Non-invasive Continuous Glucose Monitoring Research Articles

Advancing Glucose Monitoring: A Near-Infrared Device for Continuous Invasive Assessment

Diabetes is a chronic disease that affects millions of people worldwide, with the number of newly diagnosed cases continuing to rise at an alarming rate. Patients diagnosed with diabetes require routine monitoring of their blood glucose levels, which is commonly done through invasive and minimally invasive techniques. However, these methods are often painful, prone to infection, and costly in the long run. Therefore, it is necessary to develop non-invasive, pain-free, affordable glucose monitoring techniques. Near-infrared spectroscopy has emerged as a promising technique among the non-invasive techniques for glucose monitoring, with several studies reporting its efficacy in detecting glucose concentration. This study designed and developed a near-infrared system based on an 1150nm wavelength for continuous non-invasive glucose monitoring. The system gave the output voltages that vary with increased glucose concentrations. It was ascertained from the Clark error grid analysis that the glucose concentration falls within region A and region B. This implies that the device is suitable for measuring glucose concentration non-invasively. As per Bland Altman's analysis, the majority of the data points were within both limits of agreement except one data point that was outside the upper limit of agreement, indicating 93% degree of accuracy, and the residual plot indicates that the regression model for the system is appropriate for predicting non-invasive glucose measurements.

Flexible cellulose paper-based biosensor from inkjet printing for non-invasive glucose monitoring

Wearable glucose sensors have attracted significant attention for enabling non-invasive blood glucose measurement without discomfort and risk of infection. However, it is a challenge to simultaneously realize wearable adaptability, biodegradability, and excellent sensing performance. Herein, a cellulose paper-based non-invasive biosensor relying on reverse iontophoresis was designed to detect glucose in interstitial fluid (ISF), and two different enzyme immobilization strategies have been compared. The results showed inkjet-printed cellulose paper-based biosensor (IPB) performances better than the drop-coated cellulose paper-based biosensor (DPB). IPB has twice response current more than DPB in detection range (0–10 mM). In sensitivity, IPB is 1.170 μA/mM three times higher than the DPB (0.376 μA/mM). Besides, IPB's electron-transfer resistance (Rct) is 7.27 kΩ smaller than DPB (Rct = 10.51 kΩ) about 30 %. More importantly, IPB exhibited a good reproducibility (RSD, 4.82 %), which was much less than DPB (RSD, 18.35 %). Furthermore, the IPB realizes noninvasive continuous glucose monitoring over 6 h in volunteer experiments with great analytical performance comparable to commercial devices (Pearson correlation 0.732). Cellulose paper-based glucose sensors with inkjet printing provide non-invasive access to statistically significant diagnostic information, simple and cost-effective, which promotes the application of flexible, wearable, degradable bioelectrodes in continuous glucose monitoring at home, providing a concept for full integration in a compact and portable way in the future.

Optimizing the Performance of AI Model for Non-Invasive Continuous Glucose Monitoring: Hyperparameter Tuning and Random Oversampling Approach

Diabetes Mellitus (DM) as a non-communicable disease (NCD) continues to increase every year. Continuous glucose monitoring (CGM) is essential for effective DM management. However, existing disposable glucose monitoring methods still rely on invasive techniques, cause pain, and lack continuous monitoring capabilities. On the other hand, non-invasive techniques are not feasible for CGM due to the biometric data's complexity and the classification system's inadequate performance. This study aims to develop a non-invasive technology to improve the performance of a non-invasive blood glucose classification system using Artificial Intelligence (AI), specifically Convolutional Neural Network (CNN) and an oversampling technique. The oversampling technique could improve data quantity by balancing the amount of data for each class. This study recruited twenty-three participants in the age range of 20 to 22 years comprising seven females and fifteen males. During data recording sessions, blood glucose levels were simultaneously assessed using a gold-standard glucometer and a non-invasive CGM prototype. The proposed CNN model successfully improved the classification accuracy of non-invasive blood glucose monitoring significantly. With the implementation of oversampling for augmenting the data, the accuracy of the proposed model increased to more than 88%. This study concludes that non-invasive approaches combined with AI technology have the potential to provide a convenient and pain-free alternative to traditional monitoring methods, significantly improving diabetes management and enhancing the overall quality of life for those affected by this condition. These findings could revolutionize the field of diabetes management, offering a more comfortable and accurate monitoring solution that could potentially transform the lives of millions of diabetes patients.

