Noninvasive, wearable, and tunable electromagnetic multisensing system for continuous glucose monitoring, mimicking vasculature anatomy

Non-Destructive Sensor for Glucose Solution Concentration Detection Using Electromagnetic Technology

In this paper, a sensor using a complementary split ring resonator (CSRR) is proposed for non-destructive testing of blood glucose. By depicting the complementary split ring structure on the ground, the electromagnetic field strength between the split rings can be enhanced effectively. The structure size of the sensor by CSRR is determined by simulation, so that the insertion loss curve of the device has a resonance point at the frequency of 3.419 GHz. With a special holder created by three-dimensional (3D) printing technology, the test platform was established when the concentration of the solution varied from 0 mg/mL to 20 mg/mL. The experimental results indicate that there is an obvious linear relationship between the insertion loss S21 and the glucose concentration at the resonant frequency. Similarly, the measured real part and imaginary part of the S21 both vary with glucose concentration linearly. Based on the above experimental results, the feasibility of the sensor using a CSRR proposed in this paper for non-destructive detection of blood glucose is preliminarily verified.

In Vitro Glucose Measurement from NIR and MIR Spectroscopy: Comprehensive Benchmark of Machine Learning and Filtering Chemometrics

The quantitative analysis of glucose using spectroscopy is a topic of great significance and interest in science and industry. One conundrum in this area is deploying appropriate preprocessing and regression tools. To contribute to addressing this challenge, in this study, we conducted a comprehensive and novel comparative analysis of various machine learning and preprocessing filtering techniques applied to near-infrared, mid-infrared, and a combination of near-infrared and mid-infrared spectroscopy for glucose assay. Our objective was to evaluate the effectiveness of these techniques in accurately predicting glucose levels and to determine which approach was most optimal. Our investigation involved the acquisition of spectral data from samples of glucose solutions using the three aforementioned spectroscopy techniques. The data was subjected to several preprocessing filtering methods, including convolutional moving average, Savitzky-Golay, multiplicative scatter correction, and normalisation. We then applied representative machine learning algorithms from three categories: linear modelling, traditional nonlinear modelling, and artificial neural networks. The evaluation results revealed that linear models exhibited higher predictive accuracy than nonlinear models, whereas artificial neural network models demonstrated comparable performance. Additionally, the comparative analysis of various filtering methods demonstrated that the convolutional moving average and Savitzky-Golay filters yielded the most precise outcomes overall. In conclusion, our study provides valuable insights into the efficacy of different machine learning techniques for glucose measurement and highlights the importance of applying appropriate filtering methods in enhancing predictive accuracy. These findings have important implications for the development of new and improved glucose quantification technologies.

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.

Technological Advances of Wearable Device for Continuous Monitoring of In Vivo Glucose

Managing diabetes is a chronic challenge today, requiring monitoring and timely insulin injections to maintain stable blood glucose levels. Traditional clinical testing relies on fingertip or venous blood collection, which has facilitated the emergence of continuous glucose monitoring (CGM) technology to address data limitations. Continuous glucose monitoring technology is recognized for tracking long-term blood glucose fluctuations, and its development, particularly in wearable devices, has given rise to compact and portable continuous glucose monitoring devices, which facilitates the measurement of blood glucose and adjustment of medication. This review introduces the development of wearable CGM-based technologies, including noninvasive methods using body fluids and invasive methods using implantable electrodes. The advantages and disadvantages of these approaches are discussed as well as the use of microneedle arrays in minimally invasive CGM. Microneedle arrays allow for painless transdermal puncture and are expected to facilitate the development of wearable CGM devices. Finally, we discuss the challenges and opportunities and look forward to the biomedical applications and future directions of wearable CGM-based technologies in biological research.

Non-invasive blood glucose estimation method based on the phase delay between oxy- and deoxyhemoglobin using visible and near-infrared spectroscopy

Significance

Many researchers have attempted to estimate blood glucose levels (BGLs) noninvasively using near-infrared (NIR) spectroscopy. However, the optical absorption change induced by blood glucose is weak in the NIR region and often masked by interference from other components such as water and hemoglobin.

Aim

Instead of using direct optical absorption by glucose, this study proposes an index calculated from oxy- and deoxyhemoglobin signals that shows a good correlation with BGLs while using conventional visible and NIR spectroscopy.

Approach

The metabolic index, which is based on tissue oxygen consumption, was derived through analytical methods and further verified and reproduced in a series of glucose challenge experiments. Blood glucose estimation units were prototyped by utilizing commercially available smart devices.

Results

Our experimental results showed that the phase delay between the oxy- and deoxyhemoglobin signals in near-infrared spectroscopy correlates with BGL measured by a conventional continuous glucose monitor. The proposed method was also confirmed to work well with visible spectroscopy systems based on smartphone cameras. The proposed method also demonstrated excellent repeatability in results from a total of 19 oral challenge tests.

Conclusions

This study demonstrated the feasibility of non-invasive glucose monitoring using existing photoplethysmography sensors for pulse oximeters and smartwatches. Evaluating the proposed method in diabetic or unhealthy individuals may serve to further increase its practicality.

Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes

Innovations in digital health and machine learning are changing the path of clinical health and care. People from different geographical locations and cultural backgrounds can benefit from the mobility of wearable devices and smartphones to monitor their health ubiquitously. This paper focuses on reviewing the digital health and machine learning technologies used in gestational diabetes - a subtype of diabetes that occurs during pregnancy. This paper reviews sensor technologies used in blood glucose monitoring devices, digital health innovations and machine learning models for gestational diabetes monitoring and management, in clinical and commercial settings, and discusses future directions. Despite one in six mothers having gestational diabetes, digital health applications were underdeveloped, especially the techniques that can be deployed in clinical practice. There is an urgent need to (1) develop clinically interpretable machine learning methods for patients with gestational diabetes, assisting health professionals with treatment, monitoring, and risk stratification before, during and after their pregnancies; (2) adapt and develop clinically-proven devices for patient self-management of health and well-being at home settings ("virtual ward" and virtual consultation), thereby improving clinical outcomes by facilitating timely intervention; and (3) ensure innovations are affordable and sustainable for all women with different socioeconomic backgrounds and clinical resources.

3D Printing of Dietary Products for the Management of Inborn Errors of Intermediary Metabolism in Pediatric Populations

The incidence of Inborn Error of Intermediary Metabolism (IEiM) diseases may be low, yet collectively, they impact approximately 6-10% of the global population, primarily affecting children. Precise treatment doses and strict adherence to prescribed diet and pharmacological treatment regimens are imperative to avert metabolic disturbances in patients. However, the existing dietary and pharmacological products suffer from poor palatability, posing challenges to patient adherence. Furthermore, frequent dose adjustments contingent on age and drug blood levels further complicate treatment. Semi-solid extrusion (SSE) 3D printing technology is currently under assessment as a pioneering method for crafting customized chewable dosage forms, surmounting the primary limitations prevalent in present therapies. This method offers a spectrum of advantages, including the flexibility to tailor patient-specific doses, excipients, and organoleptic properties. These elements are pivotal in ensuring the treatment's efficacy, safety, and adherence. This comprehensive review presents the current landscape of available dietary products, diagnostic methods, therapeutic monitoring, and the latest advancements in SSE technology. It highlights the rationale underpinning their adoption while addressing regulatory aspects imperative for their seamless integration into clinical practice.

In-human testing of a non-invasive continuous low-energy microwave glucose sensor with advanced machine learning capabilities

Continuous glucose monitoring schemes that avoid finger pricking are of utmost importance to enhance the comfort and lifestyle of diabetic patients. To this aim, we propose a microwave planar sensing platform as a potent sensing technology that extends its applications to biomedical analytes. In this paper, a compact planar resonator-based sensor is introduced for noncontact sensing of glucose. Furthermore, in vivo and in-vitro tests using a microfluidic channel system and in clinical trial settings demonstrate its reliable operation. The proposed sensor offers real-time response and a high linear correlation (R2 ∼ 0.913) between the measured sensor response and the blood glucose level (GL). The sensor is also enhanced with machine learning to predict the variation of body glucose levels for non-diabetic and diabetic patients. This addition is instrumental in triggering preemptive measures in cases of unusual glucose level trends. In addition, it allows for the detection of common artifacts of the sensor as anomalies so that they can be removed from the measured data. The proposed system is designed to noninvasively monitor interstitial glucose levels in humans, introducing the opportunity to create a customized wearable apparatus with the ability to learn.

Perspectives in Wearable Systems in the Human-Robot Interaction (HRI) Field

Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human-machine interaction (HRI) field. However, HRI in complex clinical rehabilitation scenarios has further requirements for wearable sensor systems, which has aroused the interest of many researchers. However, the traditional wearable system has problems such as low integration, limited types of measurement data, and low accuracy, causing a gap with the actual needs of HRI. This paper will introduce the latest progress in the current wearable systems of HRI from four aspects. First of all, it introduces the breakthroughs of current research in system integration, which includes processing chips and flexible sensing modules to reduce the system's volume and increase battery life. After that, this paper reviews the latest progress of wearable systems in electrochemical measurement, which can extract single or multiple biomarkers from biological fluids such as sweat. In addition, the clinical application of non-invasive wearable systems is introduced, which solves the pain and discomfort problems caused by traditional clinical invasive measurement equipment. Finally, progress in the combination of current wearable systems and the latest machine-learning methods is shown, where higher accuracy and indirect acquisition of data that cannot be directly measured is achieved. From the evidence presented, we believe that the development trend of wearable systems in HRI is heading towards high integration, multi-electrochemical measurement data, and clinical and intelligent development.

Artificial intelligence enhanced sensors - enabling technologies to next-generation healthcare and biomedical platform

The fourth industrial revolution has led to the development and application of health monitoring sensors that are characterized by digitalization and intelligence. These sensors have extensive applications in medical care, personal health management, elderly care, sports, and other fields, providing people with more convenient and real-time health services. However, these sensors face limitations such as noise and drift, difficulty in extracting useful information from large amounts of data, and lack of feedback or control signals. The development of artificial intelligence has provided powerful tools and algorithms for data processing and analysis, enabling intelligent health monitoring, and achieving high-precision predictions and decisions. By integrating the Internet of Things, artificial intelligence, and health monitoring sensors, it becomes possible to realize a closed-loop system with the functions of real-time monitoring, data collection, online analysis, diagnosis, and treatment recommendations. This review focuses on the development of healthcare artificial sensors enhanced by intelligent technologies from the aspects of materials, device structure, system integration, and application scenarios. Specifically, this review first introduces the great advances in wearable sensors for monitoring respiration rate, heart rate, pulse, sweat, and tears; implantable sensors for cardiovascular care, nerve signal acquisition, and neurotransmitter monitoring; soft wearable electronics for precise therapy. Then, the recent advances in volatile organic compound detection are highlighted. Next, the current developments of human-machine interfaces, AI-enhanced multimode sensors, and AI-enhanced self-sustainable systems are reviewed. Last, a perspective on future directions for further research development is also provided. In summary, the fusion of artificial intelligence and artificial sensors will provide more intelligent, convenient, and secure services for next-generation healthcare and biomedical applications.

