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

Next-Generation Potentiometric Sensors: A Review of Flexible and Wearable Technologies

In recent years, the field of wearable sensors has undergone significant evolution, emerging as a pivotal topic of research due to the capacity of such sensors to gather physiological data during various human activities. Transitioning from basic fitness trackers, these sensors are continuously being improved, with the ultimate objective to make compact, sophisticated, highly integrated, and adaptable multi-functional devices that seamlessly connect to clothing or the body, and continuously monitor bodily signals without impeding the wearer's comfort or well-being. Potentiometric sensors, leveraging a range of different solid contact materials, have emerged as a preferred choice for wearable chemical or biological sensors. Nanomaterials play a pivotal role, offering unique properties, such as high conductivity and surface-to-volume ratios. This article provides a review of recent advancements in wearable potentiometric sensors utilizing various solid contacts, with a particular emphasis on nanomaterials. These sensors are employed for precise ion concentration determinations, notably sodium, potassium, calcium, magnesium, ammonium, and chloride, in human biological fluids. This review highlights two primary applications, that is, (1) the enhancement of athletic performance by continuous monitoring of ion levels in sweat to gauge the athlete's health status, and (2) the facilitation of clinical diagnosis and preventive healthcare by monitoring the health status of patients, in particular to detect early signs of dehydration, fatigue, and muscle spasms.

Knowledge, Attitudes, and Practices of Chronic Type 2 Diabetes Patients in China Toward Continuous Glucose Monitoring: An Online Questionnaire Survey

Purpose

Investigate the knowledge, attitude, and practices (KAP) of type 2 diabetes patients regarding continuous glucose monitoring (CGM).

Methods

A cross-sectional study was undertaken at the First People's Hospital of Jiujiang City from Sep 20, 2023, to Dec 10, 2023.

Results

A total of 633 patients with type 2 diabetes mellitus accessed the questionnaire link. Of these, 544 patients completed the questionnaires. After data cleaning, 493 questionnaires were included in the analysis, resulting in a response rate of 86% and an effective rate of 91%. Among the 493 participants, 66.9% were male, and 70.8% reported using continuous glucose monitoring (CGM). Median scores: knowledge 17 (14, 26), attitude 34 (32, 40), and practice 20 (17, 24). Positive correlations existed between knowledge and attitude (r = 0.562, P < 0.001), knowledge and practice (r = 0.653, P < 0.001), and attitude and practice (r = 0.661, P < 0.001). Logistic regression revealed that being male, participating in diabetes education, and possessing higher knowledge and attitude scores were independently associated with positive practices. Structural equation model (SEM) showed knowledge directly influenced attitude (β = 0.538, P = 0.010) and practice (β = 0.433, P = 0.010), while attitude directly influenced practice (β = 0.450, P = 0.010). Knowledge indirectly impacted practice through its influence on attitude (β = 0.242, P = 0.010).

Conclusion

Type 2 diabetes patients exhibited insufficient knowledge but positive attitudes and practices toward CGM. Recommends educational interventions to enhance knowledge, potentially improving CGM utilization and outcomes in this population. Regular and comprehensive diabetes education should be integrated into routine clinical practice to optimize self-management and overall patient outcomes.

Advancements in electrochemical glucose sensors

The development of electrochemical glucose sensors with high sensitivity, specificity, and stability, enabling real-time continuous monitoring, has posed a significant challenge. However, an opportunity exists to fabricate electrochemical glucose biosensors with optimal performance through innovative device structures and surface modification materials. This paper provides a comprehensive review of recent advances in electrochemical glucose sensors. Novel classes of nanomaterials-including metal nanoparticles, carbon-based nanomaterials, and metal-organic frameworks-with excellent electronic conductivity and high specific surface areas, have increased the availability of reactive sites to improved contact with glucose molecules. Furthermore, in line with the trend in electrochemical glucose sensor development, research progress concerning their utilisation with sweat, tears, saliva, and interstitial fluid is described. To facilitate the commercialisation of these sensors, further enhancements in biocompatibility and stability are required. Finally, the characteristics of the ideal electrochemical glucose sensor are described and the developmental trends in this field are outlines.

Thermal Transfer Printed Flexible and Wearable Bionic Skin with Bilayer Nanofiber for Comfortable Multimodal Health Management

The advent of bionic skin sensors represents a significant leap forward in the realm of wearable health monitoring technologies. Existing bionic skin technologies face several limitations, including complex and expensive manufacturing processes, low wearing comfort, and challenges in achieving comfortable real-time health monitoring. These shortcomings hinder the widespread adoption and practical utility of bionic skin in various applications. The bionic skin invention presented in this article addresses these issues by introducing a novel thermal transfer manufacturing process that is low-cost and easy to operate. This method is particularly suitable for the small-scale mass production required for bionic skin applications. Additionally, the innovative bilayer unidirectional moisture transport nanomembrane incorporated into the bionic skin offers high extensibility and breathability. This feature enhances the ability of the skin to absorb sweat, thereby facilitating comfortable real-time health monitoring. The specially designed bionic skin sensor embedded within this system can monitor various biomarkers in sweat, including glucose, lactic acid, uric acid, pH, temperature, and skin impedance. When combined with the CARE(Continuous Analyte Monitoring with Real-time Engagement) system, it enables real-time data transmission and processing, offering a comprehensive approach to health monitoring that is both comfortable and reliable.

Technological advancements in glucose monitoring and artificial pancreas systems for shaping diabetes care

The management of diabetes mellitus has undergone remarkable progress with the introduction of cutting-edge technologies in glucose monitoring and artificial pancreas systems. These innovations have revolutionized diabetes care, offering patients more precise, convenient, and personalized management solutions that significantly improve their quality of life. This review aims to provide a comprehensive overview of recent technological advancements in glucose monitoring devices and artificial pancreas systems, focusing on their transformative impact on diabetes care. A detailed review of the literature was conducted to examine the evolution of glucose monitoring technologies, from traditional invasive methods to more advanced systems. The review explores minimally invasive techniques such as continuous glucose monitoring (CGM) systems and flash glucose monitoring (FGM) systems, which have already been proven to enhance glycemic control and reduce the risk of hypoglycemia. In addition, emerging non-invasive glucose monitoring technologies, including optical, electrochemical, and electro-mechanical methods, were evaluated. These techniques are paving the way for more patient-friendly options that eliminate the need for frequent finger-prick tests, thereby improving adherence and ease of use. Advancements in closed-loop artificial pancreas systems, which integrate CGM with automated insulin delivery, were also examined. These systems, often referred to as "hybrid closed-loop" or "automated insulin delivery" systems, represent a significant leap forward in diabetes care by automating the process of insulin dosing. Such advancements aim to mimic the natural function of the pancreas, allowing for better glucose regulation without the constant need for manual interventions by the patient. Technological breakthroughs in glucose monitoring and artificial pancreas systems have had a profound impact on diabetes management, providing patients with more accurate, reliable, and individualized treatment options. These innovations hold the potential to significantly improve glycemic control, reduce the incidence of diabetes-related complications, and ultimately enhance the quality of life for individuals living with diabetes. Researchers are continually exploring novel methods to measure glucose more effectively and with greater convenience, further refining the future of diabetes care. Researchers are also investigating the integration of artificial intelligence and machine learning algorithms to further enhance the precision and predictive capabilities of glucose monitoring and insulin delivery systems. With ongoing advancements in sensor technology, connectivity, and data analytics, the future of diabetes care promises to deliver even more seamless, real-time management, empowering patients with greater autonomy and improved health outcomes.

