength range and small differences between the absorbance spectra of diluted compounds. To resolve them, the OPBS method relies on simultaneous optical excitation at two wavelengths for differential measurements. However, the first validation in vitro with calibrated aqueous solutions of glucose and albumin revealed strong dependence on the phase difference between the two lights sources. In this paper, we report a systematic investigation of this parameter, from PA-based measurements over a wide range of phase differences and an extensive characterization in the frequency domain. The process of maintaining the phase quadrature of the two optical signals is demonstrated in real time through an analysis of the PA signal and therefore does not require any additional equipment. Finally, a comparison of aqueous glucose solution characterizations at high concentration levels with the two methods was performed and consistent results were obtained.

Modelling, verification, and calibration of a photoacoustics based continuous non-invasive blood glucose monitoring system

This paper examines the use of photoacoustic spectroscopy (PAS) at an excitation wavelength of 905 nm for making continuous non-invasive blood glucose measurements. The theoretical background of the measurement technique is verified through simulation. An apparatus is fabricated for performing photoacoustic measurements in vitro on glucose solutions and in vivo on human subjects. The amplitude of the photoacoustic signals measured from glucose solutions is observed to increase with the solution concentration, while photoacoustic amplitude obtained from in vivo measurements follows the blood glucose concentration of the subjects, indicating a direct proportionality between the two quantities. A linear calibration method is applied separately on measurements obtained from each individual in order to estimate the blood glucose concentration. The estimated glucose values are compared to reference glucose concentrations measured using a standard glucose meter. A plot of 196 measurement pairs taken over 30 normal subjects on a Clarke error grid gives a point distribution of 82.65% and 17.35% over zones A and B of the grid with a mean absolute relative deviation (MARD) of 11.78% and a mean absolute difference (MAD) of 15.27 mg/dl (0.85 mmol/l). The results obtained are better than or comparable to those obtained using photoacoustic spectroscopy based methods or other non-invasive measurement techniques available. The accuracy levels obtained are also comparable to commercially available continuous glucose monitoring systems.

Hypo- and Hyperglycemic Alarms: Devices and Algorithms

Soon after the discovery that insulin regulates blood glucose by Banting and Best in 1922, the symptoms and risks associated with hypoglycemia became widely recognized. This article reviews devices to warn individuals of impending hypo- and hyperglycemia; biosignals used by these devices include electroencephalography, electrocardiography, skin galvanic resistance, diabetes alert dogs, and continuous glucose monitors (CGMs). While systems based on other technology are increasing in performance and decreasing in size, CGM technology remains the best method for both reactive and predictive alarming of hypo- or hyperglycemia.