Search Results (90)

Sweat is a valuable biofluid for non-invasive health monitoring, as it contains electrolytes, metabolites, and organic compounds that can correlate with blood levels, making it highly attractive for wearable sensing. Building on advances in low-cost, portable electrochemical sensors, sweat analysis enables tracking of hydration status, metabolic stress, and energy availability via key markers such as sodium, potassium, lactate, and glucose. In the sports context, such wearable platforms can support performance optimization and recovery by assessing fluid loss and electrolyte balance in real time. Here, a multiplexed wearable sweat patch is developed to simultaneously monitor temperature, pH, ammonium, sodium, and sweat rate. The integrated platform demonstrates sensitivities of 10.1 mV/ln[NH₄⁺], 9.1 mV/ln[K⁺], 1.11 mV/ln[Na⁺], 14 mV/pH, 0.19% °C⁻¹, and approximately −1.0 mA (mL/min)⁻¹ for sweat rate, with stable signals and linear calibration responses over relevant physiological ranges. The sensor is implemented on a lightweight, biocompatible laser-scribed graphene on a PDMS substrate suitable for prolonged skin contact and mechanical deformation. In addition, a custom PDMS adhesive patch with optimized suction-cup microstructures is engineered to improve skin adhesion under both dry and wet conditions. Finally, the design of the platform was inspired by an adaptive cycling marathon across Saudi Arabia, where an earlier prototype of a wearable patch was deployed for real-time monitoring during a 30-day campaign. Full article

As a promising class of catalysts for enzymatic glucose sensors, Prussian blue analogues (PBAs) exhibit exceptional biomimetic activity. However, their performance is often constrained by poor intrinsic conductivity, which typically limits their sensitivity. To address this limitation, this study presents an effective approach using direct in situ growth of PBAs on the electrode substrates, which enables the effective integration of PBA-based electrochemical systems. A porous Ni framework was first electrodeposited onto a screen-printed gold electrode substrate, followed by the reduction of Pt onto the porous Ni. Subsequently, NiFe PBA was synthesized in situ using the porous Pt/Ni structure as a sacrificial template. Functionalized with glucose oxidase (GO_x), the PBA/Pt/Ni biosensor exhibited excellent performance for glucose detection in buffer solution, with a high sensitivity of 262.6 μA mM⁻¹·cm⁻² and an ultra-low detection limit of 1.45 μM (calculated at a signal-to-noise ratio of 3, S/N = 3). Notably, its sensitivity corresponds to a two-fold enhancement relative to the electrodes modified with commercial Prussian blue using the conventional drop-casting method. Even when tested in human sweat samples, the biosensor achieved a high sensitivity of 236.4 μA mM⁻¹·cm⁻² and a linear detection range of 20–1000 μM, with the broad sensing range fully encompassing the typical physiological concentrations of glucose in human sweat. This excellent performance arises from the high specific surface area of the porous Pt/Ni structure and the tight connection between PBA and the sacrificial Ni anode. This research presents a promising design strategy for advanced, wearable, and non-invasive health-monitoring platforms. Full article

Two-dimensional Ti₃C₂O₂ MXene has emerged as a promising electrode material for non-enzymatic glucose sensing due to its metallic conductivity and biocompatibility. However, the atomic-scale sensing mechanism remains unclear. This DFT study uses the PBE functional with the D3(BJ) dispersion correction to elucidate glucose–MXene interactions under idealized vacuum conditions. Pristine Ti₃C₂O₂ shows metallic behavior with a density of states of about 8.2 states per electron volt at the Fermi level, dominated by Ti 3d states. β-d-glucose adsorbs onto the surface through hydrogen bonding, with an adsorption energy of −0.82 eV at a separation distance of 2.8 angstroms. Bader analysis indicates a transfer of about 0.15 electrons from MXene to glucose, resulting in a Fermi level shift of about −0.15 eV and an 18% reduction in the density of states at the Fermi level. These changes correspond to an estimated sensitivity of approximately 0.6 μA mM⁻¹ cm⁻² and a detection limit of about 17 µM, consistent with reported experimental performance of MXene-based sensors. Comparative adsorption calculations for common sweat interferents yield −0.45 eV for lactate and −0.25 eV for urea, indicating weaker interfacial affinity than glucose; these values reflect thermodynamic binding strength and possible surface occupation rather than definitive electrochemical selectivity, which additionally depends on redox potential, electron-transfer kinetics, and operating bias. We acknowledge three main limitations: first, the model considers only pure oxygen termination rather than mixed oxygen, hydroxyl, and fluorine terminations; second, the calculations are performed under vacuum rather than in aqueous conditions; third, the study is based on static zero kelvin structures rather than finite temperature dynamics. Despite these idealizations, the results provide baseline mechanistic insights to support rational design of MXene-based glucose sensors. Full article