Revolutionizing Precision Medicine: Exploring Wearable Sensors for Therapeutic Drug Monitoring and Personalized Therapy

Precision medicine, particularly therapeutic drug monitoring (TDM), is essential for optimizing drug dosage and minimizing toxicity. However, current TDM methods have limitations, including the need for skilled operators, patient discomfort, and the inability to monitor dynamic drug level changes. In recent years, wearable sensors have emerged as a promising solution for drug monitoring. These sensors offer real-time and continuous measurement of drug concentrations in biofluids, enabling personalized medicine and reducing the risk of toxicity. This review provides an overview of drugs detectable by wearable sensors and explores biosensing technologies that can enable drug monitoring in the future. It presents a comparative analysis of multiple biosensing technologies and evaluates their strengths and limitations for integration into wearable detection systems. The promising capabilities of wearable sensors for real-time and continuous drug monitoring offer revolutionary advancements in diagnostic tools, supporting personalized medicine and optimal therapeutic effects. Wearable sensors are poised to become essential components of healthcare systems, catering to the diverse needs of patients and reducing healthcare costs.

A Voxel Vascular Structure-based Mannequin-like Arm Electromagnetic Model for Radio Frequency Biomedical Sensors

Radio Frequency (RF) sensor is widely used to monitor physiological signals. Generally, RF sensor simulation is mostly done using a layered model, which sometimes cannot model the accurate properties in the real world. A voxel vascular structure-based mannequin-like arm electromagnetic model (VVS-MaM) is proposed to evaluate the RF sensor, which mainly gathers the real physiological signal. This model is built with high-precision Magnetic Resonance Imaging (MRI), and it can finish fast simulation while there is also a voxel-like part in it which means it has the advantages of both the layered model and the real human model. After modelling, both simulation and in-vivo experiments are designed to test this sensor. In the simulation, the simulated standard resonant frequency of the equivalent model is 1.8137 GHz, and the relative error of the VVS-MaM is 0.012 GHz, which is closer to the standard value than the layer model result of 0.049 GHz. Meanwhile, in the in-vivo experiments, an RF sensor based on a composite right/left-handed transmission line (CRLH-TL) and complementary split resonator rings (CSRRs) are fabricated, and the measurements from the real experiments are gathered and stored to compare with that of the simulation. The comparison shows that the relative error of the VVS-MaM (0.08804 GHz)is closer to the in-vivo measurements than that of the layer model (0.09891 GHz), which validates the performance of VVS-MaM.Clinical Relevance-Radio Frequency, magnetic resonance imaging, scattering parameter, composite right/left-handed, complementary split resonator ring.

Wearable non-invasive glucose sensors based on metallic nanomaterials

The development of wearable non-invasive glucose sensors provides a convenient technical means to monitor the glucose concentration of diabetes patients without discomfortability and risk of infection. Apart from enzymes as typical catalytic materials, the active catalytic materials of the glucose sensor are mainly composed of polymers, metals, alloys, metal compounds, and various metals that can undergo catalytic oxidation with glucose. Among them, metallic nanomaterials are the optimal materials applied in the field of wearable non-invasive glucose sensing due to good biocompatibility, large specific surface area, high catalytic activity, and strong adsorption capacity. This review summarizes the metallic nanomaterials used in wearable non-invasive glucose sensors including zero-dimensional (0D), one-dimensional (1D), and two-dimensional (2D) monometallic nanomaterials, bimetallic nanomaterials, metal oxide nanomaterials, etc. Besides, the applications of wearable non-invasive biosensors based on these metallic nanomaterials towards glucose detection are summarized in detail and the development trend of the wearable non-invasive glucose sensors based on metallic nanomaterials is also outlook.

Dual quantum cascade lasers for noninvasive glucose detection using photoacoustic spectroscopy

The combination of mid-infrared and photoacoustic spectroscopy has shown promising developments as a substitute for invasive glucose detection technology. A dual single-wavelength quantum cascade laser system has been developed using photoacoustic spectroscopy for noninvasive glucose monitoring. Biomedical skin phantoms with similar properties to human skin have been prepared with blood components at different glucose concentrations as test models for the setup. The detection sensitivity of the system has been improved to ± 12.5 mg/dL in the hyperglycemia blood glucose ranges. An ensemble machine learning classifier has been developed to predict the glucose level in the presence of blood components. The model, which was trained with 72,360 unprocessed datasets, achieved a 96.7% prediction accuracy with 100% of the predicted data located in zones A and B of Clarke's error grid analysis. These findings fulfill both the US Food and Drug Administration and Health Canada requirements for glucose monitors.