Mechanical Robustness Enhanced Flexible Antennas Using Ti3C2 MXene and Nanocellulose Composites for Noninvasive Glucose Sensing.

Electromagnetic sensors with flexible antennas as sensing elements have attracted increasing attention in noninvasive continuous glucose monitoring for diabetic patients. The significant radiation performance loss of flexible antennas during mechanical deformation impairs the reliability of glucose monitoring. Here, we present flexible ultrawideband monopole antennas composed of Ti3C2 MXene and cellulose nanofibril (CNF) composite films for continuous glucose monitoring. The flexible MXene/CNF antenna with 20% CNF content can obtain a gain of up to 3.33 dBi and a radiation efficiency of up to 65.40% at a frequency range from 2.3 to 6.0 GHz. Compared with the pure MXene antenna, this antenna offers a comparable radiation performance and a lower performance loss in mechanical bending deformation. Moreover, the MXene/CNF antenna shows a stable response to fetal bovine serum/glucose, with a correlation of >0.9 at the reference glucose levels, and responds sensitively to the variations in blood glucose levels during human trials. The proposed strategy enhancing the mechanical robustness of MXene-based flexible antennas makes metallic two-dimensional nanomaterials more promising in wearable electromagnetic sensors.

High-accuracy noninvasive continuous glucose monitoring using OCT angiography-purified blood scattering signals in human skin.

The accuracy of noninvasive continuous glucose monitoring (CGM) through near-infrared scattering is challenged by mixed scattering signals from different compartments, where glucose has a positive correlation with a blood scattering coefficient but a negative correlation with a tissue scattering coefficient. In this study, we developed a high-accuracy noninvasive CGM based on OCT angiography (OCTA)-purified blood scattering signals. The blood optical scattering coefficient (BOC) was initially extracted from the depth attenuation of backscattered light in OCT and then purified by eliminating the scattering signals from the surrounding tissues under the guidance of a 3D OCTA vascular map in human skin. The purified BOC was used to estimate the optical blood glucose concentration (BGC) through a linear calibration. The optical and reference BGC measurements were highly correlated (R = 0.94) without apparent time delay. The mean absolute relative difference was 6.09%. All optical BGC measurements were within the clinically acceptable Zones A + B, with 96.69% falling in Zone A on Parke's error grids. The blood glucose response during OGTT was mapped with a high spatiotemporal resolution of the single vessel and 5 seconds. This noninvasive OCTA-based CGM shows promising accuracy for clinical use. Future research will involve larger sample sizes and diabetic participants to confirm these preliminary findings.

ТРАНСФОРМАЦИЯ ЗДОРОВЬЕСБЕРЕГАЮЩИХ ТЕХНОЛОГИЙ НА ПРИМЕРЕ МОНИТОРИНГА УРОВНЯ ГЛЮКОЗЫ КРОВИ. ЛИТЕРАТУРНЫЙ ОБЗОР

In recent years, there has been a steady increase in the number of people with chronic non-communicable diseases and premature death due to a sedentary lifestyle and decreased physical activity. Studying the consequences of physical inactivity is justified to obtain irrefutable evidence of the relationship between such behavior and the increasing prevalence of obesity and diabetes. The incidence of diabetes is growing at an alarming rate and regular monitoring of glucose levels is critical to combating diabetes complications in the era of developing health-saving technologies. Currently, glucose level in the body is measured invasively by determining it in a small blood sample, usually taken from the fingertip and placed on a disposable test strip. Therefore, there is a need for non-invasive continuous glucose monitoring. Researchers' innovations in the field of non-invasive continuous glucose monitoring using sensors are based on various approaches and are mainly associated with the development of analyzers that can be integrated into a constantly worn device. This review article presents the latest advances in health-saving technologies for diabetes.