Additively manufactured microwave sensor for glucose level detection in saliva

In this paper, a novel realization of an ink-on-glass microwave sensor for biomedical applications is proposed. The Aerosol Jet Printing (AJP) technology is leveraged to implement a compact single-layer coplanar waveguide sensor featuring arc-shaped interdigital fingers that can accommodate a droplet of the Material-Under-Test (MUT). Such geometry provides a high sensitivity to even a very small deviation of MUT`s electrical properties when placed as a superstrate. An application towards the detection of trace amounts of glucose in saliva, which is a biomarker for diabetes, is showcased. The design and fabrication process of an exemplary sensor is discussed in detail. A circular geometry feature is introduced that helps a droplet to lie over the sensitive region due to wettability difference of glass substrate and silver ink. Sensor operating in K-band is developed providing a tradeoff between circuit size and droplet volume. The study is conducted for an artificial saliva requiring roughly a 0.5 µL droplet where changes in mixture content are proportional to relative changes of sensor`s transmission coefficient in a broad frequency range for occupied vs. empty states. The obtained results show that 10 mg of glucose per 100 ml of saliva can be easily distinguished in a frequency range of 20-30 GHz, whereas a monotonical change is visible for frequencies 20-26 GHz, which indicates the applicability of this sensor towards the detection of saliva-glucose levels and potential application in the detection of small amounts of other substances in liquids.

Surface-modified CMOS biosensors

Biosensors translate biological events into electronic signals that quantify biological processes. They are increasingly used in in vitro diagnostics applications that leverage their ability to process small sample volumes. One recent trend has been to integrate biosensors with complementary metal-oxide-semiconductor (CMOS) chips to provide enhanced miniaturization, parallel sensing, and low power consumption at a low cost. CMOS-enabled biosensors are used in monitoring DNA hybridization, enzymatic reactions, and cell proliferation, to name a few applications. This paper explores the materials and processes used in emerging CMOS biosensors. We discuss subtractive and additive processes for creating electrodes for electrochemical sensing applications. We discuss functionalization techniques for creating bioelectronic interfaces that allow molecular events to be transduced into the electrical domain using a plurality of modalities that are readily provided by CMOS chips. Example modalities featured are optical sensing, electrochemical detection, electrical detection, magnetic sensing, and mechanical sensing.

ZnFe(PBA)@Ti3C2Tx nanohybrid-based highly sensitive non-enzymatic electrochemical sensor for the detection of glucose in human sweat

The ZnFe prussian blue analogue [ZnFe(PBA)] was infused with Ti3C2Tx (MXene) denoted as ZnFe(PBA)@Ti3C2Tx and was prepared by an in-situ sonication method to use as a non-enzymatic screen printed electrode sensor. The advantage of non-enzymatic sensors is their excellent sensitivity, rapid detection, low cost and simple design. The synthesized ZnFe(PBA)@Ti3C2Tx was characterized for its physical and chemical characterization by XRD, Raman, XPS, EDAX, and FESEM analysis. It possessed multiple functionalized layers and a cubic structure in the nanohybrid. Further, the sensor was investigated by using electroanalytical studies such as cyclic voltammetry and chronoamperometry analysis. The enhanced surface area with a cubic structure of ZnFe(PBA) and the excellent electrical response of Ti3C2 nanosheet support the advancement of a non-enzymatic electrochemical glucose sensor with improved sensitivity of 973.42 µA mM-1 cm-2 with the limit of detection (LOD) of 3.036 µM (S/N = 3) and linear detection range (LDR) from 0.01 to 1 mM.

Metal Organic Frameworks Based Wearable and Point-of-Care Electrochemical Sensors for Healthcare Monitoring

The modern healthcare system strives to provide patients with more comfortable and less invasive experiences, focusing on noninvasive and painless diagnostic and treatment methods. A key priority is the early diagnosis of life-threatening diseases, which can significantly improve patient outcomes by enabling treatment at earlier stages. While most patients must undergo diagnostic procedures before beginning treatment, many existing methods are invasive, time-consuming, and inconvenient. To address these challenges, electrochemical-based wearable and point-of-care (PoC) sensing devices have emerged, playing a crucial role in the noninvasive, continuous, periodic, and remote monitoring of key biomarkers. Due to their numerous advantages, several wearable and PoC devices have been developed. In this focused review, we explore the advancements in metal-organic frameworks (MOFs)-based wearable and PoC devices. MOFs are porous crystalline materials that are cost-effective, biocompatible, and can be synthesized sustainably on a large scale, making them promising candidates for sensor development. However, research on MOF-based wearable and PoC sensors remains limited, and no comprehensive review has yet to synthesize the existing knowledge in this area. This review aims to fill that gap by emphasizing the design of materials, fabrication methodologies, sensing mechanisms, device construction, and real-world applicability of these sensors. Additionally, we underscore the importance and potential of MOF-based wearable and PoC sensors for advancing healthcare technologies. In conclusion, this review sheds light on the current state of the art, the challenges faced, and the opportunities ahead in MOF-based wearable and PoC sensing technologies.

Digital health and wearable devices for retinal disease monitoring

Digital health is wielding a growing influence across all areas of healthcare, encompassing various facets such as telemedicine, artificial intelligence (AI), and electronic healthcare records. In Ophthalmology, digital health innovations can be broadly divided into four categories: (i) self-monitoring home devices and apps, (ii) virtual and augmented reality visual aids, (iii) AI software, and (iv) wearables. Wearable devices can work in the background, collecting large amounts of objective data while we do our day-to-day activities, which may be ecologically more valid and meaningful to patients than that acquired in traditional hospital settings. They can be a watch, wristband, piece of clothing, glasses, cane, smartphone in our pocket, earphones, or any other device with a sensor that we carry with us. Focusing on retinal diseases, a key challenge in developing novel therapeutics has been to prove a meaningful benefit in patients' lives and the creation of objective patient-centred endpoints in clinical trials. In this review, we will discuss wearable devices collecting different aspects of visual behaviour, visual field, central vision, and functional vision, as well as their potential implementation as outcome measures in research/clinical trial settings. The healthcare landscape is facing a paradigm shift. Clinicians have a key role of collaborating with the development and fine-tuning of digital health innovations, as well as identifying opportunities where they can be leveraged to enhance our understanding of retinal diseases and improve patient outcomes.

Calibration algorithms for continuous glucose monitoring systems based on interstitial fluid sensing

Continuous glucose monitoring (CGM) is of great importance to the treatment and prevention of diabetes. As a proven commercial technology, electrochemical glucose sensor based on interstitial fluid (ISF) sensing has high sensitivity and wide detection range. Therefore, it has good promotion prospects in noninvasive or minimally-invasive CGM system. However, since there are concentration differences and time lag between glucose in plasma and ISF, the accuracy of this type of sensors are still limited. Typical calibration algorithms rely on simple linear regression which do not account for the variability of the sensitivity of sensors. To enhance the accuracy and stability of CGM based on ISF, optimization of calibration algorithm for sensors is indispensable. While there have been considerable researches on improving calibration algorithms for CGM, they have still received less attention. This article reviews the problem of typical calibration and presents the outstanding calibration algorithms in recent years. Finally, combined with existing research and emerging sensing technologies, this paper makes an outlook on the future calibration algorithms for CGM sensors.