Dielectric and Biological Characterization of Liver Tissue in a High-Fat Diet Mouse Model

Hepatic steatosis may be caused by type 2 diabetes or obesity and is one of the origins of chronic liver disease. A non-invasive technique based on microwave propagation can be a good solution to monitor hepatic tissue pathologies. The present work is devoted to the dielectric permittivity measurements in healthy and fatty liver in the microwave range. A mouse model following normal and high sugar/glucose (HFS) diets was used. We demonstrated the change in the triglyceride and glucose concentration in the hepatic tissue of HFS diet mice. The difference in the dielectric permittivity of healthy and fatty liver was observed in the range from 100 MHz to 2 GHz. The dielectric permittivity was found to be 42 in the healthy tissue and 31 in the fatty liver tissue at 1 GHz. The obtained results demonstrate that dielectric permittivity can be a sensitive tool to distinguish between healthy and fatty hepatic tissue.

Accurate Post-Calibration Predictions for Noninvasive Glucose Measurements in People Using Confocal Raman Spectroscopy

In diabetes prevention and care, invasiveness of glucose measurement impedes efficient therapy and hampers the identification of people at risk. Lack of calibration stability in non-invasive technology has confined the field to short-term proof of principle. Addressing this challenge, we demonstrate the first practical use of a Raman-based and portable non-invasive glucose monitoring device used for at least 15 days following calibration. In a home-based clinical study involving 160 subjects with diabetes, the largest of its kind to our knowledge, we find that the measurement accuracy is insensitive to age, sex, and skin color. A subset of subjects with type 2 diabetes highlights promising real-life results with 99.8% of measurements within A + B zones in the consensus error grid and a mean absolute relative difference of 14.3%. By overcoming the problem of calibration stability, we remove the lingering uncertainty about the practical use of non-invasive glucose monitoring, boding a new, non-invasive era in diabetes monitoring.

Fluorescence-Amplified Origami Microneedle Device for Quantitatively Monitoring Blood Glucose

Exploration of clinically acceptable blood glucose monitors has been engaging in the past decades, yet the ability to quantitatively detect blood glucose in a painless, accurate, and highly sensitive manner remains limited. Herein, a fluorescence-amplified origami microneedle (FAOM) device is described that integrates tubular DNA-origami nanostructures and glucose oxidase molecules into its inner network to quantitatively monitor blood glucose. The skin-attached FAOM device can collect glucose molecules in situ and transfer the input into a proton signal after the oxidase's catalysis. The proton-driven mechanical reconfiguration of DNA-origami tubes separates fluorescent molecules and their quenchers, eventually amplifying the glucose-correlated fluorescence signal. The function equation established on clinical examinees suggests that FAOM can report blood glucose in a highly sensitive and quantitative manner. In clinical blind tests, the FAOM achieves well-matched accuracy (98.70 ± 4.77%) compared with a commercial blood biochemical analyzer, fully meeting the requirements of accurate blood glucose monitoring. The FAOM device can be inserted into skin tissue in a trivially painful manner and with minimal leakage of DNA origami, substantially improving the tolerance and compliance of the blood glucose test.

Comparative assessment of blood glucose monitoring techniques: a review

Monitoring blood glucose levels is a vital indicator of diabetes mellitus management. The mainstream techniques of glucometers are invasive, painful, expensive, intermittent, and time-consuming. The ever-increasing number of global diabetic patients urges the development of alternative non-invasive glucose monitoring techniques. Recent advances in electrochemical biosensors, biomaterials, wearable sensors, biomedical signal processing, and microfabrication technologies have led to significant research and ideas in elevating the patient's life quality. This review provides up-to-date information about the available technologies and compares the advantages and limitations of invasive and non-invasive monitoring techniques. The scope of measuring glucose concentration in other bio-fluids such as interstitial fluid (ISF), tears, saliva, and sweat are also discussed. The high accuracy level of invasive methods in measuring blood glucose concentrations gives them superiority over other methods due to lower average absolute error between the detected glucose concentration and reference values. Whereas minimally invasive, and non-invasive techniques have the advantages of continuous and pain-free monitoring. Various blood glucose monitoring techniques have been evaluated based on their correlation to blood, patient-friendly, time efficiency, cost efficiency, and accuracy. Finally, this review also compares the currently available glucose monitoring devices in the market.

Pilot study in human healthy volunteers on the use of magnetohydrodynamics in needle-free continuous glucose monitoring

The benefits of continuous glucose monitoring (CGM) in diabetes management are extensively documented. Yet, the broader adoption of CGM systems is limited by their cost and invasiveness. Current CGM devices, requiring implantation or the use of hypodermic needles, fail to offer a convenient solution. We have demonstrated that magnetohydrodynamics (MHD) is effective at extracting dermal interstitial fluid (ISF) containing glucose, without the use of needles. Here we present the first study of ISF sampling with MHD for glucose monitoring in humans. We conducted 10 glucose tolerance tests on 5 healthy volunteers and obtained a significant correlation between the concentration of glucose in ISF samples extracted with MHD and capillary blood glucose samples. Upon calibration and time lag removal, the data indicate a Mean Absolute Relative Difference (MARD) of 12.9% and Precision Absolute Relative Difference of 13.1%. In view of these results, we discuss the potential value and limitations of MHD in needle-free glucose monitoring.