Analysis of Non-Invasive Devices and Techniques Involved in Continuous Monitoring of Interstitial Glucose of Patients with Type 1 Diabetes

Abstract: There are 422 million diabetes patients worldwide according to 2023 census of WHO, and around 100 million cases in India. 8.4 million type 1 diabetes cases were recorded as of 2021. By 2040, it is projected that the number of people living with Type 1 Diabetes will reach 13.5–17.4 million. The surge in diabetes cases has created the critical need for regular glucose monitoring to effectively manage this prevalent health issue. Currently, glucose levels are predominantly measured invasively by pricking the finger for a blood sample and involves invasive methods, such as fingertip pricks, which can be uncomfortable and inconvenient, particularly for paediatric patients. This method utilizes blood glucose monitoring devices, which measure sugar levels in a small blood sample placed on a disposable test strip and have a certain degree of inaccuracy. Patients do not test as often as they should because of the pain and hassle of finger pricks and many do not achieve optimal glycaemic control. However, the shift toward non-invasive continuous glucose monitoring is becoming increasingly imperative and a promising alternative. With current biotechnological advances, many techniques offer a non-invasive, continuous means of monitoring glucose levels and have garnered significant attention in recent years. The objective is to consolidate and summarize recent advancements in non-invasive continuous glucose monitoring, emphasizing integration into wearable platforms for seamless and real-time monitoring. Furthermore, paediatric patients with Type 1 Diabetes face elevated risks of severe hypoglycaemic and hyperglycaemic events due to challenges in glycaemic control. Frequently, monitoring blood glucose is crucial to mitigate these risks and achieve optimal glycaemic management. The objective of ongoing research is to validate AI-based algorithms utilizing ECG signals collected through non-invasive devices to detect glycaemic events. These advancements, once commercially available, have the potential to revolutionize glucose monitoring, offering a convenient, efficient, and less intrusive approach, particularly benefiting paediatric patients and improving overall healthcare management. Despite substantial research and development, challenges persist, including standardizing sweat collection methods, addressing sample degradation, accounting for variations in sweat composition among individuals, optimizing diverse detection methods, improving glucose detection sensitivity, and ensuring overall commercial viability. Overcoming these challenges is paramount to bridge the gap between research and market availability, paving the way for a technological revolution in glucose monitoring. In this study, we compared potential non-invasive glucose monitoring devices and techniques to evaluate the most accurate, pain-free, fast, and cost-friendly device. Upon examination and survey, we have theorized the drawbacks persisting in the existing devices and hypothesized techniques. Looking forward this study has a broader application in not only understanding the limitations and creating more accurate devices but also in continuous glucose monitoring for diabetic patient care.

Review of Noninvasive Continuous Glucose Monitoring in Diabetics.

For diabetics, taking regular blood glucose measurements is crucial. However, traditional blood glucose monitoring methods are invasive and unfriendly to diabetics. Recent studies have proposed a biofluid-based glucose sensing technique that creatively combines wearable devices with noninvasive glucose monitoring technology to enhance diabetes management. This is a revolutionary advance in the diagnosis and management of diabetes, reflects the thoughtful modernization of medicine, and promotes the development of digital medicine. This paper reviews the research progress of noninvasive continuous blood glucose monitoring (CGM), with a focus on the biological liquids that replace blood in monitoring systems, the technical principles of continuous noninvasive glucose detection, and the output and calibration of sensor signals. In addition, the existing limits of noninvasive CGM systems and prospects for the future are discussed. This work serves as a resource for further promoting the development of noninvasive CGM systems.

Beware of buying online noninvasive continuous glucose monitoring devices: danger is just around the corner!

Beware of buying online noninvasive continuous glucose monitoring devices: danger is just around the corner!

