Non-invasive glucose measurement technologies: an update from 1999 to the dawn of the new millennium

Non-invasive glucose prediction and classification using NIR technology with machine learning

In this paper, a dual wavelength short near-infrared system is described for the detection of glucose levels. The system aims to improve the accuracy of blood glucose detection in a cost-effective and non-invasive way. The accuracy of the method is evaluated using real-time samples collected with the reference finger prick glucose device. A feed forward neural network (FFNN) regression method is employed to predict glucose levels based on the input data obtained from NIR technology. The system calculates glucose evaluation metrics and performs Surveillance error grid (SEG) analysis. The coefficient of determination R 2 and mean absolute error are observed 0.99 and 2.49 mg/dl, respectively. Additionally, the system determines the root mean square error (RMSE) as 3.02 mg/dl. It also shows that the mean absolute percentage error (MAPE) is 1.94% and mean squared error (MSE) is 9.16 ( m g / d l ) 2 for FFNN. The SEG analysis shows that the glucose values measured by the system fall within the clinically acceptable range when compared to the reference method. Finally, the system uses the multi-class classification method of the multilayer perceptron (MLP) and K-nearest neighbors (KNN) classifier to classify glucose levels with an accuracy of 99%.

Progress and Perspectives of Mid-Infrared Photoacoustic Spectroscopy for Non-Invasive Glucose Detection

The prevalence of diabetes is rapidly increasing worldwide and can lead to a range of severe health complications that have the potential to be life-threatening. Patients need to monitor and control blood glucose levels as it has no cure. The development of non-invasive techniques for the measurement of blood glucose based on photoacoustic spectroscopy (PAS) has advanced tremendously in the last couple of years. Among them, PAS in the mid-infrared (MIR) region shows great promise as it shows the distinct fingerprint region for glucose. However, two problems are generally encountered when it is applied to monitor real samples for in vivo measurements in this MIR spectral range: (i) low penetration depth of MIR light into the human skin, and (ii) the effect of other interfering components in blood, which affects the selectivity of the detection system. This review paper systematically describes the basics of PAS in the MIR region, along with recent developments, technical challenges, and data analysis strategies, and proposes improvements for the detection sensitivity of glucose concentration in human bodies. It also highlights the recent trends of incorporating machine learning (ML) to enhance the detection sensitivity of the overall system. With further optimization of the experimental setup and incorporation of ML, this PAS in the MIR spectral region could be a viable solution for the non-invasive measurement of blood glucose in the near future.

Is Raman the best strategy towards the development of non-invasive continuous glucose monitoring devices for diabetes management?

Diabetes has no well-established cure; thus, its management is critical for avoiding severe health complications involving multiple organs. This requires frequent glycaemia monitoring, and the gold standards for this are fingerstick tests. During the last decades, several blood-withdrawal-free platforms have been being studied to replace this test and to improve significantly the quality of life of people with diabetes (PWD). Devices estimating glycaemia level targeting blood or biofluids such as tears, saliva, breath and sweat, are gaining attention; however, most are not reliable, user-friendly and/or cheap. Given the complexity of the topic and the rise of diabetes, a careful analysis is essential to track scientific and industrial progresses in developing diabetes management systems. Here, we summarize the emerging blood glucose level (BGL) measurement methods and report some examples of devices which have been under development in the last decades, discussing the reasons for them not reaching the market or not being really non-invasive and continuous. After discussing more in depth the history of Raman spectroscopy-based researches and devices for BGL measurements, we will examine if this technique could have the potential for the development of a user-friendly, miniaturized, non-invasive and continuous blood glucose-monitoring device, which can operate reliably, without inter-patient variability, over sustained periods.

Spectral Methods for Response Enhancement of Microwave Resonant Sensors in Continuous Non-Invasive Blood Glucose Monitoring

In this paper, the performance of three recent algorithms for the frequency-response enhancement of microwave resonant sensors are compared. The first one, a single-step algorithm, is based on a couple of direct-inverse Fourier transforms, giving a densely sampled response as a result. The second algorithm exploits an iterative procedure to progressively restricts the frequency response. The final one is based on the super-resolution MUSIC algorithm. The comparison is carried out through a Monte Carlo analysis. In particular, synthetic signals are firstly exploited to mimic the frequency response of a resonant microwave sensor. Then, experimental data collected from water-glucose solutions are adopted as validation test for potential applications in noninvasive blood-glucose monitoring.

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%.