Subcutaneously implantable electromagnetic biosensor system for continuous glucose monitoring

Continuous glucose monitoring systems (CGMS) are becoming increasingly popular in diabetes management compared to conventional methods of self-blood glucose monitoring systems. They help understanding physiological responses towards nutrition intake, physical activities in everyday life and glucose control. CGMS available in market are of two types based on their working principle. Needle type systems with few weeks lifespan (e.g., enzyme-based Freestyle Libre) and implant type system (e.g., fluorescence-based Senseonics) with few months of lifespan are commercially available. An alternate to both working methods, herein, we propose electromagnetic-based sensor that can be subcutaneously implanted and capable of tracking minute changes in dielectric permittivity owing to changes in blood glucose level (BGL). Proof-of-concept of proposed electromagnetic-based implant sensor has been validated in intravenous glucose tolerance test (IVGTT) conducted on swine and beagle in a controlled environment. Sensor interface modules, mobile applications, and glucose mapping algorithms are also developed for continuous measurement in a freely moving beagle during oral glucose tolerance test (OGTT). The results of the short-term (1 h, IVGTT) and long-term (52 h, OGTT) test are summarized in this work. A close trend is observed between sensor frequency and BGL during GTT experiments on both animal species.

Wearable, wireless, multi-sensor device for monitoring tissue circulation after free-tissue transplantation: a multicentre clinical trial

Wearable sensors have seen remarkable recent technological developments, and their role in healthcare is expected to expand. Specifically, monitoring tissue circulation in patients who have undergone reconstructive surgery is critical because blood flow deficiencies must be rescued within hours or the transplant will fail due to thrombosis/haematoma within the artery or vein. We design a wearable, wireless, continuous, multipoint sensor to monitor tissue circulation. The system measures pulse waves, skin colour, and tissue temperature to reproduce physician assessment. Data are analysed in real time for patient risk using an algorithm. This multicentre clinical trial involved 73 patients who underwent transplant surgery and had their tissue circulation monitored until postoperative day 7. Herein, we show that the overall agreement rate between physician and sensor findings is 99.2%. In addition, the patient questionnaire results indicate that the device is easy to wear. The sensor demonstrates non-invasive, real-time, continuous, multi-point, wireless, and reliable monitoring for postoperative care. This wearable system can improve the success rate of reconstructive surgeries.

Wearable flexible body matched electromagnetic sensors for personalized non-invasive glucose monitoring

This work introduces novel body-matched, vasculature-inspired, quasi-antenna-arrays that act as electromagnetic sensors to instantaneously, continuously, and wirelessly sense glucose variations in the bloodstream. The proposed sensors are personalized, leverage electromagnetic waves, and are coupled with a custom machine-learning-based signal-processing module. These sensors are flexible, and embedded in wearable garments such as socks, which provide conformity to curved skin surfaces and movement resilience. The entire wearable system is calibrated against temperature, humidity, and movement resulting in high accuracy in glucose variations tracking. In-Vivo experiments on diabetic rats and pigs exhibit a 100% diagnostic accuracy over a wide range of glucose variations. Human trials on patients with diabetes and healthy individuals reveal a clinical accuracy of continuous glucose monitoring of 99.01% in twenty-eight subjects who underwent Oral Glucose Tolerance Tests. Hence, our approach ensures the continuous tracking of glucose variations from hypo-to-hyper glycemic levels with great fidelity.

Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection

Diabetes mellitus is characterized by elevated blood glucose levels, however patients with diabetes may also develop hypoglycemia due to treatment. There is an increasing demand for non-invasive blood glucose monitoring and trends detection amongst people with diabetes and healthy individuals, especially athletes. Wearable devices and non-invasive sensors for blood glucose monitoring have witnessed considerable advances. This review is an update on recent contributions utilizing novel sensing technologies over the past five years which include electrocardiogram, electromagnetic, bioimpedance, photoplethysmography, and acceleration measures as well as bodily fluid glucose sensors to monitor glucose and trend detection. We also review methods that use machine learning algorithms to predict blood glucose trends, especially for high risk events such as hypoglycemia. Convolutional and recurrent neural networks, support vector machines, and decision trees are examples of such machine learning algorithms. Finally, we address the key limitations and challenges of these studies and provide recommendations for future work.

Assessing the Potential of Wearable Health Monitors for Health System Strengthening in Low- and Middle-Income Countries: A Prospective Study of Technology Adoption in Cambodia

Wearable health monitors are a rapidly evolving technology that may offer new opportunities for strengthening health system responses to cardiovascular and other non-communicable diseases (NCDs) in low- and middle-income countries (LMICs). In light of this, we explored opportunities for, and potential challenges to, technology adoption in Cambodia, considering the complexity of contextual factors that may influence product uptake and sustainable health system integration. Data collection for this study involved in-depth interviews with national and international stakeholders and a literature review. The analytical approach was guided by concepts and categories derived from the non-adoption, abandonment, scale-up, spread, and sustainability (NASSS) framework—an evidence-based framework that was developed for studying health technology adoption and the challenges to scale-up, spread and sustainability of such technologies in health service organizations. Three potential applications of health wearables for the prevention and control of NCDs in Cambodia were identified: health promotion, follow-up and monitoring of patients and surveys of NCD risk factors. However, several challenges to technology adoption emerged across the research domains, associated with the intended adopters, the organization of the national health system, the wider infrastructure, the regulatory environment and the technology itself. Our findings indicate that, currently, wearables could be best used to conduct surveys of NCD risk factors in Cambodia and in other LMICs with similar health system profiles. In the future, a more integrated use of wearables to strengthen monitoring and management of patients could be envisaged, although this would require careful consideration of feasibility and organizational issues.