Optical Image Sensors for Smart Analytical Chemiluminescence Biosensors

Optical biosensors have emerged as a powerful tool in analytical biochemistry, offering high sensitivity and specificity in the detection of various biomolecules. This article explores the advancements in the integration of optical biosensors with microfluidic technologies, creating lab-on-a-chip (LOC) platforms that enable rapid, efficient, and miniaturized analysis at the point of need. These LOC platforms leverage optical phenomena such as chemiluminescence and electrochemiluminescence to achieve real-time detection and quantification of analytes, making them ideal for applications in medical diagnostics, environmental monitoring, and food safety. Various optical detectors used for detecting chemiluminescence are reviewed, including single-point detectors such as photomultiplier tubes (PMT) and avalanche photodiodes (APD), and pixelated detectors such as charge-coupled devices (CCD) and complementary metal-oxide-semiconductor (CMOS) sensors. A significant advancement discussed in this review is the integration of optical biosensors with pixelated image sensors, particularly CMOS image sensors. These sensors provide numerous advantages over traditional single-point detectors, including high-resolution imaging, spatially resolved measurements, and the ability to simultaneously detect multiple analytes. Their compact size, low power consumption, and cost-effectiveness further enhance their suitability for portable and point-of-care diagnostic devices. In the future, the integration of machine learning algorithms with these technologies promises to enhance data analysis and interpretation, driving the development of more sophisticated, efficient, and accessible diagnostic tools for diverse applications.

Optical blood glucose non-invasive detection and its research progress

Blood glucose concentration is an important index for the diagnosis of diabetes, its self-monitoring technology is the method for scientific diabetes management. Currently, the typical household blood glucose meters have achieved great success in diabetes management, but they are discrete detection methods, and involve invasive blood sampling procedures. Optical detection technologies, which use the physical properties of light to detect the glucose concentration in body fluids non-invasively, have shown great potential in non-invasive blood glucose detection. This article summarized and analyzed the basic principles, research status, existing problems, and application prospects of different optical glucose detection technologies. In addition, this article also discusses the problems of optical detection technology in wearable sensors and perspectives on the future of non-invasive blood glucose detection technology to improve blood glucose monitoring in diabetic patients.

Shape-Specific Gold Nanoparticles for Multiplex Biosensing Applications

The biosensing field faces a significant challenge in efficiently detecting multiple analytes in a single diagnostic sample in order to compete with other established multiplex molecular diagnostic technologies such as PCR and ELISA. In response, we have developed a colorimetric nanobiosensor based on multiple morphological forms of functionalized gold nanoparticles (AuNPs) for the simultaneous detection of the influenza virus and SARS-CoV-2 virus. Gold nanospheres (GNSp) were modified with oligonucleotides specific for the influenza A virus, while gold nanoshells (GNSh) were modified with oligonucleotides specific for the SARS-CoV-2 virus. In the presence of their respective targets, AuNPs remain stable due to DNA-DNA interactions; conversely, in the absence of targets, AuNPs aggregate. Consequently, the hybrid system exhibits an indigo color with the SARS-CoV-2 target, a blue color with the Influenza A target, and a purple color with both targets, visible to the naked eye. Analytical sensitivity was 100 nM, and no cross-reactivity was observed with potentially confounding pathogens. This approach holds great promise for the simultaneous identification of multiple pathogens in a rapid manner without the need for equipment or trained personnel.

Recent advances in biosensors based on metal-oxide semiconductors system-integrated into bioelectronics

Metal-oxide semiconductors (MOSs) have emerged as pivotal components in technology related to biosensors and bioelectronics. Detecting biomarkers in sweat provides a glimpse into an individual's metabolism without the need for sample preparation or collection steps. The distinctive attributes of this biosensing technology position it as an appealing option for biomedical applications beyond the scope of diagnosis and healthcare monitoring. This review encapsulates ongoing developments of cutting-edge biosensors based on MOSs. Recent advances in MOS-based biosensors for human sweat analyses are reviewed. Also discussed is the progress in sweat-based biosensing technologies to detect and monitor diseases. Next, system integration of biosensors is demonstrated ultimately to ensure the accurate and reliable detection and analysis of target biomarkers beyond individual devices. Finally, the challenges and opportunities related to advanced biosensors and bioelectronics for biomedical applications are discussed.

Evaluation of sweat-based biomarkers using wearable biosensors for monitoring stress and fatigue: a systematic review

Objectives. This systematic review aims to report the evaluation of wearable biosensors for the real-time measurement of stress and fatigue using sweat biomarkers. Methods. A thorough search of the literature was carried out in databases such as PubMed, Web of Science and IEEE. A three-step approach for selecting research articles was developed and implemented. Results. Based on a systematic search, a total of 17 articles were included in this review. Lactate, cortisol, glucose and electrolytes were identified as sweat biomarkers. Sweat-based biomarkers are frequently monitored in real time using potentiometric and amperometric biosensors. Wearable biosensors such as an epidermal patch or a sweatband have been widely validated in scientific literature. Conclusions. Sweat is an important biofluid for monitoring general health, including stress and fatigue. It is becoming increasingly common to use biosensors that can measure a wide range of sweat biomarkers to detect fatigue during high-intensity work. Even though wearable biosensors have been validated for monitoring various sweat biomarkers, such biomarkers can only be used to assess stress and fatigue indirectly. In general, this study may serve as a driving force for academics and practitioners to broaden the use of wearable biosensors for the real-time assessment of stress and fatigue.

Bridging the Gap: A Literature Review of Advancements in Obesity and Diabetes Mellitus Management

This literature review explores advancements in obesity and diabetes mellitus diagnosis and treatment, highlighting recent innovations that promise more personalized and effective healthcare interventions. For obesity diagnosis, traditional methods like body mass index (BMI) calculations are now complemented by bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) scans, with emerging biomarkers from “omics” technologies. Diabetes diagnosis has advanced with standard hemoglobin A1c (HbA1c) testing supplemented by novel measures such as advanced glycation end products (AGEs) and autoantibodies, alongside the use of artificial intelligence to enhance diagnostic accuracy. Treatment options for obesity are expanding beyond traditional methods. Minimally invasive bariatric surgeries, endoscopic procedures, fecal microbiota transplants (FMTs), and pharmaceuticals like GLP-1 receptor agonists (semaglutide, tirzepatide) show promising results. Cognitive behavioral therapy (CBT) and prescription digital therapeutics (PDTs) are also valuable tools for weight management. Diabetes treatment is also undergoing a transformation. Ultra-long-acting insulins and innovative oral insulin delivery methods are on the horizon. SGLT2 inhibitors and GLP-1 receptor agonists are proving to be effective medications for blood sugar control. Continuous glucose monitoring (CGM) systems and closed-loop insulin delivery are revolutionizing diabetes management, while stem cell therapy holds promise for the future. By integrating advanced diagnostic tools with personalized treatment plans, obesity and diabetes care are entering a new era. This personalized approach empowers patients and paves the way for improved health outcomes and a better quality of life.

DEMIGOD: A Low-Cost Microcontroller-Based Closed-Loop System Integrating Nanoengineered Sweat-Based Glucose Monitoring and Controlled Transdermal Nanoemulsion Release of Hypoglycemic Treatment with a Software Application for Noninvasive Personalized Diabetes Care

This study endeavored to design and develop an innovative closed-loop diagnostic and therapeutic system with the following objectives: (a) the noninvasive detection of glucose concentration in sweat utilizing nanonengineered screen-printed biosensors; (b) the management of measured data through a specialized computer system comprising both hardware and software components, thereby enabling the precise control of therapeutic responses via a patch-based nanomedicine delivery system. This initiative addresses the significant challenges inherent in the management of diabetes mellitus, including the imperative need for glucose-level monitoring to optimize glycemic control. Leveraging chronoamperometric results as a foundational dataset and the in vivo hypoglycemic activity of nanoemulsion formulations, this research underscores the efficacy and accuracy of glucose concentration estimation, decision-making mechanism responses, and transdermal hypoglycemic treatment effects, within the proposed system.