Optimization of the Transverse Electric Photonic Strip Waveguide Biosensor for Detecting Diabetes Mellitus from Bulk Sensitivity

Diabetes mellitus is a chronic metabolic condition that affects millions of people worldwide. The present paper investigates the bulk sensitivity of silicon and silicon nitride strip waveguides in the transverse electric (TE) mode. At 1550 nm wavelength, silicon on insulator (SOI) and silicon nitride (Si₃N₄) are two distinct waveguides of the same geometry structure that can react to refractive changes around the waveguide surface. This article examines the response of two silicon-based waveguide structures to the refractive index of urine samples (human renal fluids) to diagnose diabetes mellitus. An asymmetric Mach–Zehnder interferometer has waveguide sensing and a reference arm with a device that operates in the transverse electric (TE) mode. 3D FDTD simulated waveguide width 800 nm, thickness 220 nm, and analyte thickness 130 nm give the bulk sensitivity of 1.09 (RIU/RIU) and 1.04 (RIU/RIU) for silicon and silicon nitride, respectively, high compared to the regular transverse magnetic (TM) mode strip waveguides. Furthermore, the proposed design gives simple fabrication, contrasting sharply with the state-of-the-art 220 nm wafer technology.

Noncontact Optical Measurement of Aqueous Humor Glucose Levels and Correlation with Serum Glucose Levels in Rabbit

The noninvasive measurement of serum glucose levels has been investigated for the monitoring of blood sugar control in diabetes. In our study, we aimed to develop a novel noncontact glucometer (NCGM) utilizing an optical approach to measure the intraocular aqueous humor glucose levels in the anterior chamber of rabbit eyes. The NCGM consists of a hybrid optical system that simultaneously measures near-infrared absorption and the polarized rotatory distribution of glucose molecules in the aqueous humor. In vitro optical measurements demonstrated that NCGM measurements had high precision and repeatability for different glucose levels, including 50 mg/dL (14.36%), 100 mg/dL (−4.05%), 200 mg/dL (−5.99%), 300 mg/dL (4.86%), 400 mg/dL (−2.84%), 500 mg/dL (−0.11%), and 600 mg/dL (4.48%). In the rabbit experiments, we found a high correlation between aqueous glucose levels and serum glucose levels, with a mean difference of 8 mg/dL. According to the testing results, the in vivo NCGM measurement of aqueous humor glucose levels also displayed a high correlation with serum glucose levels, with a mean difference of 29.2 mg/dL. In conclusion, aqueous humor glucose levels were accurately measured using the NCGM, and the results correlated with serum glucose levels.

Backpropagation Neural Network-Based Machine Learning Model for Prediction of Blood Urea and Glucose in CKD Patients

Diabetes mellitus and its complication such as heart disease, stroke, kidney failure, etc. is a serious concern all over the world. Hence, monitoring some important blood parameters non-invasively is of utmost importance, that too with high accuracy. This paper presents an in-house developed system, which will be helpful for diabetes patients with Chronic Kidney Disease (CKD) to monitor blood urea and glucose. This manuscript discusses a comparative study for the prediction of blood urea and glucose using Backpropagation Artificial Neural Network (BP- ANN) and Partial Least Square Regression (PLSR) model. The NVIDIA Jetson Nano board controls the five fixed LED wavelengths in the Near Infrared (NIR) region from [Formula: see text] to [Formula: see text] with a constant emission power of 1.2 mW. The spectra for 57 laboratory prepared samples conforming with major blood constituents of the blood sample were recorded. From these samples, 53 spectra were used for training/calibration of the BP-ANN/PLSR model and the remaining 4 samples were used for validating the model. The PLSR model predicts blood urea and glucose with a Root Mean Square Error (RMSE) of 0.88 & 12.01 mg/dL, Coefficient of Determination R2 = 0.93 & R2 = 0.97, Accuracy of 94.2 % and 90.14 %, respectively. To improve the prediction accuracy, BP-ANN model is applied. Later the Principal Component Analysis (PCA) technique was applied to these 57 spectra values. These PCA values were used to train and validate the BP-ANN model. After applying the BP-ANN model, the prediction of blood urea & glucose improved remarkably, which achieved RMSE of 0.69 mg/dL, R2 = 0.96, Accuracy of 95.96 % for urea and RMSE of 2.06 mg/dL, R2 = 0.99, and Accuracy of 98.65 % for glucose. The system performance is then evaluated with Bland Altman analysis and Clarke Error Grid Analysis (CEGA).

Non-Invasive Determination of Glucose Concentration Using a Near-Field Sensor

The article presents a model of a near-field sensor for non-invasive glucose monitoring. The sensor has a specific design and forms a rather extended near-field. Due to this, the high penetration of electromagnetic waves into highly absorbing media (biologic media) is achieved. It represents a combined slot antenna based on a flexible RO3003 substrate. Moreover, it is small and rather flat (25 mm in diameter, 0.76 mm thick). These circumstances are the distinguishing features of this sensor in comparison with microwave sensors of other designs. The article presents the results of numerical modeling and experimental verification of a near-field sensor. Furthermore, a phantom of human biological media (human hand) was created for experimentation. In the case of numerical modeling, the sensor is located close to the hand model. In a full-scale experiment, it is located close to the phantom of the human hand for the maximum interaction of the near-field with biological materials. As a result of a series of measurements for this sensor, the reflection coefficient is measured, and the dependences of the reflected signal on the frequency are plotted. According to the results of the experiments carried out, there is a clear difference in glucose concentrations. At the same time, the accuracy of determining the difference in glucose concentrations is high. The values of the amplitude of the reflected signal with a change in concentration differ by 0.5-0.8 dB. This sensor can be used for developing a non-invasive blood glucose measurement procedure.