New Consumer Research Technology for Food Behaviour: Overview and Validity

BACKGROUND

the last decade has witnessed an explosion of new consumer behaviour research technology, and new methods are published almost monthly. To what extent are these methods applicable in the specific area of food consumer science, and if they are, are they any good?

METHODS

in this paper, we attempt to give an overview of the developments in this area. We distinguish between ('input') methods needed to shape the measurement context a consumer is brought in, e.g., by means of 'immersive' methods, and ('output') methods that perform measurements proper. Concerning the latter, we distinguish between methods focusing on neuro-science, on psychology, and on behaviour. In addition, we suggest a way to assess the validity of the methods, based on psychological theory, concerning biases resulting from consumer awareness of a measurement situation. The methods are evaluated on three summarising validity criteria; conclusions: the conclusion is that behavioural measures generally appear more valid than psychological or neuro-scientific methods. The main conclusion is that validity of a method should never be taken for granted, and it should be always be assessed in the context of the research question.

Skin Patchable Sensor Surveillance for Continuous Glucose Monitoring

Diabetes mellitus is a physiological and metabolic disorder affecting millions of people worldwide, associated with global morbidity, mortality, and financial expenses. Long-term complications can be avoided by frequent, continuous self-monitoring of blood glucose. Therefore, this review summarizes the current state-of-art glycemic control regimes involving measurement approaches and basic concepts. Following an introduction to the significance of continuous glucose sensing, we have tracked the evolution of glucose monitoring devices from minimally invasive to non-invasive methods to present an overview of the spectrum of continuous glucose monitoring (CGM) technologies. The conveniences, accuracy, and cost-effectiveness of the real-time CGM systems (rt-CGMs) are the factors considered for discussion. Transdermal biosensing and drug delivery routes have recently emerged as an innovative approach to substitute hypodermal needles. This work reviews skin-patchable glucose monitoring sensors for the first time, providing specifics of all the major findings in the past 6 years. Skin patch sensors and their progressive form, i.e., microneedle (MN) array sensory and delivery systems, are elaborated, covering self-powered, enzymatic, and non-enzymatic devices. The critical aspects reviewed are material design and assembly techniques focusing on flexibility, sensitivity, selectivity, biocompatibility, and user-end comfort. The review highlights the advantages of patchable MNs' multi-sensor technology designed to maintain precise blood glucose levels and administer diabetes drugs or insulin through a "sense and act" feedback loop. Subsequently, the limitations and potential challenges encountered from the MN array as rt-CGMs are listed. Furthermore, the current statuses of working prototype glucose-responsive "closed-loop" insulin delivery systems are discussed. Finally, the expected future developments and outlooks in clinical applications are discussed.

Remote Healthcare for Elderly People Using Wearables: A Review

The growth of health care spending on older adults with chronic diseases faces major concerns that require effective measures to be adopted worldwide. Among the main concerns is whether recent technological advances now offer the possibility of providing remote health care for the aging population. The benefits of suitable prevention and adequate monitoring of chronic diseases by using emerging technological paradigms such as wearable devices and the Internet of Things (IoT) can increase the detection rates of health risks to raise the quality of life for the elderly. Specifically, on the subject of remote health monitoring in older adults, a first approach is required to review devices, sensors, and wearables that serve as tools for obtaining and measuring physiological parameters in order to identify progress, limitations, and areas of opportunity in the development of health monitoring schemes. For these reasons, a review of articles on wearable devices was presented in the first instance to identify whether the selected articles addressed the needs of aged adults. Subsequently, the direct review of commercial and prototype wearable devices with the capability to read physiological parameters was presented to identify whether they are optimal or usable for health monitoring in older adults.

Permittivity-Inspired Microwave Resonator-Based Biosensor Based on Integrated Passive Device Technology for Glucose Identification

In this study, we propose a high-performance resonator-based biosensor for mediator-free glucose identification. The biosensor is characterized by an air-bridge capacitor and fabricated via integrated passive device technology on gallium arsenide (GaAs) substrate. The exterior design of the structure is a spiral inductor with the air-bridge providing a sensitive surface, whereas the internal capacitor improves indicator performance. The sensing relies on repolarization and rearrangement of surface molecules, which are excited by the dropped sample at the microcosmic level, and the resonance performance variation corresponds to the difference in glucose concentration at the macroscopic level. The air-bridge capacitor in the modeled RLC circuit serves as a bio-recognition element to glucose concentration (εglucoseC0), generating resonant frequency shifts at 0.874 GHz and 1.244 GHz for concentrations of 25 mg/dL and 300 mg/dL compared to DI water, respectively. The proposed biosensor exhibits excellent sensitivity at 1.38 MHz per mg/dL with a wide detection range for glucose concentrations of 25-300 mg/dL and a low detection limit of 24.59 mg/dL. Additionally, the frequency shift and concentration are highly linear with a coefficient of determination of 0.98823. The response time is less than 3 s. We performed multiple experiments to verify that the surface morphology reveals no deterioration and chemical binding, thus validating the reusability and reliability of the proposed biosensor.