Cleanroom-Free Direct Laser Micropatterning of Polymers for Organic Electrochemical Transistors in Logic Circuits and Glucose Biosensors

Organic electrochemical transistors (OECTs) are promising devices for bioelectronics, such as biosensors. However, current cleanroom-based microfabrication of OECTs hinders fast prototyping and widespread adoption of this technology for low-volume, low-cost applications. To address this limitation, a versatile and scalable approach for ultrafast laser microfabrication of OECTs is herein reported, where a femtosecond laser to pattern insulating polymers (such as parylene C or polyimide) is first used, exposing the underlying metal electrodes serving as transistor terminals (source, drain, or gate). After the first patterning step, conducting polymers, such as poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), or semiconducting polymers, are spin-coated on the device surface. Another femtosecond laser patterning step subsequently defines the active polymer area contributing to the OECT performance by disconnecting the channel and gate from the surrounding spin-coated film. The effective OECT width can be defined with high resolution (down to 2 µm) in less than a second of exposure. Micropatterning the OECT channel area significantly improved the transistor switching performance in the case of PEDOT:PSS-based transistors, speeding up the devices by two orders of magnitude. The utility of this OECT manufacturing approach is demonstrated by fabricating complementary logic (inverters) and glucose biosensors, thereby showing its potential to accelerate OECT research.

3D Paper-Based Origami Device for Programmable Multifold Analyte Preconcentration

In analytical chemistry, preconcentration represents a critical step able to enhance the accuracy of detection; however, the experimental procedures needed to preconcentrate samples might be characterized by drawbacks regarding the whole analytical process, e.g., being complex, invasive, and/or time-consuming. In this study, a novel 3D paper-based origami device is introduced for multifold analyte preconcentration. Leveraging the benefits of paper-based substrates, the proposed architecture boosts sample preconcentration while minimizing time and tasks for measurements, solely by exploiting the porous and versatile nature of paper-based substrates. In comparison with other paper-based approaches reported in the literature for preconcentration, the present architecture offers the ability to be programmed for obtaining the needed sensitivity increase without sacrificing measurement time. To demonstrate the efficacy of the novel approach, the 3D paper-based origami device was deeply characterized, including the most relevant parameters, i.e., disk size and number, unfolding time, and volume, and subsequently applied for the preconcentration and the detection of various analytes in real matrices, namely, mercury in tap water and glucose in sweat, resulting in a 400% and 300% sensitivity enhancement, respectively. This innovative preconcentration tool addresses the limitations of existing conventional methods, providing increased sensitivity without the use of expensive and time-consuming procedures through only exploiting the intrinsic properties of paper-based substrates and a rationale design. The proposed architecture emerges as a universal tool to be adopted and programmed for various analytical systems and fields of application.

A Wearable Thin-Film Hydrogel Laser for Functional Sensing on Skin

Flexible photonics offers the possibility of realizing wearable sensors by bridging the advantages of flexible materials and photonic sensing elements. Recently, optical resonators have emerged as a tool to improve their oversensitivity by integrating with flexible photonic sensors. However, direct monitoring of multiple psychological information on human skin remains challenging due to the subtle biological signals and complex tissue interface. To tackle the current challenges, here, we developed a functional thin film laser formed by encapsulating liquid crystal droplet lasers in a flexible hydrogel for monitoring metabolites in human sweat (lactate, glucose, and urea). The three-dimensional cross-linked hydrophilic polymer serves as the adhesive layer to allow small molecules to penetrate from human tissue to generate strong light--matter interactions on the interface of whispering gallery modes resonators. Both the hydrogel and cholesteric liquid crystal microdroplets were modified specifically to achieve high sensitivity and selectivity. As a proof of concept, wavelength-multiplexed sensing and a prototype were demonstrated on human skin to detect human metabolites from perspiration. These results present a significant advance in the fabrication and potential guidance for wearable and functional microlasers in healthcare.

Self-powered optical fiber biosensor integrated with enzymes for non-invasive glucose sensing

To alleviate the discomfort associated with frequent blood glucose detection in diabetic patients, a novel non-invasive tear glucose biosensor has been developed. This involved the design and preparation of a photoelectrochemical probe based on an optical fiber and biological enzymes. One end of the optical fiber connects to a light source, acting as an energy source and imparting, self-powered capability to the biosensor. The opposite end is loaded with nanomaterials and glucose oxidase, designed for insertion into the sample to realize photoelectrochemical sensing. This innovative configuration not only improves the integration of the biosensor but is also suitable for analyzing minuscule voluminal samples. The results show that the proposed biosensor exhibits a linear range from 10 nM to 100 μM, possesses a low detection limit of 4.1 nM and a short response time of 0.7 s. Benefiting from the high selectivity of the enzyme, the proposed biosensor demonstrates excellent resistance to the interference of common tear components. In summary, this work provides a more effective method for non-invasive glucose detection and affords valuable ideas for the design and fabrication of non-invasive and self-powered biosensors.

Using Artificial Intelligence to Improve the Accuracy of a Wrist-Worn, Noninvasive Glucose Monitor: A Pilot Study

BACKGROUND

Self-monitoring of glucose is important to the successful management of diabetes; however, existing monitoring methods require a degree of invasive measurement which can be unpleasant for users. This study investigates the accuracy of a noninvasive glucose monitoring system that analyses spectral variations in microwave signals.

METHODS

An open-label, pilot design study was conducted with four cohorts (N = 5/cohort). In each session, a dial-resonating sensor (DRS) attached to the wrist automatically collected data every 60 seconds, with a novel artificial intelligence (AI) model converting signal resonance output to a glucose prediction. Plasma glucose was measured in venous blood samples every 5 minutes for Cohorts 1 to 3 and every 10 minutes for Cohort 4. Accuracy was evaluated by calculating the mean absolute relative difference (MARD) between the DRS and plasma glucose values.

RESULTS

Accurate plasma glucose predictions were obtained across all four cohorts using a random sampling procedure applied to the full four-cohort data set, with an average MARD of 10.3%. A statistical analysis demonstrates the quality of these predictions, with a surveillance error grid (SEG) plot indicating no data pairs falling into the high-risk zones.

CONCLUSIONS

These findings show that MARD values approaching accuracies comparable to current commercial alternatives can be obtained from a multiparticipant pilot study with the application of AI. Microwave biosensors and AI models show promise for improving the accuracy and convenience of glucose monitoring systems for people with diabetes.

Pyrene Derivative Incorporated Ni MOF as an Enzyme Mimic for Noninvasive Salivary Glucose Detection Toward Diagnosis of Diabetes Mellitus

Herein, we demonstrate the detection of glucose in a noninvasive and nonenzymatic manner by utilizing an extended gate field-effect transistor (EGFET) based on the organic molecule pyrene phosphonic acid (PyP4OH8) incorporated nickel metal-organic framework (NiOM-MOF). The prepared electrode responds selectively to glucose instead of sucrose, fructose, maltose, ascorbic acid, and uric acid in a 1× phosphate buffer saline solution. Also, utilizing the scanning Kelvin probe system, the sensing electrode's work function (Φ) is measured to validate the glucose-sensing mechanism. The sensitivity, detection range, response time, limit of detection, and limit of quantification of the electrode are determined to be 24.5 μA mM-1 cm-2, 20 μM to 10 mM, less than 5 s, 2.73 μM, and 8.27 μM, respectively. Most interestingly, the developed electrode follows the Michaelis-Menten kinetics, and the calculated rate constant (km) 0.07 mM indicates a higher affinity of NiOM-MOF toward glucose. The real-time analysis has revealed that the prepared electrode is sensitive to detect glucose in real human saliva, and it can be an alternative device for the noninvasive detection of glucose. Overall, the outcomes of the EGFET studies demonstrate that the prepared electrodes are well-suited for expeditious detection of glucose levels in saliva.