Association between tear and blood glucose concentrations: Random intercept model adjusted with confounders in tear samples negative for occult blood

AIMS/INTRODUCTION

To prevent diabetic complications, strict glucose control and frequent monitoring of blood glucose levels with invasive methods are necessary. We considered the monitoring of tear glucose levels might be a possible method for non-invasive glucose monitoring. To develop tear glucose monitoring for clinical application, we investigated the precise correlation between the blood and tear glucose concentrations.

MATERIALS AND METHODS

A total of 10 participants and 20 participants with diabetes were admitted, and blood and tear samples were collected. Before statistical analysis, we eliminated tear samples contaminated with blood. We observed the daily blood and tear glucose dynamics, and carried out a random intercept model analysis to examine the association between the blood and tear glucose concentrations.

RESULTS

Tear occult blood tests showed that the tear glucose concentrations and their variation increased in both participants with and without diabetes as contamination of blood increased. In both participants with and without diabetes, fluctuations of the plasma glucose concentrations were observed depending on the timing of collection of the samples, and the dynamics of the tear glucose concentrations paralleled those of the plasma glucose concentrations. The random intercept model analysis showed a significant association between the plasma and tear glucose concentrations in participants with diabetes (P < 0.001). This association still existed even after adjusting for the glycated hemoglobin levels and the prandial state (P < 0.001).

CONCLUSIONS

It is important to eliminate the tear samples contaminated with blood. Tear glucose monitoring might be a reliable and non-invasive substitute method for monitoring the blood glucose concentrations for diabetes patients, irrespective of glycated hemoglobin levels and timing of sample collection.

The past, present, and prospective on UV-VIS-NIR skin photonics and spectroscopy-a wavelength guide

The study and applications of in vivo skin optics have been openly documented as early as the year 1954, or possibly earlier. To date, challenges in analyzing the complexities of this field remain, with wide scopes requiring more scrutiny. Recent advances in spectroscopic research and multivariate analytics allow a closer look into applications potentially for detecting or monitoring diseases. One of the challenges in this field is in establishing a reference for applications which correspond to certain bandwidths. This article reviews the scope on past research on skin spectroscopy, and the clinical aspects which have or may have applications on disease detection or enhancing diagnostics. A summary is supplied on the technicalities surrounding the measurements reported in literature, focused towards the wavelength-dependent applications in themes central to the respective research. Analytics on the topology of the papers' data cited in this work is also provided for a statistical perspective. In short, this paper strives to immediately inform the reader with possible applications via the spectroscopic devices at hand. Graphical Abstract .

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.

Direct observation of glucose fingerprint using in vivo Raman spectroscopy

Noninvasive blood glucose monitoring has been a long-standing dream in diabetes management. The use of Raman spectroscopy, with its molecular specificity, has been investigated in this regard over the past decade. Previous studies reported on glucose sensing based on indirect evidence such as statistical correlation to the reference glucose concentration. However, these claims fail to demonstrate glucose Raman peaks, which has raised questions regarding the effectiveness of Raman spectroscopy for glucose sensing. Here, we demonstrate the first direct observation of glucose Raman peaks from in vivo skin. The signal intensities varied proportional to the reference glucose concentrations in three live swine glucose clamping experiments. Tracking spectral intensity based on linearity enabled accurate prospective prediction in within-subject and intersubject models. Our direct demonstration of glucose signal may quiet the long debate about whether glucose Raman spectra can be measured in vivo in transcutaneous glucose sensing.

Effect of electrode geometry on the electrolyte resistance measurement over the surface of a skin phantom in a noninvasive manner

We analyzed the electrode geometry to obtain the potential (E) and current density (J) distributions at the surface of a skin phantom (SP), in this case a planar surface. Two electrode geometries were tested: a circular electrode (CiE) and a rectangular electrode (ReE). First, by a finite element simulation, we calculated the E and J distributions at the surface of the SP. Second, we determined the resistivity properties as a function of the electrochemical impedance. Three- and four-electrode configurations were used to measure the E versus distance between the reference electrodes (d). For the ReE, the electrolyte resistance (R_e) measurements show a linear behavior with respect to "d" if the zone of the linear distribution of E and the homogeneous current density (J_H) is considered. In contrast, the CiE shows nonlinear behavior due to the absence of that zone of the linear distribution of E and J_H in the entire range. For ReE, we deduced that the behavior of R_e versus "d" is related to the material resistivity. Consequently, the ReE geometry improves the R_e measurements on the surface and shows us a way to control the behavior of this element in planar samples such as skin.