Recent progress in the fabrication of flexible materials for wearable sensors

Wearable sensors have been widely studied because of their small size, light weight, and potential for the noninvasive tracking and monitoring of human physiological information. Wearable flexible sensors generally consist of two parts: a flexible substrate in contact with the skin and a signal processing module. At present, wearable electronics cover many fields, such as machinery, physics, chemistry, materials science, and biomedicine. The design concept and selection of materials are very important to the function of a sensor. In this review, we summarize the latest developments in flexible materials for wearable sensors, including developments in flexible materials, electrode materials, and new flexible biodegradable materials, and describe the important role of innovation in material and sensor design in the development of wearable flexible sensors. Strategies and challenges related to the improvement of the performances of wearable flexible sensors, as well as the development prospects of wearable devices based on flexible materials, are also discussed.

Recent Progress in Intelligent Wearable Sensors for Health Monitoring and Wound Healing Based on Biofluids

The intelligent wearable sensors promote the transformation of the health care from a traditional hospital-centered model to a personal portable device-centered model. There is an urgent need of real-time, multi-functional, and personalized monitoring of various biochemical target substances and signals based on the intelligent wearable sensors for health monitoring, especially wound healing. Under this background, this review article first reviews the outstanding progress in the development of intelligent, wearable sensors designed for continuous, real-time analysis, and monitoring of sweat, blood, interstitial fluid, tears, wound fluid, etc. Second, this paper reports the advanced status of intelligent wound monitoring sensors designed for wound diagnosis and treatment. The paper highlights some smart sensors to monitor target analytes in various wounds. Finally, this paper makes conservative recommendations regarding future development of intelligent wearable sensors.

Trending Technology of Glucose Monitoring during COVID-19 Pandemic: Challenges in Personalized Healthcare

The COVID-19 pandemic has continued to spread rapidly, and patients with diabetes are at risk of experiencing rapid progression and poor prognosis for appropriate treatment. Continuous glucose monitoring (CGM), which includes accurately tracking fluctuations in glucose levels without raising the risk of coronavirus exposure, becomes an important strategy for the self-management of diabetes during this pandemic, efficiently contributing to the diabetes care and the fight against COVID-19. Despite being less accurate than direct blood glucose monitoring, wearable noninvasive systems can encourage patient adherence by guaranteeing reliable results through high correlation between blood glucose levels and glucose concentrations in various other biofluids. This review highlights the trending technologies of glucose sensors during the ongoing COVID-19 pandemic (2019-2020) that have been developed to make a significant contribution to effective management of diabetes and prevention of coronavirus spread, from off-body systems to wearable on-body CGM devices, including nanostructure and sensor performance in various biofluids. The advantages and disadvantages of various human biofluids for use in glucose sensors are also discussed. Furthermore, the challenges faced by wearable CGM sensors with respect to personalized healthcare during and after the pandemic are deliberated to emphasize the potential future directions of CGM devices for diabetes management.

Low dimensional materials for glucose sensing

Biosensors are essential components for effective healthcare management. Since biological processes occur on molecular scales, nanomaterials and nanosensors intrinsically provide the most appropriate landscapes for developing biosensors. Low-dimensional materials have the advantage of offering high surface areas, increased reactivity and unique physicochemical properties for efficient and selective biosensing. So far, nanomaterials and nanodevices have offered significant prospects for glucose sensing. Targeted glucose biosensing using such low-dimensional materials enables much more effective monitoring of blood glucose levels, thus providing significantly better predictive diabetes diagnostics and management. In this review, recent advances in using low dimensional materials for sensing glucose are summarized. Sensing fundamentals are discussed, as well as invasive, minimally-invasive and non-invasive sensing methods. The effects of morphological characteristics and size-dependent properties of low dimensional materials are explored for glucose sensing, and the key performance parameters such as selectivity, stability and sensitivity are also discussed. Finally, the challenges and future opportunities that low dimensional materials can offer for glucose sensing are outlined.

Smart-watch-programmed green-light-operated percutaneous control of therapeutic transgenes

Wearable smart electronic devices, such as smart watches, are generally equipped with green-light-emitting diodes, which are used for photoplethysmography to monitor a panoply of physical health parameters. Here, we present a traceless, green-light-operated, smart-watch-controlled mammalian gene switch (Glow Control), composed of an engineered membrane-tethered green-light-sensitive cobalamin-binding domain of Thermus thermophilus (TtCBD) CarH protein in combination with a synthetic cytosolic TtCBD-transactivator fusion protein, which manage translocation of TtCBD-transactivator into the nucleus to trigger expression of transgenes upon illumination. We show that Apple-Watch-programmed percutaneous remote control of implanted Glow-controlled engineered human cells can effectively treat experimental type-2 diabetes by producing and releasing human glucagon-like peptide-1 on demand. Directly interfacing wearable smart electronic devices with therapeutic gene expression will advance next-generation personalized therapies by linking biopharmaceutical interventions to the internet of things.

Enhancing the Accuracy of Non-Invasive Glucose Sensing in Aqueous Solutions Using Combined Millimeter Wave and Near Infrared Transmission

We reported measurement results relating to non-invasive glucose sensing using a novel multiwavelength approach that combines radio frequency and near infrared signals in transmission through aqueous glucose-loaded solutions. Data were collected simultaneously in the 37–39 GHz and 900–1800 nm electromagnetic bands. We successfully detected changes in the glucose solutions with varying glucose concentrations between 80 and 5000 mg/dl. The measurements showed for the first time that, compared to single modality systems, greater accuracy on glucose level prediction can be achieved when combining transmission data from these distinct electromagnetic bands, boosted by machine learning algorithms.