MOF-Based Materials for Glucose Detection

Metal–organic frameworks (MOFs), constructed by coordination between metal-containing nodes and organic linkers, are widely used in various fields due to the advantages of tunable pores, diverse functional sites, stable structure, and multi-functionality. It should be noted that MOF-based materials play a major role in glucose detection, serving as a signal transducer or functional substrate for embedding nanoparticles/enzymes. Diabetes is one of the most common and fast-growing diseases worldwide, whose main clinical manifestation is high blood sugar levels. Therefore, accurate, sensitive, and point-of-care glucose detection is necessary. This review orderly introduces general synthetic strategies of MOF-based materials (pristine MOF, nanoparticles, or enzymes-modified MOF and MOF-derived materials) and detection methods (electrochemical and optical methods) for glucose detection. Then, the review refers to the novel MOF-based glucose detection devices (flexible wearable devices and microfluidic chips), which enable non-invasive continuous glucose monitoring or low-cost microscale detection. On the basis of describing the development of glucose sensors based on MOF materials in the past five years, the review presents merits, demerits, and possible improvements of various detection methods.

Longitudinal Studies of Wearables in Patients with Diabetes: Key Issues and Solutions.

Glucose monitoring is key to the management of diabetes mellitus to maintain optimal glucose control whilst avoiding hypoglycemia. Non-invasive continuous glucose monitoring techniques have evolved considerably to replace finger prick testing, but still require sensor insertion. Physiological variables, such as heart rate and pulse pressure, change with blood glucose, especially during hypoglycemia, and could be used to predict hypoglycemia. To validate this approach, clinical studies that contemporaneously acquire physiological and continuous glucose variables are required. In this work, we provide insights from a clinical study undertaken to study the relationship between physiological variables obtained from a number of wearables and glucose levels. The clinical study included three screening tests to assess neuropathy and acquired data using wearable devices from 60 participants for four days. We highlight the challenges and provide recommendations to mitigate issues that may impact the validity of data capture to enable a valid interpretation of the outcomes.

Noninvasive Continuous Glucose Monitoring With a Novel Wearable Dial Resonating Sensor: A Clinical Proof-of-Concept Study.

A noninvasive, wearable continuous glucose monitor would be a major advancement in diabetes therapy. This trial investigated a novel noninvasive glucose monitor which analyzes spectral variations in radio frequency/microwave signals reflected from the wrist. A single-arm, open-label, experimental study compared glucose values from a prototype investigational device with laboratory glucose measurements from venous blood samples (Super GL Glucose Analyzer, Dr. Müller Gerätebau GmbH) at varying levels of glycemia. The study included 29 male participants with type 1 diabetes (age range = 19-56 years). The study comprised three stages with the following aims: (1) demonstrate initial proof-of-principle, (2) test an improved device design, and (3) test performance on two consecutive days without device recalibration. The co-primary endpoints in all trial stages were median and mean absolute relative difference (ARD) calculated across all data points. In stage 1, the median and mean ARDs were 30% and 46%, respectively. Stage 2 produced marked performance improvements with a median and mean ARD of 22% and 28%, respectively. Stage 3 showed that, without recalibration, the device performed as well as the initial prototype (stage 1) with a median and mean ARD of 35% and 44%, respectively. This proof-of-concept study shows that a novel noninvasive continuous glucose monitor was capable of detecting glucose levels. Furthermore, the ARD results are comparable to first models of commercially available minimally invasive products without the need to insert a needle. The prototype has been further developed and is being tested in subsequent studies. NCT05023798.