Noninvasive Electromagnetic Wave Sensing of Glucose

Diabetic patients need long-term and frequent glucose monitoring to assist in insulin intake. The current finger-prick devices are painful and costly, which places noninvasive glucose sensors in high demand. In this review paper, we list several advanced electromagnetic (EM)-wave-based technologies for noninvasive glucose measurement, including infrared (IR) spectroscopy, photoacoustic (PA) spectroscopy, Raman spectroscopy, fluorescence, optical coherence tomography (OCT), Terahertz (THz) spectroscopy, and microwave sensing. The development of each method is discussed regarding the fundamental principle, system setup, and experimental results. Despite the promising achievements that have been previously reported, no established product has obtained FDA approval or survived a marketing test. The limitations of, and prospects for, these techniques are presented at the end of this review.

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.

Scattering-independent glucose absorption measurement using a spectrally resolved reflectance setup with specialized variable source-detector separations

We report a novel approach for the accurate measurement of glucose absorption in turbid media using a spectrally resolved reflectance setup. Our proposed reflectance setup with specialized variable source-detector separations enables scattering-independent absorption measurement, which is critical to in vivo long-term glucose concentration monitoring. Starting from the first-order approximation of the radiative transfer equation (RTE), we developed a scattering-independent glucose absorption measurement method and then evaluated this approach by Monte Carlo simulations as well as tissue-mimicking phantom studies in which glucose concentration was accurately measured. Our study demonstrates the potential of our proposed scattering-independent absorption measurement technique as an effective tool to quantify glucose levels in turbid media, which is an important step towards future in vivo long-term glucose concentration monitoring in human subjects.

Evaluation of accuracy dependence of Raman spectroscopic models on the ratio of calibration and validation points for non-invasive glucose sensing

Optical monitoring of blood glucose levels for non-invasive diagnosis is a growing area of research. Recent efforts in this direction have been inclined towards reducing the requirement of calibration framework. Here, we are presenting a systematic investigation on the influence of variation in the ratio of calibration and validation points on the prospective predictive accuracy of spectral models. A fiber-optic probe coupled Raman system has been employed for transcutaneous measurements. Limit of agreement analysis between serum and partial least square regression predicted spectroscopic glucose values has been performed for accurate comparison. Findings are suggestive of strong predictive accuracy of spectroscopic models without requiring substantive calibration measurements. Graphical abstract.

Near-Infrared Diffuse Reflectance Measurement Method Based on Temperature-Insensitive Radial Distance

The variation of temperature is one of the main interference factors that affect the detection accuracy of near-infrared (NIR) diffuse reflectance. In this paper, a measurement method based on temperature-insensitive radial distance was proposed, and its feasibility and effectiveness were verified in Intralipid solutions. First, the possibility of temperature-insensitive radial distance was deduced based on the analytic solution of the steady-state diffusion equation in an infinite media, and the temperature-insensitive radial distances of 3% Intralipid solution in the wavelength range of 1000-1600 nm was calculated. Second, a detection system was designed to measure the diffuse reflectance of 3% Intralipid solutions at multiple radial distances with different glucose concentration (0-100 mM) and different temperatures (35-40 ℃). Both theoretical calculations and experimental results demonstrated the existence of temperature-insensitive radial distances in the range of 1000-1340 nm and 1440-1600 nm, and the distances were hardly affected by glucose variations. Finally, the glucose information extracted from the diffuse reflectance of Intralipid solutions at different radial distances under random temperature variations and constant temperature were compared. The result showed that the correlation between the glucose concentration and the diffuse reflectance obtained at the temperature-insensitive radial distance was significantly better than that of other radial distances, which was almost close to the situation of constant temperature. Therefore, the measurement method based on temperature-insensitive radial distance can effectively reduce the influence of temperature variations on NIR diffuse reflectance, and it is expected to improve the accuracy of diffuse reflectance in human body components detection and industrial field analysis.

Noninvasive measurement of glucose concentration on human fingertip by optical coherence tomography

A method is proposed for determining the glucose concentration on the human fingertip by extracting two optical parameters, namely the optical rotation angle and the depolarization index, using a Mueller optical coherence tomography technique and a genetic algorithm. The feasibility of the proposed method is demonstrated by measuring the optical rotation angle and depolarization index of aqueous glucose solutions with low and high scattering, respectively. It is shown that for both solutions, the optical rotation angle and depolarization index vary approximately linearly with the glucose concentration. As a result, the ability of the proposed method to obtain the glucose concentration by means of just two optical parameters is confirmed. The practical applicability of the proposed technique is demonstrated by measuring the optical rotation angle and depolarization index on the human fingertip of healthy volunteers under various glucose conditions.

Differential Mueller matrix polarimetry technique for non-invasive measurement of glucose concentration on human fingertip

A differential Mueller matrix polarimetry technique is proposed for obtaining non-invasive (NI) measurements of the glucose concentration on the human fingertip. The feasibility of the proposed method is demonstrated by detecting the optical rotation angle and depolarization index of tissue phantom samples containing de-ionized water (DI), glucose solutions with concentrations ranging from 0~500 mg/dL and 2% lipofundin. The results show that the extracted optical rotation angle increases linearly with an increasing glucose concentration, while the depolarization index decreases. The practical applicability of the proposed method is demonstrated by measuring the optical rotation angle and depolarization index properties of the human fingertips of healthy volunteers.

