Search Results (49)

Sweat analysis represents an emerging non-invasive approach for health monitoring, yet its practical application is hindered by challenges such as insufficient natural sweat secretion and inefficient collection. To overcome these limitations, this study develops a hydrogel sheet composed of agarose and glycerol, which efficiently facilitates resting sweat collection without external stimulation when integrated into the microfluidic channels of a sweat-sensing patch. The microfluidic sweat-sensing patch, fabricated with laser-cut technology, features a sandwich structure that enables the measurement of sweat rate and chloride ion concentration while minimizing interference from electrochemical reactions. Additionally, a colorimetric module utilizing glucose oxidase and peroxidase is also integrated into the platform for cost-effective and efficient glucose detection through a color change that can be quantified via RGB analysis. The hydrogel interface, characterized by its optimal thickness and water content, exhibits superior absorption capability for efficient sweat collection and retention, with a negligible effect on the dilution of sweat components. This hydrogel-interfaced microfluidic platform demonstrates high efficiency in sweat collection and multi-biomarker analysis, offering a non-invasive, real-time solution for health monitoring. Its low-cost and wearable design highlights its potential for broad applications in personalized healthcare. Full article

Microphysiological systems (MPS) incorporating microfluidic technologies offer improved physiological relevance and real-time analysis for cell-based assays, but often lack non-invasive monitoring capabilities. Addressing this gap, we developed a microfluidic cell-based assay platform integrating an electrochemical biosensor for real-time, non-invasive monitoring of kinetic cell status through glucose consumption. The platform addresses the critical limitations of traditional cell assays, which typically rely on invasive, discontinuous methods. By combining enzyme-modified platinum electrodes within a microfluidic device, our biosensor can quantify dynamic changes in glucose concentration resulting from cellular metabolism. We have integrated a calibration function that corrects sensor drift, ensuring accurate and prolonged short-term measurement stability. In the validation experiments, the system successfully monitored glucose levels continuously for 20 h, demonstrating robust sensor performance and reliable glucose concentration predictions. Furthermore, in the cell toxicity assays using HepG2 cells exposed to varying concentrations of paraquat, the platform detected changes in glucose consumption, effectively quantifying the cellular toxicity responses. This capability highlights the device’s potential for accurately assessing the dynamic physiological conditions of the cells. Overall, our integrated platform significantly enhances cell-based assays by enabling continuous, quantitative, and non-destructive analysis, positioning it as a valuable tool for future drug development and biomedical research. Full article

This paper presents a fully 3D-printed microfluidic microwave sensor based on substrate-integrated waveguide (SIW) technology for detecting glucose levels in liquid, aimed at monitoring diabetic patients. The sensor’s design features a circular SIW cavity with an integrated sample holder placed in the cavity’s center, maximizing the electric field disturbance from the liquid under test (LUT). Operating in the TM₀₁₀ mode at a resonance frequency around 5.740 GHz, the sensor detects glucose concentrations by measuring resonance frequency shifts in the S₁₁ reflection response across glucose levels. A conductive sheath partially covers the sample holder to enhance sensitivity and improve the limit of detection (LOD) by increasing field penetration into the LUT. Fabricated using an additive manufacturing electronics (AMEs) method, the sensor is produced in a single pass without post-processing. The experimental validation confirms its high sensitivity of 1.218 MHz/(mg/dL) and a low limit of detection of 0.774 mg/dL in the glucose concentration range (10–200 mg/dL), reflecting typical Type 2 diabetes levels. The key advantages of the sensor include its compactness, enhanced sensitivity and limit of detection, innovative manufacturing, and cost-effectiveness, supporting its potential as a non-invasive glucose monitoring tool. This study establishes a proof of concept for the in vitro measurement of glucose, demonstrating the sensor’s ability to provide accurate and reliable results in a controlled environment. Full article