The increasing demand for continuous physiological monitoring has accelerated the development of high-sensitivity wearable electrochemical platforms. This study reports the fabrication of a multi-analyte electrochemical sensor based on single-walled carbon nanotubes (SWCNTs) for the detection of sweat-associated metabolites. To facilitate efficient heterogeneous electron transfer, glucose oxidase (Gox), lactate oxidase (Lox), and urease (Ure) were immobilized onto the SWCNT network through π–π interaction using 1-pyrenebutanoic acid succinimidyl ester (PBSE), followed by additional stabilization via 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) coupling. The developed platform exhibited concentration-dependent resistance responses within the ranges of 0.02–0.20 mM for glucose, 20–100 mM for lactate, and 50–400 mM for urea under controlled experimental conditions. The resistance-based configuration enabled stable and reproducible signal modulation across these concentration intervals. Although direct testing with human sweat was not performed, the electrochemical behavior of key sweat-related metabolites was systematically evaluated as a preparatory step toward future wearable integration. Full article

Background: Traditionally, wild jujube (Ziziphus jujuba Mill. var. spinosa (Bunge) Hu ex H. F. Chou) has been used to nourish the heart, calm the spirit, and arrest spontaneous sweating. Modern research confirms its broad pharmacological activities, including antioxidant, anti-inflammatory, neuroprotective, and cognitive-enhancing effects. This study aims to isolate and characterize the structure of jujube polysaccharides and evaluate their protective effects against oxidative stress damage in neural stem cells (NSCs). Methods: We successfully isolated and purified a novel pectin polysaccharide (ZJP-2) from wild jujube. Its structure was characterized in detail using high-performance liquid chromatography coupled with multi-angle laser light scattering and refractive index detection (HPLC-MALS-RI), high-performance anion exchange chromatography (HPAEC), gas chromatography–mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR) spectroscopy. Results: Structural analysis revealed that ZJP-2 is a pectin heteropolysaccharide with a molecular weight of approximately 67.93 kDa. Its monosaccharide composition primarily includes galac-turonic acid (GalA), arabinose (Ara), rhamnose (Rha), galactose (Gal), and glucose (Glc). The backbone consists of α-GalA and rhamnose-galacturonic acid-I (RG-I) domains linked by (1→4)-glycosidic bonds. NMR spectroscopy further confirmed its glycosidic bond types. In activity assessment, our study demonstrated that ZJP-2 significantly alleviated DMNQ-induced oxidative stress damage in C17.2 neural stem cells. Its protective effect was achieved by reducing intracellular reactive oxygen species (ROS) levels and upregulating the mRNA expression of antioxidant genes associated with the signaling axis (p < 0.05). Moreover, ZJP-2 suppressed DMNQ-induced overexpression of Nestin and NeuN (p < 0.05), contributing to the maintenance of NSCs’ undifferentiated state and functional homeostasis. Conclusions: In conclusion, ZJP-2 possesses distinct structural characteristics and significant neuroprotective potential, supporting its development as a natural functional food or dietary supplement for preventing oxidative stress-related neural damage. Full article