Noninvasive Monitoring of Blood Glucose with Raman Spectroscopy

The successful development of a noninvasive blood glucose sensor that can operate reliably over sustained periods of time has been a much sought after but elusive goal in diabetes management. Since diabetes has no well-established cure, control of elevated glucose levels is critical for avoiding severe secondary health complications in multiple organs including the retina, kidney and vasculature. While fingerstick testing continues to be the mainstay of blood glucose detection, advances in electrochemical sensing-based minimally invasive approaches have opened the door for alternate methods that would considerably improve the quality of life for people with diabetes. In the quest for better sensing approaches, optical technologies have surfaced as attractive candidates as researchers have sought to exploit the endogenous contrast of glucose, notably its absorption, scattering, and polarization properties. Vibrational spectroscopy, especially spontaneous Raman scattering, has exhibited substantial promise due to its exquisite molecular specificity and minimal interference of water in the spectral profiles acquired from the blood-tissue matrix. Yet, it has hitherto been challenging to leverage the Raman scattering signatures of glucose for prediction in all but the most basic studies and under the least demanding conditions. In this Account, we discuss the newly developed array of methodologies that address the key challenges in measuring blood glucose accurately using Raman spectroscopy and unlock new prospects for translation to sustained noninvasive measurements in people with diabetes. Owing to the weak intensity of spontaneous Raman scattering, recent research has focused on enhancement of signals from the blood constituents by designing novel excitation-collection geometries and tissue modulation methods while our attempts have led to the incorporation of nonimaging optical elements. Additionally, invoking mass transfer modeling into chemometric algorithms has not only addressed the physiological lag between the actual blood glucose and the measured interstitial fluid glucose values but also offered a powerful tool for predictive measurements of hypoglycemia. This framework has recently been extended to provide longitudinal tracking of glucose concentration without necessitating extensive a priori concentration information. These findings are advanced by the results of recent glucose tolerance studies in human subjects, which also hint at the need for designing nonlinear calibration models that can account for subject-to-subject variations in skin heterogeneity and hematocrit levels. Together, the emerging evidence underscores the promise of a blood withdrawal-free optical platform-featuring a combination of high-throughput Raman spectroscopic instrumentation and data analysis of subtle variations in spectral expression-for diabetes screening in the clinic and, ultimately, for personalized monitoring.

Self-referenced, microdegree, optical rotation polarimeter for biomedical applications: an analysis

We comprehensively analyze the performance of a type of optical rotation (OR) polarimeter, which has been designed from the outset to fit the special requirements of two major applications: general chiral detection during the separation of optical isomers by high-pressure liquid chromatography systems in the pharmaceutical industry, and monitoring of glucose in the interstitial fluid of diabetics by a fully implanted long-term optical sensor. Both very demanding applications call for an OR polarimeter that can be miniaturized while maintaining high resolution and accuracy in the microdegree range in the face of considerable noise from various sources. These two characteristics—miniature size and immunity to noise—set this polarimeter apart from the traditional OR polarimeters currently in use, which are both bulky and very susceptible to noise. The following detailed analysis demonstrates the advantages of this polarimeter and its potential as an analytic and diagnostic tool.

Behavior of long-period measurements using a small-sized photoacoustic cell for aqueous glucose monitoring

Reliable, noninvasive glucose-monitoring devices are not currently available. From the patient's point of view, it is necessary that glucose-monitoring devices are portable as well as noninvasive. In photoacoustic spectroscopy (PAS), the PA signal induced by the irradiation of the sample with modulated light depends on the optical absorption coefficient of the sample. Unlike the sensitivity of conventional absorption spectroscopy, the sensitivity of PAS scales inversely with the dimensions. An external laser (wavelength of 1550 nm) and a PA cell with a volume of only 4.0 mm(3) were used for monitoring a glucose solution contained in a special sample reservoir. We present PA measurements of glucose in aqueous solutions using a sample reservoir that is suitable for investigations of liquid samples, such as native capillary blood, by performing a long-period measurement.