The development and evolution of insulin pumps: from early beginnings to future prospects

Diabetes technology has proliferated extensively over the past few decades with vast ameliorations in glucose monitoring and in insulin delivery systems. From a treatment based on daily insulin injections, we have moved to increasingly advanced technologies. Despite such advancements which have allowed better glycemic control, decreased diabetes-related complications, and improved the quality of life among diabetic patients, it has left many individuals unsatisfied with the current rate of commercial artificial pancreas development, stemming the need for further research into novel technologies. Accordingly, the Juvenile Diabetes Research Foundation has marked three generations for the development of an artificial pancreas comprising historical landmarks and future prospects which aim to produce an advanced technological system that attempts to mimic the endogenous pancreas, eliminating the need for user input. This review presents a synopsis of the development and evolution of insulin pumps, starting with the earliest technologies available such as continuous subcutaneous insulin infusion and continuous glucose monitoring as separate components, to currently available integrated advanced closed-loop hybrid systems and possible future technologies. The aim of the review is to provide insight of the advantages and limitations of past and currently available insulin pumps with the hope of driving research into novel technologies that attempt to mimic endogenous pancreatic function as closely as possible.

Advancing 3D printed microfluidics with computational methods for sweat analysis

The intricate tapestry of biomarkers, including proteins, lipids, carbohydrates, vesicles, and nucleic acids within sweat, exhibits a profound correlation with the ones in the bloodstream. The facile extraction of samples from sweat glands has recently positioned sweat sampling at the forefront of non-invasive health monitoring and diagnostics. While extant platforms for sweat analysis exist, the imperative for portability, cost-effectiveness, ease of manufacture, and expeditious turnaround underscores the necessity for parameters that transcend conventional considerations. In this regard, 3D printed microfluidic devices emerge as promising systems, offering a harmonious fusion of attributes such as multifunctional integration, flexibility, biocompatibility, a controlled closed environment, and a minimal requisite analyte volume-features that leverage their prominence in the realm of sweat analysis. However, formidable challenges, including high throughput demands, chemical interactions intrinsic to the printing materials, size constraints, and durability concerns, beset the landscape of 3D printed microfluidic devices. Within this paradigm, we expound upon the foundational aspects of 3D printed microfluidic devices and proffer a distinctive perspective by delving into the computational study of printing materials utilizing density functional theory (DFT) and molecular dynamics (MD) methodologies. This multifaceted approach serves manifold purposes: (i) understanding the complexity of microfluidic systems, (ii) facilitating comprehensive analyses, (iii) saving both cost and time, (iv) improving design optimization, and (v) augmenting resolution. In a nutshell, the allure of 3D printing lies in its capacity for affordable and expeditious production, offering seamless integration of diverse components into microfluidic devices-a testament to their inherent utility in the domain of sweat analysis. The synergistic fusion of computational assessment methodologies with materials science not only optimizes analysis and production processes, but also expedites their widespread accessibility, ensuring continuous biomarker monitoring from sweat for end-users.

Stretchable Nanofiber-Based Felt as a String Electrode for Potential Use in Wearable Glucose Biosensors

Nanofiber technology is leading the revolution of wearable technology and provides a unique capability to fabricate smart textiles. With the novel fabrication technique of electrospinning, nanofibers can be fabricated and then manufactured into a durable conductive string for the application of smart textiles. This paper presents an electrospun nanofiber mesh-based (NF-Felt) string electrode with a conducting polymer coating for an electrochemical enzymatic glucose sensor. The surface area of a nanofiber matrix is a key physical property for enhanced glucose oxidase (GOx) enzyme binding for the development of an electrochemical biosensor. A morphological characterization of the NF-Felt string electrode was performed using scanning electron microscopy (SEM) and compared with a commercially available cotton-polyester (Cot-Pol) string coated with the same conducting polymer. The results from stress-strain testing demonstrated high stretchability of the NF-Felt string. Also, the electrochemical characterization results showed that the NF-Felt string electrode was able to detect a glucose concentration in the range between 0.0 mM and 30.0 mM with a sensitivity of 37.4 μA/mM·g and a detection limit of 3.31 mM. Overall, with better electrochemical performance and incredible flexibility, the NF-Felt-based string electrode is potentially more suitable for designing wearable biosensors for the detection of glucose in sweat.

A personalized multitasking framework for real-time prediction of blood glucose levels in type 1 diabetes patients

Real-time prediction of blood glucose levels (BGLs) in individuals with type 1 diabetes (T1D) presents considerable challenges. Accordingly, we present a personalized multitasking framework aimed to forecast blood glucose levels in patients. The patient data was initially categorized according to gender and age and subsequently utilized as input for a modified GRU network model, creating five prediction sub-models. The model hyperparameters were optimized and tuned after introducing the decay factor and incorporating the TCN network and attention mechanism into the GRU model. This step was undertaken to improve the capability of feature extraction. The Ohio T1DM clinical dataset was used to train and evaluate the performance of the proposed model. The metrics, including Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Clark Error Grid Analysis (EGA), were used to evaluate the performance. The results showed that the average RMSE and the MAE of the proposed model were 16.896 and 9.978 mg/dL, respectively, over the prediction horizon (PH) of 30 minutes. The average RMSE and the MAE were 28.881 and 19.347 mg/dL, respectively, over the PH of 60 min. The proposed model demonstrated excellent prediction accuracy. In addition, the EGA analysis showed that the proposed model accurately predicted 30-minute and 60-minute PH within zones A and B, demonstrating that the framework is clinically feasible. The proposed personalized multitask prediction model in this study offers robust assistance for clinical decision-making, playing a pivotal role in improving the outcomes of individuals with diabetes.

Plasmonic Optical Fiber Based Continuous in-Vivo Glucose Monitoring for ICU/CCU Setup

This paper reports a sensor architecture for continuous monitoring of biomarkers directly in the blood, especially for ICU/CCU patients requiring critical care and rapid biomarker measurement. The sensor is based on a simple optical fiber that can be inserted through a catheter into the bloodstream, wherein gold nanoparticles are attached at its far distal end as a plasmonic material for highly sensitive opto-chemical sensing of target biomolecules (glucose in our application) via the excitation of surface plasmon polaritons. For specificity, the nanoparticles are functionalized with a specific receptor enzyme that enables the localized surface plasmon resonance (LSPR)-based targeted bio-sensing. Further, a micro dialysis probe is introduced in the proposed architecture, which facilitates continuous monitoring for an extended period without fouling the sensor surface with cells and blood debris present in whole blood, leading to prolonged enhanced sensitivity and limit of detection, relative to existing state-of-the-art continuous monitoring devices that can conduct direct measurements in blood. To establish this proof-of-concept, we tested the sensor device to monitor glucose in-vivo involving an animal model, where continuous monitoring was done directly in the circulation of living rats. The sensor's sensitivity to glucose was found to be 0.0354 a.u./mg.dl-1 with a detection limit of 50.89 mg/dl.

Advances in Non-Electrochemical Sensing of Human Sweat Biomarkers: From Sweat Sampling to Signal Reading

Sweat, commonly referred to as the ultrafiltrate of blood plasma, is an essential physiological fluid in the human body. It contains a wide range of metabolites, electrolytes, and other biologically significant markers that are closely linked to human health. Compared to other bodily fluids, such as blood, sweat offers distinct advantages in terms of ease of collection and non-invasive detection. In recent years, considerable attention has been focused on wearable sweat sensors due to their potential for continuous monitoring of biomarkers. Electrochemical methods have been extensively used for in situ sweat biomarker analysis, as thoroughly reviewed by various researchers. This comprehensive review aims to provide an overview of recent advances in non-electrochemical methods for analyzing sweat, including colorimetric methods, fluorescence techniques, surface-enhanced Raman spectroscopy, and more. The review covers multiple aspects of non-electrochemical sweat analysis, encompassing sweat sampling methodologies, detection techniques, signal processing, and diverse applications. Furthermore, it highlights the current bottlenecks and challenges faced by non-electrochemical sensors, such as limitations and interference issues. Finally, the review concludes by offering insights into the prospects for non-electrochemical sensing technologies. By providing a valuable reference and inspiring researchers engaged in the field of sweat sensor development, this paper aspires to foster the creation of innovative and practical advancements in this domain.