Non-invasive method for blood glucose monitoring using ECG signal

Abstract Introduction: Tight glucose monitoring is crucial for diabetic patients by using a Continuous Glucose Monitor (CGM). The existing CGMs measure the Blood Glucose Concentration (BGC) from the interstitial fluid. These technologies are quite expensive, and most of them are invasive. Previous studies have demonstrated that hypoglycemia and hyperglycemia episodes affect the electrophysiology of the heart. However, they did not determine a cohort relationship between BGC and ECG parameters. Material and method: In this work, we propose a new method for determining the BGC using surface ECG signals. Recurrent Convolutional Neural Networks (RCNN) were applied to segment the ECG signals. Then, the extracted features were employed to determine the BGC using two mathematical equations. This method has been tested on 04 patients over multiple days from the D1namo dataset, using surface ECG signals instead of intracardiac signal. Results: We were able to segment the ECG signals with an accuracy of 94% using the RCNN algorithm. According to the results, the proposed method was able to estimate the BGC with a Mean Absolute Error (MAE) of 0.0539, and a Mean Squared Error (MSE) of 0.1604. In addition, the linear relationship between BGC and ECG features has been confirmed in this paper. Conclusion: In this paper, we propose the potential use of ECG features to determine the BGC. Additionally, we confirmed the linear relationship between BGC and ECG features. That fact will open new perspectives for further research, namely physiological models. Furthermore, the findings point to the possible application of ECG wearable devices for non-invasive continuous blood glucose monitoring via machine learning.

Design and Verification of Noninvasive Wearable Continuous Blood Glucose Monitoring System for Smartwatches

Design and Verification of Noninvasive Wearable Continuous Blood Glucose Monitoring System for Smartwatches

Monitoring glucose levels in urine using FTIR spectroscopy combined with univariate and multivariate statistical methods

The development of novel platforms for non-invasive continuous glucose monitoring applied in the screening and monitoring of diabetes is crucial to improve diabetes surveillance systems. Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy of urine can be an alternative as a sustainable, label-free, fast, non-invasive, and highly sensitive analysis to detect changes in urine promoted by diabetes and insulin treatment. In this study, we used ATR-FTIR to evaluate the urinary components of non-diabetic (ND), diabetic (D), and diabetic insulin-treated (D + I) rats. As expected, insulin treatment was capable to revert changes in glycemia, 24-h urine collection volume, urine creatinine, urea, and glucose excretion promoted by diabetes. Several differences in the urine spectra of ND, D, and D + I were observed, with urea, creatinine, and glucose analytes being related to these changes. Principal components analysis (PCA) scores plots allowed for the discrimination of ND and D + I from D with an accuracy of ∼ 99 %. The PCA loadings associated with PC1 confirmed the importance of urea and glucose vibrational modes for this discrimination. Univariate analysis of second derivative spectra showed a high correlation (r: 0.865, p < 0.0001) between the height of 1074 cm-1 vibrational mode with urinary glucose concentration. In order to estimate the amount of glucose present in the infrared spectra from urine, multivariate curve resolution-alternating least square (MCR-ALS) was applied and a higher predicted concentration of glucose in the urine was observed with a correlation of 78.9 % compared to urinary glucose concentration assessed using enzyme assays. In summary, ATR-FTIR combined with univariate and multivariate chemometric analyses provides an innovative, non-invasive, and sustainable approach to diabetes surveillance.

A Concise and Systematic Review on Non-Invasive Glucose Monitoring for Potential Diabetes Management.

The current standard of diabetes management depends upon the invasive blood pricking techniques. In recent times, the availability of minimally invasive continuous glucose monitoring devices have made some improvements in the life of diabetic patients however it has its own limitations which include painful insertion, excessive cost, discomfort and an active risk due to the presence of a foreign body under the skin. Due to all these factors, the non-invasive glucose monitoring has remain a subject of research for the last two decades and multiple techniques of non-invasive glucose monitoring have been proposed. These proposed techniques have the potential to be evolved into a wearable device for non-invasive diabetes management. This paper reviews research advances and major challenges of such techniques or methods in recent years and broadly classifies them into four types based on their detection principles. These four methods are: optical spectroscopy, photoacoustic spectroscopy, electromagnetic sensing and nanomaterial based sensing. The paper primarily focuses on the evolution of non-invasive technology from bench-top equipment to smart wearable devices for personalized non-invasive continuous glucose monitoring in these four methods. With the rapid evolve of wearable technology, all these four methods of non-invasive blood glucose monitoring independently or in combination of two or more have the potential to become a reality in the near future for efficient, affordable, accurate and pain-free diabetes management.