Accuracy of Noninvasive Glucose Sensing Based on Near-Infrared Spectroscopy

The noninvasive sensing of the blood glucose concentration is usually based on optical, electrical, or acoustical signals induced by blood glucose; these signals are extremely weak and subject to fluctuations caused by the variation in the body or surroundings. Therefore, it is challenging to detect blood glucose noninvasively with high accuracy, and no successful accurate and noninvasive clinical application has been reported. We found that there are two key measurement issues to be addressed: systematic errors, such as the errors induced by the drifts of devices or by variations in body temperature, among others, are too large to guarantee the trueness of measurement at present; and random disturbances in repeated tests, such as disturbances associated with variations in the human-machine interface, pulses, and the thermal noise of the devices, cause larger repeated measurement errors and compromise precision. Recent novel reference measurements based on differential near-infrared (NIR) spectroscopy are considered promising for solving the systematic error issue by establishing matched references, collected at another detection site or at another time, and subsequently differencing to remove the common systematic errors. However, differencing weakens the signal of interest itself and enlarges the effects of the second issue, random disturbances affecting the precision. It is understood that only reference measurements that can meet the precision requirement will be promising for future applications. Therefore, this study quantitatively evaluates the precision of the main differential NIR spectroscopy measurements considering similar conditions and minimized random disturbances. The precision of the measurements under these conditions should represent their optimal precision levels. After the evaluation, noninvasive glucose-sensing methods that hold promise for future clinical application are proposed. Finally, the evaluation criteria could be a reference for the noninvasive detection of other physiological components.

Why Have So Many Intravascular Glucose Monitoring Devices Failed?

Secondary to the inherent limitations of both point-of-care and central laboratory glucose technologies, continuous glucose measurement has recently enjoyed a high level of investment. Because of the perceived advantages by some of measuring in the intravascular space compared to the subcutaneous tissue, a number of technologies have been developed. In this review, we evaluate nine systems that have shown promise, although only one of these has been cleared for sale in the United States. The detection methodology, regulatory status, technical issues, and company circumstance surrounding each technology are examined.

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.

Ex vivo optical measurements of glucose diffusion kinetics in native and diabetic mouse skin

The aim of this study was to estimate the glucose diffusion coefficients ex vivo in skin of mice with diabetes induced in vivo by alloxan in comparison to non-diabetic mice. The temporal dependences of collimated transmittance of tissue samples immersed in glucose solutions were measured in the VIS-NIR spectral range to quantify the glucose diffusion/permeability coefficients and optical clearing efficiency of mouse skin. The average thickness of intact healthy and diabetic skin was 0.023 ± 0.006 cm and 0.019 ± 0.005 cm, respectively. Considerable differences in optical and kinetic properties of diabetic and non-diabetic skin were found: clearing efficiency was 1.5-fold better and glucose diffusivity was 2-fold slower for diabetic skin. Experimental Setup for measuring collimated transmittance spectra of mouse skin samples.

Emerging trends in optical sensing of glycemic markers for diabetes monitoring

In the past decade, considerable attention has been focused on the measurement of glycemic markers, such as glycated hemoglobin and glycated albumin, that provide retrospective indices of average glucose levels in the bloodstream. While these biomarkers have been regularly used to monitor long-term glucose control in established diabetics, they have also gained traction in diabetic screening. Detection of such glycemic markers is challenging, especially in a point-of-care setting, due to the stringent requirements for sensitivity and robustness. A number of non-separation based measurement strategies were recently proposed, including photonic tools that are well suited to reagent-free marker quantitation. Here, we critically review these methods while focusing on vibrational spectroscopic methods, which offer highly specific molecular fingerprinting capability. We examine the underlying principles and the utility of these approaches as reagentless assays capable of multiplexed detection of glycemic markers and also the challenges in their eventual use in the clinic.

Noninvasive in vivo glucose sensing on human subjects using mid-infrared light

Mid-infrared quantum cascade laser spectroscopy is used to noninvasively predict blood glucose concentrations of three healthy human subjects in vivo. We utilize a hollow-core fiber based optical setup for light delivery and collection along with a broadly tunable quantum cascade laser to obtain spectra from human subjects and use standard chemo-metric techniques (namely partial least squares regression) for prediction analysis. Throughout a glucose concentration range of 80-160 mg/dL, we achieve clinically accurate predictions 84% of the time, on average. This work opens a new path to a noninvasive in vivo glucose sensor that would benefit the lives of hundreds of millions of diabetics worldwide.

Blood glucose measurement by using hollow optical fiber-based attenuated total reflection probe

A noninvasive glucose monitoring system based on mid-infrared, attenuated total reflection spectroscopy using a hollow optical fiber probe is developed. Owing to the flexible fiber probe, measurement of oral mucosa, where blood capillaries are near the skin surface, is possible. Blood glucose levels are measured by detecting the peak intensity of glucose absorption bands, and the experimental results showed that the reproducibility of the measurement is high enough for monitoring blood glucose.