The development of efficient bioelectrodes requires suitable fabrication strategies, starting with the electrode material, which affects the electron transfer between the biocatalyst and the electrode surface. Then, selection and adjustment of the enzyme immobilization conditions are essential to enhance the performance of the bioelectrodes for their desirable utility. In this study, we report the fabrication of a high-performance bioelectrode using a one-step crosslinking of FAD-dependent glucose dehydrogenase (FAD-GDH) and thionine acetate as a redox mediator, with genipin serving as a natural, biocompatible crosslinker. Electrodes were manufactured on flexible polyester substrates using a direct printing technique, enabling reproducible and low-cost production. Among the tested crosslinkers, genipin significantly enhanced the catalytic performance of bioelectrodes. Comparative studies on graphite, silver, and gold electrode materials identified graphite as the most suitable due to its extended electroactive surface area. The developed bioelectrodes applied to glucose biosensing demonstrated a linear amperometric response to glucose in the range of 0.02–2 mM and 0.048–30 mM, covering clinically relevant concentrations. The application of artificial sweat confirmed high detection accuracy. These findings highlight the potential integration of genipin-based enzyme–mediator networks for future non-invasive sweat glucose monitoring platforms. Full article

Diabetes is a chronic metabolic disorder that poses a growing global health challenge, currently affecting nearly 500 million people. Over the past four decades, the rising prevalence of diabetes has highlighted the urgent need for innovations in monitoring and management. Traditional enzymatic methods, including those using glucose oxidase, glucose dehydrogenase, and hexokinase, are widely adopted due to their specificity and relative ease of use. However, they are hindered by issues of instability, environmental sensitivity, and interference from other biomolecules. Non-enzymatic sensors, which employ metals and nanomaterials for the direct oxidation of glucose, offer an attractive alternative. These platforms demonstrate higher sensitivity and cost-effectiveness, though they remain under refinement for routine use. Non-invasive glucose detection represents a futuristic leap in diabetes care. By leveraging alternative biofluids such as saliva, tears, sweat, and breath, these methods promise enhanced patient comfort and compliance. Nonetheless, their limited sensitivity continues to challenge widespread adoption. Looking forward, the integration of nanotechnology, wearable biosensors, and artificial intelligence paves the way for personalized, affordable, and patient-centered diabetes management, marking a transformative era in healthcare. This review explores the evolution of glucose monitoring, from early chemical assays to advanced state-of-the-art nanotechnology-based approaches. Full article

Type 1 diabetes (T1D) management is increasingly enhanced by wearable glucose sensors (WGSs) integrated with artificial intelligence (AI) that combine multiple physiological parameters—such as heart rate, galvanic skin response, body temperature, and physical activity—to predict glucose fluctuations more accurately. Noninvasive sensor technologies, including optical and sweat-based methods, show promise in reducing patient discomfort but still require further clinical validation to confirm reliability. Recent clinical data demonstrate significant potential for these advanced WGS technologies, with substantial improvements in glycemic control and overall disease management reported among all surveyed patients. Insulin pumps integrated with continuous glucose monitoring form “artificial pancreas” systems that automatically adjust insulin delivery in real time, improving patient convenience and metabolic outcomes. Despite progress, challenges remain related to response latency, device interoperability, and adaptation to abrupt physiological changes. According to our results, patient acceptance of WGS-based treatments is high, with nearly all individuals willing to adopt these technologies. Initial reluctance is mostly observed during the first weeks, coinciding with the AI algorithm’s calibration and learning phase; however, adherence increases significantly once this period concludes. In conclusion, these integrated technologies represent a practical shift toward personalized, proactive T1D care. Their successful implementation depends on overcoming technical and ethical challenges while addressing psychological factors such as alert fatigue, particularly in vulnerable populations. Full article