A highly sensitive and long-term stable wearable patch for continuous analysis of biomarkers in sweat

Although increasing efforts have been devoted to the development of non-invasive wearable or stretchable electrochemical sweat sensors for monitoring physiological and metabolic information, most of them still suffer from poor stability and specificity over time and fluctuating temperatures. This study reports the design and fabrication of a long-term stable and highly sensitive flexible electrochemical sensor based on nanocomposite-modified porous graphene by simple and facile laser treatment for detecting biomarkers such as glucose in sweat. The laser-reduced and patterned stable conductive nanocomposite on the porous graphene electrode provides the resulting glucose sensor with an excellent sensitivity of 1317.69 μAmM-1cm-2 with an ultra-low limit of detection (LOD) of 0.079 μM. The sensor can also detect pH and exhibit extraordinary stability to maintain more than 91% sensitivity over 21 days in ambient conditions. Taken together with a temperature sensor based on the same material system, the dual glucose and pH sensor integrated with a flexible microfluidic sweat sampling network further results in accurate continuous on-body glucose detection calibrated by the simultaneously measured pH and temperature. The low-cost, highly sensitive, and long-term stable platform could facilitate and pave the way for the early identification and continuous monitoring of different biomarkers for non-invasive disease diagnosis and treatment evaluation.

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

Diabetes is one of the leading non-communicable diseases globally, adversely impacting an individual's quality of life and adding a considerable burden to the healthcare systems. The necessity for frequent blood glucose (BG) monitoring and the inconveniences associated with self-monitoring of BG, such as pain and discomfort, has motivated the development of non-invasive BG approaches. However, the current research progress is slow, and only a few BG self-monitoring devices have made considerable progress. Hence, we evaluate the available non-invasive glucose monitoring technologies validated against BG recordings to provide future research direction to design, develop, and deploy self-monitoring of BG with integrated emerging technologies. We searched five databases, Embase, MEDLINE, Proquest, Scopus, and Web of Science, to assess the non-invasive technology's scope in the diabetes management paradigm published from 2000 to 2020. A total of three approaches to non-invasive screening, including saliva, skin, and breath, were identified and discussed. We observed a statistical relationship between BG measurements obtained from non-invasive methods and standard clinical measures. Opportunities exist for future research to advance research progress and facilitate early technology adoption for healthcare practice. The results promise clinical validity; however, formulating regulatory guidelines could foresee the deployment of approved non-invasive BG monitoring technologies in healthcare practice. Further, research prospects are there to design, develop, and deploy integrated diabetes management systems with mobile technologies, data analytics, and the internet of things (IoT) to deliver a personalised monitoring system.

Optimized Copper-Based Microfeathers for Glucose Detection

Diabetes is expected to rise substantially by 2045, prompting extensive research into accessible glucose electrochemical sensors, especially those based on non-enzymatic materials. In this context, advancing the knowledge of stable metal-based compounds as alternatives to non-enzymatic sensors becomes a scientific challenge. Nonetheless, these materials have encountered difficulties in maintaining stable responses under physiological conditions. This work aims to advance knowledge related to the synthesis and characterization of copper-based electrodes for glucose detection. The microelectrode presented here exhibits a wide linear range and a sensitivity of 1009 µA∙cm-2∙mM-1, overperfoming the results reported in literature so far. This electrode material has also demonstrated outstanding results in terms of reproducibility, repeatability, and stability, thereby meeting ISO 15197:2015 standards. Our study guides future research on next-generation sensors that combine copper with other materials to enhance activity in neutral media.

Adoption of Wearable Insulin Biosensors for Diabetes Management: A Cross-Sectional Study

BACKGROUND

Wearable insulin biosensors represent a novel approach that combines the benefits of real-time glucose monitoring and automated insulin delivery, potentially revolutionizing how individuals with diabetes manage their condition.

STUDY PURPOSE

To analyze the behavioral intentions of wearable insulin biosensors among diabetes patients, the factors that drive or hinder their usage, and the implications for diabetes management and healthcare outcomes.

METHODS

A cross-sectional survey design was adopted in this study. The validated questionnaire included 10 factors (Performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, trust, perceived privacy risk, and personal innovativeness) affecting the acceptance of wearable insulin sensors. A total of 248 diabetic patients who had used wearable sensors participated in the study.

RESULTS

Performance expectancy was rated the highest (Mean = 3.84 out of 5), followed by effort expectancy (Mean = 3.78 out of 5), and trust (Mean = 3.53 out of 5). Statistically significant differences (p < 0.05) were observed with respect to socio-demographic variables including age and gender on various influencing factors and adoption intentions. PE, EE, and trust were positively associated with adoption intentions.

CONCLUSION

While wearable insulin sensors are positively perceived with respect to diabetes management, issues like privacy and security may affect their adoption.

Fabrication of conductive Ag/AgCl/Ag nanorods ink on Laser-induced graphene electrodes on flexible substrates for non-enzymatic glucose detection

An unusual strategy was designed to fabricate conductive patterns for flexible surfaces, which were utilized for non-enzymatic amperometric glucose sensors. The Ag/AgCl/Ag quasi-reference ink formulation utilized two reducing agents, NaBH[Formula: see text] and ethylene glycol. The parameters of the ink, such as sintering time and temperature, NaBH[Formula: see text] concentration, and layer number of coatings on flexible laser-induced graphene (LIG) electrodes were investigated. The conductive Ag/AgCl/Ag ink was characterized using electrochemical and surface analysis techniques. The electrocatalytic activity of Ag/AgCl/Ag NRs can be attributed to their high surface area, which offer numerous active sites for catalytic reactions. The selectivity and sensitivity of the electrodes for glucose detection were investigated. The XRD analysis showed (200) oriented AgCl on covered Ag NRs, and with the addition of NaBH[Formula: see text], the intensity of the peaks of the Ag NRs increased. The wide linear range of non-enzymatic sensors was attained from 0.003 to 0.18 mM and 0.37 to 5.0 mM, with a low limit of detection of 10 [Formula: see text]M and 20 [Formula: see text]M, respectively.The linear range of enzymatic sensor in real sample was determined from 0.040 to 0.097 mM with a detection limit of 50 [Formula: see text]M. Furthermore, results of the interference studies demonstrated excellent selectivity of the Ag/AgCl/Ag NRs/LIG electrode. The Ag/AgCl/Ag NRs on the flexible LIG electrode exhibited excellent sensitivity,long-time stablity,and reproducibility. The efficient electroactivity were deemed suitable for various electrochemical applications and biosensors.

Correlation of Transmission Properties with Glucose Concentration in a Graphene-Based Microwave Resonator

Carbon-based materials, such as graphene, exhibit interesting physical properties and have been recently investigated in sensing applications. In this paper, a novel technique for glucose concentration correlation with the resonant frequency of a microwave resonator is performed. The resonator exploits the variation of the electrical properties of graphene at radio frequency (RF). The described approach is based on the variation in transmission coefficient resonating frequency of a microstrip ring resonator modified with a graphene film. The graphene film is doctor-bladed on the ring resonator and functionalised in order to detect glucose. When a drop with a given concentration is deposited on the graphene film, the resonance peak is shifted. The graphene film is modelled with a lumped element analysis. Several prototypes are realised on Rogers Kappa substrate and their transmission coefficient measured for different concentrations of glucose. Results show a good correlation between the frequency shift and the concentration applied on the film.