Using experimental data designs and multivariate modeling to assess the effect of glycated serum protein concentration on glucose prediction from near-infrared spectra of human serum

Near-infrared (NIR) spectra of human blood serum consist of overlapping strong absorption bands of water and serum proteins, which affect the ability of multivariate calibration models to predict glucose. Furthermore, serum proteins such as albumin and globulins undergo a glycation reaction by forming covalent bonds with freely available glucose molecules in the serum. In diabetic individuals with poor glucose control, more and more serum protein molecules react with glucose, resulting in a high glycated protein concentration. The glucose molecules covalently bonded to serum proteins might contribute to the overall glucose signal acquired by NIR spectroscopy. This might affect the prediction ability of multivariate calibration models such as partial least squares regression (PLSR). In this study, we investigated the effect of total protein concentration and the glycated protein concentration in blood serum on the prediction ability of PLSR calibration models. Serum samples were subjected to ultra-filtration, and the PLSR model was built using NIR spectra of filtered serum solutions. Prediction performance was found to improve by 39-42% in absence of serum protein molecules. Various experimental data set designs were generated by carefully varying the glycated serum protein concentration in calibration and test sets of PLSR models. This investigation revealed that the impact of varying glycated protein concentration on the root mean square error of prediction was not drastic. To test the statistical significance of the prediction results, a multiple linear regression model was built. The glycated serum protein concentration was found to be statistically insignificant (p = 0.86) in predicting glucose concentration. Overall, it was concluded that the glycated serum proteins do not affect the glucose prediction accuracy of PLSR models using NIR spectra of human serum.

Detection and Monitoring of Microparticles Under Skin by Optical Coherence Tomography as an Approach to Continuous Glucose Sensing Using Implanted Retroreflectors

We demonstrate the feasibility of using optical coherence tomography (OCT) to image and detect 2.8 μm diameter microparticles (stationary and moving) on a highly-reflective gold surface both in clear media and under skin in vitro. The OCT intensity signal can clearly report the microparticle count, and the OCT response to the number of microparticles shows a good linearity. The detect ability of the intensity change (2.9% ± 0.5%) caused by an individual microparticle shows the high sensitivity of monitoring multiple particles using OCT. An optical sensing method based on this feasibility study is described for continuously measuring blood sugar levels in the subcutaneous tissue, and a molecular recognition unit is designed using competitive binding to modulate the number of bound microparticles as a function of glucose concentration. With further development, an ultra-small, implantable sensor might provide high specificity and sensitivity for long-term continuous monitoring of blood glucose concentration.

Investigation of noise-induced instabilities in quantitative biological spectroscopy and its implications for noninvasive glucose monitoring

Over the past decade, optical spectroscopy has been employed in combination with multivariate chemometric models to investigate a wide variety of diseases and pathological conditions, primarily due to its excellent chemical specificity and lack of sample preparation requirements. Despite promising results in several proof-of-concept studies, its translation to the clinical setting has often been hindered by inadequate accuracy of the conventional spectroscopic models. To address this issue and the possibility of curved (nonlinear) effects in the relationship between the concentrations of the analyte of interest and the mixture spectra (due to fluctuations in sample and environmental conditions), support vector machine-based least-squares nonlinear regression (LS-SVR) has been recently proposed. In this paper, we investigate the robustness of this methodology to noise-induced instabilities and present an analytical formula for estimating modeling precision as a function of measurement noise and model parameters. This formalism can be readily used to evaluate uncertainty in information extracted from spectroscopic measurements, particularly important for rapid-acquisition biomedical applications. Subsequently, using field data (Raman spectra) acquired from a glucose clamping study on an animal model subject, we perform the first systematic investigation of the relative effect of additive interference components (namely, noise in prediction spectra, calibration spectra, and calibration concentrations) on the prediction error of nonlinear spectroscopic models. Our results show that the LS-SVR method gives more accurate results and is substantially more robust to additive noise when compared with conventional regression methods such as partial least-squares regression (PLS), when careful selection of the LS-SVR model parameters are performed. We anticipate that these results will be useful for uncertainty estimation in similar biomedical applications where the precision of measurements and its response to noise in the data set is as important, if not more so, than the generic accuracy level.

Wearable medical systems for p-Health

Driven by the growing aging population, prevalence of chronic diseases, and continuously rising healthcare costs, the healthcare system is undergoing a fundamental transformation, from the conventional hospital-centered system to an individual-centered system. Current and emerging developments in wearable medical systems will have a radical impact on this paradigm shift. Advances in wearable medical systems will enable the accessibility and affordability of healthcare, so that physiological conditions can be monitored not only at sporadic snapshots but also continuously for extended periods of time, making early disease detection and timely response to health threats possible. This paper reviews recent developments in the area of wearable medical systems for p-Health. Enabling technologies for continuous and noninvasive measurements of vital signs and biochemical variables, advances in intelligent biomedical clothing and body area networks, approaches for motion artifact reduction, strategies for wearable energy harvesting, and the establishment of standard protocols for the evaluation of wearable medical devices are presented in this paper with examples of clinical applications of these technologies.

Recent advances in noninvasive glucose monitoring

The race for the next generation of painless and reliable glucose monitoring for diabetes mellitus is on. As technology advances, both diagnostic techniques and equipment improve. This review describes the main technologies currently being explored for noninvasive glucose monitoring. The principle of each technology is mentioned; its advantages and limitations are then discussed. The general description and the corresponding results for each device are illustrated, as well as the current status of the device and the manufacturer; internet references for the devices are listed where appropriate. Ten technologies and eleven potential devices are included in this review. Near infrared spectroscopy has become a promising technology, among others, for blood glucose monitoring. Although some reviews have been published already, the rapid development of technologies and information makes constant updating mandatory. While advances have been made, the reliability and the calibration of noninvasive instruments could still be improved, and more studies carried out under different physiological conditions of metabolism, bodily fluid circulation, and blood components are needed.