Three-dimensional printing technology is fundamentally reshaping the design and fabrication of health monitoring sensors. While it holds great promise for achieving miniaturization, multi-material integration, and personalized customization, the lack of a clear selection framework hinders the optimal matching of printing technologies to specific sensor requirements. This review presents a classification framework based on existing standards and specifically designed to address sensor-related requirements, categorizing 3D printing technologies into point-based, line-based, and area-based modalities according to their fundamental fabrication unit. This framework directly bridges the capabilities of each modality, such as nanoscale resolution, multi-material versatility, and high-throughput production, with the critical demands of modern health monitoring sensors. We systematically demonstrate how this approach guides technology selection: Point-based methods (e.g., stereolithography, inkjet) enable micron-scale features for ultra-sensitive detection; line-based techniques (e.g., Direct Ink Writing, Fused Filament Fabrication) excel in multi-material integration for creating complex functional devices such as sweat-sensing patches; and area-based approaches (e.g., Digital Light Processing) facilitate rapid production of sensor arrays and intricate structures for applications like continuous glucose monitoring. The point–line–area paradigm offers a powerful heuristic for designing and manufacturing next-generation health monitoring sensors. We also discuss strategies to overcome existing challenges, including material biocompatibility and cross-scale manufacturing, through the integration of AI-driven design and stimuli-responsive materials. This framework not only clarifies the current research landscape but also accelerates the development of intelligent, personalized, and sustainable health monitoring systems. Full article

Polymer gel-based triboelectric nanogenerators (TENGs) have emerged as versatile platforms for self-powered sensing due to their inherent softness, stretchability, and tunable conductivity. This review comprehensively explores the roles of polymer gels in TENG architecture, including their function as triboelectric layers, electrodes, and conductive matrices. We analyze four operational modes—vertical contact-separation, lateral-sliding, single-electrode, and freestanding configurations—alongside key performance metrics. Recent studies have reported output voltages of up to 545 V, short-circuit currents of 48.7 μA, and power densities exceeding 120 mW/m², demonstrating the high efficiency of gel-based TENGs. Gel materials are classified by network structure (single-, double-, and multi-network), matrix composition (hydrogels, aerogels, and ionic gels), and dielectric medium. Strategies to enhance conductivity using ionic salts, conductive polymers, and nanomaterials are discussed in relation to triboelectric output and sensing sensitivity. Morphological features such as surface roughness, porosity, and micro/nano-patterning are examined for their impact on charge generation. Application-focused sections detail the integration of gel-based TENGs in health monitoring (e.g., sweat, glucose, respiratory, and tremor sensing), environmental sensing (e.g., humidity, fire, marine, and gas detection), and tactile interfaces (e.g., e-skin and wearable electronics). Finally, we address current challenges, including mechanical durability, dehydration, and system integration, and outline future directions involving self-healing gels, hybrid architectures, and AI-assisted sensing. This review expands the subject area by synthesizing recent advances and offering a strategic roadmap for developing intelligent, sustainable, and multifunctional TENG-based sensing technologies. Full article

Sweat-based electrochemical sensors for wearable applications have attracted substantial interest due to their non-invasive nature, compact design, and ability to provide real-time data. Remarkable advancements have been made in integrating these devices into flexible platforms. While thin-film polymer substrates are frequently employed for their durability, the prolonged buildup of sweat on such materials can disrupt consistent sensing performance and adversely affect skin comfort over extended periods. Therefore, investigating lightweight, comfortable, and breathable base materials for constructing working electrodes is essential for producing flexible and breathable sweat electrochemical sensors. In this study, nylon fabric was chosen as the base material for constructing the working electrode. The electrode is prepared using a straightforward printing process, incorporating Ti₃C₂T_X MXene/polyaniline and methylene blue as modification materials in the electronic intermediary layer. The synergistic effect of the modified layer and the multi-level structure of the current collector enhances the electrochemical kinetics on the electrode surface, improves electron transmission efficiency, and enables the nylon fabric-based electrode to accurately and selectively measure glucose concentration in sweat. It exhibits a wide linear range (0.04~3.08 mM), high sensitivity (3.11 μA·mM⁻¹), strong anti-interference capabilities, and high stability. This system can monitor glucose levels and trends in sweat, facilitating the assessment of daily sugar intake for personal health management. Full article