Colorimetric sweat analysis using wearable hydrogel patch sensors for detection of chloride and glucose

Sweat is a promising non-invasive biofluid that can provide valuable insights into the physiological state of the human body. However, a major obstacle to analyzing sweat in real-time is the fabrication of simple, fast-acting, accurate, and low-cost sensing constructs. To address this challenge, we introduced easily-prepared wearable hydrogel sensors that can be placed on the skin and used colorimetric techniques to assess sweat analytes without invasive procedures. Two typical sweat sensors, chloride ion (Cl-) responsive patches for cystic fibrosis (CF) analysis and glucose response patches for diabetic monitoring, were demonstrated for real sample analysis. The Cl- colorimetric sensor, with a detection limit down to 100 μM, shows a good linear response from 1.56 mM to 200 mM Cl-, and the glucose colorimetric sensor, with a detection limit down to 1 μM, exhibits an adequate linear response from 10 μM to 1 mM glucose. These colorimetric hydrogel sensors are also incorporated into a medical dressing to create wearable sensor devices for real-time sweat analysis. The acquired readings closely match the results obtained from the benchmark analyzing instrument, with a small deviation of less than 10%. Therefore, our simple colorimetric hydrogel sensing patches hold great potential to advance real-time sweat testing and contribute to the transitional development of wearable medical devices.

Enhancing On-Skin Analysis: A Microfluidic Device and Smartphone Imaging Module for Real-Time Quantitative Detection of Multianalytes in Sweat

Wearable sweat sensors present exciting opportunities for advancing personal health monitoring and noninvasive biomarker measurements. However, existing sensors often fall short in accurate detection of low analyte volumes and concentrations and lack multimodal sensing capabilities. Herein, we present a highly portable four-channel microfluidic device capable of conducting simultaneous sweat sampling and fluorometric sensing of potential biomarkers, such as l-Tyr, l-Trp, Crt, and NH4+, specifically designed for kidney disease monitoring. Our microfluidic device seamlessly integrates with smartphones, facilitating easy data retrieval and analysis. The core of the sensing array is a novel fluorometric solid-state mechanism utilizing carbon polymer dots derived from dopamine, catechol, and o-phenylenediamine monomers embedded in gelatin hydrogels. The sensors exhibit exceptional performance, offering linear ranges of 5-275, 6-170, 4-220, and 5-170 μM, with impressively low detection limits of 1.5, 1.2, 1.3, and 1.4 μM for l-Tyr, l-Trp, Crt, and NH4+, respectively. Through meticulous optimization of operational variables, comprising the temperature, sample volume, and assay time, we achieved the best performance of the device. Furthermore, the sensors exhibited remarkable selectivity, effectively distinguishing between biologically similar species and other potential biological compounds found in sweat. Our evaluation also extended to monitoring kidney diseases in patients and healthy individuals, showcasing the device's utility in world scenarios. Promising results showcase the potential of low-cost, multidiagnostic microfluidic sensor arrays, especially with synthetic skin integration, for enhanced disease detection and healthcare outcomes.

Mini review about metal organic framework (MOF)-based wearable sensors: Challenges and prospects

Among many types of wearable sensors, MOFs-based wearable sensors have recently been explored in both commercialization and research. There has been much effort in various aspects of the development of MOF-based wearable sensors including but not limited to miniaturization, size control, safety, improvements in conformal and flexible features, improvements in the analytical performance and long-term storage of these devices. Recent progress in the design and deployment of MOFs-based wearable sensors are covered in this paper, as are the remaining obstacles and prospects. This work also highlights the enormous potential for synergistic effects of MOFs used in combination with other nanomaterials for healthcare applications and raise attention toward the economic aspect and market diffusion of MOFs-based wearable sensors.

Mill Scale-Derived Magnetite Nanoparticles: A Novel Substrate for Lactate Oxidase-Based Biosensors

Recycling and revalorization of waste are currently essential for sustainable growth. Mill scale, a waste product from steel production industries, which contains high levels of iron and minimal impurities, is proposed in this study as the source to synthesize magnetite nanoparticles (Fe3O4) for an enhancement of a lactate biosensor range. The synthesized Fe3O4 nanoparticles were coated with polydopamine (PDA) to prevent aggregation and degradation, creating a stable platform for immobilizing lactate oxidase enzyme (LOx) on their surfaces. The characterization of the Fe3O4@PDA material was carried out using transmission electron microscopy (TEM), dynamic light scattering (DLS), and measurement of the polydispersity index (PdI). The Fe3O4@PDA-LOx material was then deposited on a screen-printed carbon electrode modified with Prussian blue (SPCE-PB) for lactate detection. The biosensor exhibited a broad, dual linear concentration-response range, one from 0.1 to 4.62 mM with a limit of detection of 0.32 mM and sensitivity of 1.54 μAmM-1cm-2, and another one from 4.62 to 149.21 mM with a limit of detection of 6.31 mM and sensitivity of 0.08 μAmM-1cm-2. The dual-range concentration response of the biosensor makes it an ideal tool for lactate determination in various applications, including sports medicine, clinical diagnosis, and industrial bioprocessing.

Implicit HbA1c Achieving 87% Accuracy within 90 Days in Non-Invasive Fasting Blood Glucose Measurements Using Photoplethysmography

To reduce the error induced by overfitting or underfitting in predicting non-invasive fasting blood glucose (NIBG) levels using photoplethysmography (PPG) data alone, we previously demonstrated that incorporating HbA1c led to a notable 10% improvement in NIBG prediction accuracy (the ratio in zone A of Clarke's error grid). However, this enhancement came at the cost of requiring an additional HbA1c measurement, thus being unfriendly to users. In this study, the enhanced HbA1c NIBG deep learning model (blood glucose level predicted from PPG and HbA1c) was trained with 1494 measurements, and we replaced the HbA1c measurement (explicit HbA1c) with "implicit HbA1c" which is reversely derived from pretested PPG and finger-pricked blood glucose levels. The implicit HbA1c is then evaluated across intervals up to 90 days since the pretest, achieving an impressive 87% accuracy, while the remaining 13% falls near the CEG zone A boundary. The implicit HbA1c approach exhibits a remarkable 16% improvement over the explicit HbA1c method by covering personal correction items automatically. This improvement not only refines the accuracy of the model but also enhances the practicality of the previously proposed model that relied on an HbA1c input. The nonparametric Wilcoxon paired test conducted on the percentage error of implicit and explicit HbA1c prediction results reveals a substantial difference, with a p-value of 2.75 × 10-7.

On-body non-invasive glucose monitoring sensor based on high figure of merit (FoM) surface plasmonic microwave resonator

High-figure of merit (FoM) plasmonic microwave resonator is researched as a non-invasive on-body sensor to monitor the human body's blood glucose variation rate in adults for biomedical applications, e.g., diabetic patients. The resonance frequencies of the proposed sensor are measured to be around [Formula: see text] GHz and [Formula: see text] GHz over the frequency band of DC to 6GHz which are suitable for monitoring interstitial fluid (ISF) changing rate. The [Formula: see text] sensor is experimentally wrapped on the human body arm to monitor the blood glucose changing rate via amplitude and frequency variations of the sensor. Amplitude variation and frequency shift are measured to be around 7 dB and 30 MHz, respectively. The measured results demonstrate the high precision of the proposed approach to depict a valid diagram for glucose changing rate due to good impedance matching of the designed microwave sensor and human body. The sensor is shown to enhance the sensitivity by a factor of 5 compared to the conventional ones.