Glucose Level Sensing Using Single Asymmetric Split Ring Resonator

In this article, a biosensor composed of a single metamaterial asymmetric resonator is specifically designed for sensing the glucose level of 1 µL of solution. The resonator has two gaps, and one of them ends with a semicircle shape on which the glucose solution is placed. This design helps in confining the drops of glucose solutions in a specific area where the field is maximally confined in order to enhance the electromagnetic wave-matter interaction. Six samples of glucose solutions with concentrations that cover hypoglycemia, normal and hyperglycemia conditions that vary from around 41 to 312 mg/dL were prepared and examined by this biosensor. The resonance frequency redshift was used as a measure of the changes in the glucose level of the solutions. Without glucose solution, an excellent agreement between the measured and simulated transmission amplitude was observed. The increase in glucose concentrations exhibited clear and noticeable redshifts in the resonance frequency. This biosensor revealed a 0.9997 coefficient of determination, which implies an excellent prediction fitting model. More importantly, a sensitivity of 438 kHz/(mg/dL) was observed over the range of concentrations of the aqueous solution.

Flexible Electronics and Healthcare Applications

Flexible electronics has attracted tremendous attention in recent years. The essential requirements for flexible electronics include excellent electrical properties, flexibility and stretchability. By introducing special structures or using flexible materials, electronic devices can be given excellent flexibility and stretchability. In this paper we review the realization of flexible electronics from the perspective of structural design strategies and materials; then, healthcare application of flexible electronic systems was introduced. Finally, a brief summary and outlook are presented.

From Diagnosis to Treatment: Recent Advances in Patient-Friendly Biosensors and Implantable Devices

Patient-friendly medical diagnostics and treatments have been receiving a great deal of interest due to their rapid and cost-effective health care applications with minimized risk of infection, which has the potential to replace conventional hospital-based medical procedures. In particular, the integration of recently developed materials into health care devices allows the rapid development of point-of-care (POC) sensing platforms and implantable devices with special functionalities. In this review, the recent advances in biosensors for patient-friendly diagnosis and implantable devices for patient-friendly treatment are discussed. Comprehensive analysis of portable and wearable biosensing platforms for patient-friendly health monitoring and disease diagnosis is provided, including topics such as materials selection, device structure and integration, and biomarker detection strategies. Moreover, specific challenges related to each biological fluid for wearable biosensor-based POC applications are presented. Also, advances in implantable devices, including recent materials development and wireless communication strategies, are discussed. Furthermore, various patient-friendly surgical and treatment approaches are reviewed, such as minimally invasive insertion and mounting, in vivo electrical and optical modulations, and post-operation health monitoring. Finally, the challenges and future perspectives toward the development of the patient-friendly diagnosis and treatment are provided.

Smartphone-Addressable 3D-Printed Electrochemical Ring for Nonenzymatic Self-Monitoring of Glucose in Human Sweat

Nowadays, there is increased demand for wearable sensors for sweat glucose monitoring in order to facilitate diabetes management in a patient-friendly and noninvasive manner. This work describes a wearable glucose monitoring device in the form of an electrochemical ring (e-ring) fabricated by 3D printing. The 3D-printed e-ring consists of three carbon-based plastic electrodes (fabricated using a conductive filament) integrated at the inner side of a ring-shaped flexible plastic holder (fabricated using a nonconductive filament). The e-ring is modified with an electrodeposited gold film and is coupled to a miniature potentiostat directly addressable by a smartphone, offering the possibility for nonenzymatic amperometric self-testing of glucose levels in human sweat. Optical and electrochemical techniques are employed for the characterization of the e-ring. The device is resistant to mechanical bending and enables noninvasive glucose detection in sweat in the physiologically relevant concentration range of 12.5-400 μmol L^-1 without interference from common electroactive metabolites. The 3D-printed e-ring bridges the gap between the existing fabrication/sensing technologies and the desired operational features for glucose self-monitoring and may be employed as a paradigm of in-house fabricated wearable sensors.

Proof of Concept for a New Raman-Based Prototype for Noninvasive Glucose Monitoring

BACKGROUND

Noninvasive glucose monitoring (NIGM) in diabetes is a long-sought-for technology. Among the many attempts Raman spectroscopy was considered as the most promising because of its glucose specificity. In this study, a recently developed prototype (GlucoBeam, RSP Systems A/S, Denmark) was tested in patients with type 1 diabetes to establish calibration models and to demonstrate proof of concept for this device in real use.

METHODS

The NIGM table-top prototype was used by 15 adult subjects with type 1 diabetes for up to 25 days at home and in an in-clinic setting. On each day, the subjects performed at least six measurement units throughout the day. Each measurement unit comprised two capillary blood glucose measurements, two scans with an intermittent scanning continuous glucose monitoring (CGM) system, and two NIGM measurements using the thenar of the subject's right hand.

RESULTS

Calibration models were established using data from 19 to 24 days. The remaining 3-8 days were used for independent validation. The mean absolute relative difference of the NIGM prototype was 23.6% ± 13.1% for the outpatient days, 28.2% ± 9.9% for the in-clinic day, and 26.3% ± 10.8% for the complete study. Consensus error grid analysis of the NIGM prototype for the complete study showed 93.6% of values in clinically acceptable zones A and B.

CONCLUSIONS

This proof of concept study demonstrated a practical realization of a Raman-based NIGM device, with performance on par with early-generation CGM systems. The findings will assist in further performance improvements of the device.