Metabolic diseases are increasing in relevance both in health and the economy in most countries. In this direction, if gold-standard technologies are based on blood analysis, non-invasive glucose monitoring is a relevant and great challenge that has not yet been fully resolved. Sweat represents a more suitable medium for the non-invasive sensing and monitoring of glucose than other bodily fluids, such as saliva, tears, or urine. However, the measurement of glucose levels requires the use of highly precise and sensitive sensors, given the low glucose concentration in sweat. This paper provides an overview of the patent landscape related to wearable biosensors for the monitoring of glucose levels in sweat. Full article

Biosensors play a central role in the early detection of abnormal glucose levels in individuals with diabetes; therefore, the development of less invasive systems is essential. Herein, a 3D-printed colorimetric biosensor combining microneedles and chitosan nanoparticles was developed for glucose detection in sweat using machine learning. Briefly, hollow 3D-printed polylactic acid microneedles were constructed and loaded with chitosan nanoparticles encapsulating glucose oxidase, horseradish peroxidase, and the chromogenic substrate 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), resulting in the formation of the chitosan nanoparticle−microneedle patches. Glucose detection was performed colorimetrically by first incubating the chitosan nanoparticle−microneedle patches with glucose samples of varying concentrations and then by using photographs of the top side of each microneedle and a color recognition application on a smartphone. The Random Sample Consensus algorithm was used to train a simple linear regression model to predict glucose concentrations in unknown samples. The developed biosensor system exhibited a good linear response range toward glucose (0.025−0.375 mM), a low limit of detection (0.023 mM), a limit of quantification (0.078 mM), high specificity, and recovery rates ranging between 86–112%. Lastly, the biosensor was applied to glucose detection in spiked artificial sweat samples, confirming the potential of the proposed methodology for glucose detection in real samples. Full article

The increasing prevalence of diabetes mellitus necessitates the development of advanced glucose-monitoring systems that are non-invasive, reliable, and capable of real-time analysis. Wearable electrochemical biosensors have emerged as promising tools for continuous glucose monitoring (CGM), particularly through sweat-based platforms. This review highlights recent advancements in enzymatic and non-enzymatic wearable biosensors, with a specific focus on the pivotal role of nanomaterials in enhancing sensor performance. In enzymatic sensors, nanomaterials serve as high-surface-area supports for glucose oxidase (GOx) immobilization and facilitate direct electron transfer (DET), thereby improving sensitivity, selectivity, and miniaturization. Meanwhile, non-enzymatic sensors leverage metal and metal oxide nanostructures as catalytic sites to mimic enzymatic activity, offering improved stability and durability. Both categories benefit from the integration of carbon-based materials, metal nanoparticles, conductive polymers, and hybrid composites, enabling the development of flexible, skin-compatible biosensing systems with wireless communication capabilities. The review critically evaluates sensor performance parameters, including sensitivity, limit of detection, and linear range. Finally, current limitations and future perspectives are discussed. These include the development of multifunctional sensors, closed-loop therapeutic systems, and strategies for enhancing the stability and cost-efficiency of biosensors for broader clinical adoption. Full article

In enzymatic reaction glucose detection chips, the enzyme can easily dislodge from the electrode, which harms both the chip and test stability. Additionally, enzyme activity significantly decreases at low temperatures. Consequently, immobilizing the enzyme at the appropriate substrate and ambient temperature is a critical step for improving the chip. To address this issue, an electrochemical detection chip was modified using the nanomaterial MXene, known for its large specific surface area, excellent adsorption, good dispersion, and high conductivity. Meanwhile, AgNO₃ solution was added to the Ti₃C₂T_x MXene nanosheet solution, and the AgNP@MXene material was prepared by heating in a water bath. This process further enhances photothermal conversion efficiency due to the localized surface plasmon resonance effect of silver nanoparticles and MXene. This MXene-based photothermally enhanced paper chip exhibits outstanding photothermal conversion performance and sensitive photoelectrochemical responsiveness, along with good cycling stability. Moreover, improved glucose detection sensitivity at low winter temperatures has been achieved, and the ambient temperature range of the paper chip has been expanded to 25–37 °C. Full article