Cyclodextrin Host-Guest Recognition in Glucose-Monitoring Sensors

Diabetes mellitus is a prevalent chronic health condition that has caused millions of deaths worldwide. Monitoring blood glucose levels is crucial in diabetes management, aiding in clinical decision making and reducing the incidence of hypoglycemic episodes, thereby decreasing morbidity and mortality rates. Despite advancements in glucose monitoring (GM), the development of noninvasive, rapid, accurate, sensitive, selective, and stable systems for continuous monitoring remains a challenge. Addressing these challenges is critical to improving the clinical utility of GM technologies in diabetes management. In this concept, cyclodextrins (CDs) can be instrumental in the development of GM systems due to their high supramolecular recognition capabilities based on the host-guest interaction. The introduction of CDs into GM systems not only impacts the sensitivity, selectivity, and detection limit of the monitoring process but also improves biocompatibility and stability. These findings motivated the current review to provide a comprehensive summary of CD-based blood glucose sensors and their chemistry of glucose detection, efficiency, and accuracy. We categorize CD-based sensors into four groups based on their modification strategies, including CD-modified boronic acid, CD-modified mediators, CD-modified nanoparticles, and CD-modified functionalized polymers. These findings shed light on the potential of CD-based sensors as a promising tool for continuous GM in diabetes mellitus management.

Saliva sampling strategies affecting the salivary glucose measurement

Characterized by sustained elevated blood glucose levels, diabetes mellitus has become one of the largest global public health concerns by imposing a heavy global burden on socio-economic development. To date, regular blood glucose level check by performing a finger-prick test has been a routine strategy to monitor diabetes. However, the intrusive nature of finger blood prick tests makes it challenging for individuals to maintain consistent testing routines. Recently, salivary glucose measurement (SGM) has increasingly become a non-invasive alternative to traditional blood glucose testing for diabetes. Despite that, further research is needed to standardize the collection methods and address the issues of variability to ensure accurate and reliable SGM. To resolve possible remaining issues in SGM, we here thoroughly explored saliva sampling strategies that could impact the measurement results. Additionally, the effects of supplements taken, mouth washing, gum chewing, and smoking were collectively analyzed, followed by a continuous SGM over a long period, forming the stepping stone for the practical transitional development of SGM in non-invasive diabetes monitoring.

Sweat analysis for urea sensing: trends and challenges

With increasing population there is a rise in pathological diseases that the healthcare facilities are grappling with. Sweat-based wearable technologies for continuous monitoring have overcome the demerits associated with sweat sampling and sensing. Hence, sweat as an alternative biofluid holds great promise for the quantification of a host of biomarkers and understanding the functioning of the body, thereby deducing ailments quickly and economically. This comprehensive review accounts for recent advances in sweat-based LOCs (Lab-On-Chips), which are a likely alternative to the existing blood-urea sample testing that is invasive and time-consuming. The present review is focused on the advancements in sweat-based Lab-On-Chips (LOCs) as an alternative to invasive and time-consuming blood-urea sample testing. In addition, different sweat collection methods (direct skin, near skin and microfluidic) and their mechanism for urea sensing are explained in detail. The mechanism of urea in biofluids in protein metabolism, balancing nitrogen levels and a crucial factor of kidney function is described. In the end, research and technological advancements are explained to address current challenges and enable its widespread implementation.

Nanomaterials-based biosensor and their applications: A review

A sensor can be called ideal or perfect if it is enriched with certain characteristics viz., superior detections range, high sensitivity, selectivity, resolution, reproducibility, repeatability, and response time with good flow. Recently, biosensors made of nanoparticles (NPs) have gained very high popularity due to their excellent applications in nearly all the fields of science and technology. The use of NPs in the biosensor is usually done to fill the gap between the converter and the bioreceptor, which is at the nanoscale. Simultaneously the uses of NPs and electrochemical techniques have led to the emergence of biosensors with high sensitivity and decomposition power. This review summarizes the development of biosensors made of NPssuch as noble metal NPs and metal oxide NPs, nanowires (NWs), nanorods (NRs), carbon nanotubes (CNTs), quantum dots (QDs), and dendrimers and their recent advancement in biosensing technology with the expansion of nanotechnology.

A Novel Robust Method Mimicking Human Substratum To Dissect the Heterogeneity of Candida auris Biofilm Formation

Candida auris is a pathogen of urgent threat level as marked by the CDC. The formation of biofilms is an essential property of this fungus to establish infection and escape drug treatment. However, our understanding of pathogenesis through biofilm is hampered by heterogeneity in C. auris biofilms observed in different studies. It is imperative to replicate in vivo conditions for studying C. auris biofilm formation in vitro. Different methods are standardized, but the surface used to form biofilms lacks consistency as well as the architecture of a typical biofilm. Here, we report an in vitro technique to grow C. auris biofilms on gelatin-coated coverslips. Interestingly, C. auris cells grown on gelatin-coated coverslips either on modified synthetic sweat media or RPMI 1640 resulted in similar multilayer biofilm formation with extracellular polymeric substances (EPS). This method is also consistent with the biofilm formation of other Candida species, such as Candida glabrata and Candida albicans. Biofilms of C. glabrata developed through this method show pseudohyphae and EPS. This method can be used to understand the molecular basis of biofilm formation, associated pathogenesis, and drug tolerance. The technique is cost-effective and would thus serve in rightful screening and repurposing drug libraries for designing new therapeutics against the less-studied high-alarm pathogen C. auris. IMPORTANCE Heterogeneity is seen when multidrug-resistant C. auris biofilm is cultured using different reported methods. Biofilm formed on the gelatin surface mimics the condition of a host environment that has multilayers and EPS. This method has feasibility for drug screening and analyzing biofilms through three-dimensional (3D) reconstruction. This in vitro biofilm formation technique is also exploited to study the formation of biofilm of other Candida species. The biofilms of C. glabrata and C. albicans can also be correctly mimicked using gelatin in the biofilm-forming environment. Thus, the novel in vitro method for biofilm formation reported here can be widely used to understand the mechanism of biofilm formation, related virulence properties, and drug tolerance of C. auris and other Candida species. This simple and low-cost technique is highly suitable for screening novel inhibitors and repurposed libraries and to design new therapeutics against Candida species.

Textile Electronics with Laser-Induced Graphene/Polymer Hybrid Fibers

The concept of wearables is rapidly evolving from flexible polymer-based devices to textile electronics. The reason for this shift is the ability of textiles to ensure close contact with the skin, resulting in comfortable, lightweight, and compact "always with you" sensors. We are contributing to this polymer-textile transition by introducing a novel and simple way of laser intermixing of graphene with synthetic fabrics to create wearable sensing platforms. Our hybrid materials exhibit high electrical conductivity (87.6 ± 36.2 Ω/sq) due to the laser reduction of graphene oxide and simultaneous laser-induced graphene formation on the surface of textiles. Furthermore, the composite created between graphene and nylon ensures the durability of our materials against sonication and washing with detergents. Both of these factors are essential for real-life applications, but what is especially useful is that our free-form composites could be used as-fabricated without encapsulation, which is typically required for conventional laser-scribed materials. We demonstrate the exceptional versatility of our new hybrid textiles by successfully recording muscle activity, heartbeat, and voice. We also show a gesture sensor and an electrothermal heater embedded within a single commercial glove. Additionally, the use of these textiles could be extended to personal protection equipment and smart clothes. We achieve this by implementing self-sterilization with light and laser-induced functionalization with silver nanoparticles, which results in multifunctional antibacterial textiles. Moreover, incorporating silver into such fabrics enables their use as surface-enhanced Raman spectroscopy sensors, allowing for the direct analysis of drugs and sweat components on the clothing itself. Our research offers valuable insights into simple and scalable processes of textile-based electronics, opening up new possibilities for paradigms like the Internet of Medical Things.