Noninvasive in vitro measurement of pig-blood d-glucose by using a microwave cavity sensor

We have developed an electromagnetic microwave cavity sensor based on the resonant frequency shift for real time measurement of the glycemia in pig blood. We could determine the concentration of d-glucose in pig blood in the range of 150-550mg/dl at the resonance frequency near 4.75GHz with a bandwidth of 300MHz. The change in the d-glucose concentration in blood brings microwave reflection coefficient S(11) changes of about 6.26dB and resonance frequency shifts of about 11.25MHz due to the electromagnetic interaction between the cavity resonator and the blood filled plastic tube inserted into the cavity. This proposed system provides a unique approach for real time noninvasive and contactless glucose monitoring.

Detection of aqueous glucose based on a cavity size- and optical-wavelength-independent continuous-wave photoacoustic technique

Toward the achievement of noninvasive and continuous monitoring of blood glucose level, we developed a new measurement method based on the continuous-wave photoacoustic (CW-PA) technique and performed the first validation in vitro with calibrated aqueous glucose solutions. The PA technique has been studied in the past but exclusively based on the pulse setup since the CW one exhibits dependence on the cavity dimensions, which is not compatible with the final application requirements. This paper describes a new strategy relying on the monitoring of the resonant-frequency relative shift induced by the change of glucose concentrations rather than amplitude signal levels at a fixed frequency. From in vitro results, we demonstrate a stable and reproducible response to glucose at various cavity dimensions and optical wavelengths, with a slope of 0.19 ±0.01%/g/dL. From theoretical considerations, this method is consistent with a relative acoustic velocity measurement, which also explains the aforementioned stability. The proposed method then resolves most of the issues usually associated with the CW-PA technique and makes it a potential alternative for the noninvasive and continuous monitoring of glycemia levels. However, experimental determination of sensor responses to albumin and temperature as two potential interferents shows similar levels, which points to the selectivity to glucose as a major issue we should deal with in future development.

Correlation between sweat glucose and blood glucose in subjects with diabetes

BACKGROUND

Sweat contains glucose that can accurately reflect blood glucose. However, skin surface glucose can confound these measurements.

METHODS

A perfusion method was used to rapidly harvest sweat from forearm sites on human subjects. The sweat samples were analyzed for glucose by high-performance liquid chromatography methods and compared with the results obtained with a blood glucose meter.

RESULTS

The results of 23 different studies of seven individual subjects with diabetes show a strong correlation between sweat glucose and blood glucose.

CONCLUSION

Sweat glucose, when properly harvested to prevent contamination from other sources on the skin's surface, can accurately reflect blood glucose levels.

Non-invasive glucose monitoring technology in diabetes management: a review

The frequent monitoring of glucose is an essential part of diabetes management. Despite the fact that almost all the commercially successful blood glucose monitoring devices are invasive, there is an immense need to develop non-invasive glucose monitoring (NGM) devices that will alleviate the pain and suffering of diabetics associated with the frequent pricking of skin for taking the blood sample for glucose testing. There have been numerous developments in the field of NGM during the last decade, which stress the need for a critical review. This manuscript aims to review the various NGM techniques and devices. The challenges and future trends in NGM are also discussed.

Glucose sensing in human epidermis using mid-infrared photoacoustic detection

No reliable non-invasive glucose monitoring devices are currently available. We implemented a mid-infrared (MIR) photoacoustic (PA) setup to track glucose in vitro in deep epidermal layers, which represents a significant step towards non-invasive in vivo glucose measurements using MIR light. An external-cavity quantum-cascade laser (1010-1095 cm(-1)) and a PA cell of only 78 mm(3) volume were employed to monitor glucose in epidermal skin. Skin samples are characterized by a high water content. Such samples investigated with an open-ended PA cell lead to varying conditions in the PA chamber (i.e., change of light absorption or relative humidity) and cause unstable signals. To circumvent variations in relative humidity and possible water condensation, the PA chamber was constantly ventilated by a 10 sccm N(2) flow. By bringing the epidermal skin samples in contact with aqueous glucose solutions with different concentrations (i.e., 0.1-10 g/dl), the glucose concentration in the skin sample was varied through passive diffusion. The achieved detection limit for glucose in epidermal skin is 100 mg/dl (SNR=1). Although this lies within the human physiological range (30-500 mg/dl) further improvements are necessary to non-invasively monitor glucose levels of diabetes patients. Furthermore spectra of epidermal tissue with and without glucose content have been recorded with the tunable quantum-cascade laser, indicating that epidermal constituents do not impair glucose detection.