Design of an Out-Folded Patch Antenna With a Zeroth-Order Resonance for Non-Invasive Continuous Glucose Monitoring

This article proposes an out-folded patch antenna with a zeroth-order resonance (ZOR) that is robust to a high-dielectric condition of a human body for noninvasive continuous glucose monitoring (CGM). The proposed antenna has two faces of a tapered section and a rectangular patch separated by a gap, and those faces are connected through vias at two corners near the gap. Two identical antennas are fabricated on a flexible printed circuit board (FPCB), and the properties of ZOR are compared with those of the fundamental mode to demonstrate the feasibility. The ZOR of the proposed antenna exhibits a negligible frequency shift, and its quality factor is 2.9 times higher than the fundamental mode, when attached to the skin. The evaluation is further extended to a human experiment using the two antennas for real-time estimation of coupling strength according to the change in glucose concentration. The trend of measured coupling strength well describes that of the glucose concentration obtained from a glucose meter with a mean absolute relative difference of 12.23%. The results demonstrate that the proposed concept has a great potential to improve the accuracy of noninvasive estimation in microwave spectrum.

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.

Selection of Noninvasive Features in Wrist-Based Wearable Sensors to Predict Blood Glucose Concentrations Using Machine Learning Algorithms

Glucose monitoring technologies allow users to monitor glycemic fluctuations (e.g., blood glucose levels). This is particularly important for individuals who have diabetes mellitus (DM). Traditional self-monitoring blood glucose (SMBG) devices require the user to prick their finger and extract a blood drop to measure the blood glucose based on chemical reactions with the blood. Unlike traditional glucometer devices, noninvasive continuous glucose monitoring (NICGM) devices aim to solve these issues by consistently monitoring users’ blood glucose levels (BGLs) without invasively acquiring a sample. In this work, we investigated the feasibility of a novel approach to NICGM using multiple off-the-shelf wearable sensors and learning-based models (i.e., machine learning) to predict blood glucose. Two datasets were used for this study: (1) the OhioT1DM dataset, provided by the Ohio University; and (2) the UofM dataset, created by our research team. The UofM dataset consists of fourteen features provided by six sensors for studying possible relationships between glucose and noninvasive biometric measurements. Both datasets are passed through a machine learning (ML) pipeline that tests linear and nonlinear models to predict BGLs from the set of noninvasive features. The results of this pilot study show that the combination of fourteen noninvasive biometric measurements with ML algorithms could lead to accurate BGL predictions within the clinical range; however, a larger dataset is required to make conclusions about the feasibility of this approach.

Comprehensive Review on Wearable Sweat-Glucose Sensors for Continuous Glucose Monitoring.

The incidence of diabetes is increasing at an alarming rate, and regular glucose monitoring is critical in order to manage diabetes. Currently, glucose in the body is measured by an invasive method of blood sugar testing. Blood glucose (BG) monitoring devices measure the amount of sugar in a small sample of blood, usually drawn from pricking the fingertip, and placed on a disposable test strip. Therefore, there is a need for non-invasive continuous glucose monitoring, which is possible using a sweat sensor-based approach. As sweat sensors have garnered much interest in recent years, this study attempts to summarize recent developments in non-invasive continuous glucose monitoring using sweat sensors based on different approaches with an emphasis on the devices that can potentially be integrated into a wearable platform. Numerous research entities have been developing wearable sensors for continuous blood glucose monitoring, however, there are no commercially viable, non-invasive glucose monitors on the market at the moment. This review article provides the state-of-the-art in sweat glucose monitoring, particularly keeping in sight the prospect of its commercialization. The challenges relating to sweat collection, sweat sample degradation, person to person sweat amount variation, various detection methods, and their glucose detection sensitivity, and also the commercial viability are thoroughly covered.