Living bodies emit mid-infrared light (wavelength band centered at approximately 10 µm) with a temperature-dependent intensity. Several studies have shown the possibility of measuring blood glucose levels using the mid-infrared emission of living bodies, and we have demonstrated non-invasive blood glucose measurements through distant wrist measurements (wavelength 8–14 µm) by mid-infrared passive spectroscopic imaging. However, it is not clear why blood glucose is detectable, as there is no formula that shows the effect of material thickness and concentration on emission intensity. In this study, we developed a principle for understanding glucose detection by proposing that an emission integral effect underpins the changes in emission intensity with substance thickness and absorption coefficient. We demonstrate the emission integral effect by measuring the spectral radiance of polypropylene with different thicknesses using mid-infrared passive spectroscopic imaging. The simulation results based on the emission integral effect indicate that in living bodies, dilute components such as glucose are easier to identify than components with high concentrations. Mid-infrared passive spectroscopic imaging offers potential innovative solutions for measuring various substances from a distance, with the emission integral effect acting as the basic working principle. Full article

With improvements in medical environments and the widespread use of smartphones, interest in wearable biosensors for continuous body monitoring is growing. We developed a wearable multiplexed bio-sensing system that non-invasively monitors body fluids and integrates with a smartphone application. The system includes sensors, readout circuits, and a microcontroller unit (MCU) for signal processing and wireless communication. Potentiometric and amperometric measurement methods were used, with calibration capabilities added to ensure accurate readings of analyte concentrations and temperature. Laser-induced graphene (LIG)-based sensors for glucose, lactate, Na⁺, K⁺, and temperature were developed for fast, cost-effective production. The LIG electrode’s 3D porous structure provided an active surface area 16 times larger than its apparent area, resulting in enhanced sensor performance. The glucose and lactate sensors exhibited high sensitivity (168.15 and 872.08 μAmM⁻¹cm⁻², respectively) and low detection limits (0.191 and 0.167 μM, respectively). The Na⁺ and K⁺ sensors demonstrated sensitivities of 65.26 and 62.19 mVdec⁻¹, respectively, in a concentration range of 0.01–100 mM. Temperature sensors showed an average rate of resistance change per °C of 0.25%/°C, within a temperature range of 20–40 °C, providing accurate body temperature monitoring. Full article

With the continuous advancement of contemporary medical technology, an increasing number of individuals are inclined towards self-monitoring their physiological health information, specifically focusing on monitoring blood glucose levels. However, as an emerging flexible sensing technique, continuous and non-invasive monitoring of glucose in sweat offers a promising alternative to conventional invasive blood tests for measuring blood glucose levels, reducing the risk of infection associated with blood testing. In this study, we fabricated a flexible and wearable electrochemical enzyme sensor based on a two-dimensional Ti₃C₂T_x MXene nanosheets and coral-like polyaniline (PANI) binary nanocomposite (denoted as Ti₃C₂T_x/PANI) for continuous, non-invasive, real-time monitoring of sweat glucose. The exceptional conductivity of Ti₃C₂T_x MXene nanosheets, in conjunction with the mutual doping effect facilitated by coral-like PANI, significantly enhances electrical conductivity and specific surface areas of Ti₃C₂T_x/PANI. Consequently, the fabricated sensor exhibits remarkable sensitivity (25.16 μA·mM⁻¹·cm⁻²), a low detection limit of glucose (26 μM), and an extensive detection range (0.05 mM ~ 1.0 mM) in sweat. Due to the dense coral-like structure of Ti₃C₂T_x/PANI binary nanocomposite, a larger effective area is obtained to offer more active sites for enzyme immobilization and enhancing enzymatic catalytic activity. Moreover, the sensor demonstrates exceptional mechanical performance, enabling a 60° bend in practical applications, thus satisfying the rigorous demands of human sweat detection applications. The results obtained from continuous 60 min in vitro monitoring of sweat glucose levels demonstrate a robust correlation with the data of blood glucose levels collected by a commercial glucose meter. Furthermore, the fabricated Ti₃C₂T_x/PANI/GOx sensor demonstrated agreement with HPLC findings regarding the actual concentration of added glucose. This study presents an efficient and practical approach for the development of a highly reliable MXene glucose biosensor, enabling stable and long-term monitoring of glucose levels in human sweat. Full article

We report on the possibility of noninvasive diabetes monitoring through continuous analysis of sweat. The prediction of the blood glucose level in diabetic patients is possible on the basis of their sweat glucose content due to the positive correlation discovered. The ratio between the blood glucose and sweat glucose concentrations for a certain diabetic subject is stable within weeks, excluding requirements for frequent blood probing. The glucose variations in sweat display allometric (non-linear) dependence on those in blood, allowing more precise blood glucose estimation. Selective (avoiding false-positive responses) and sensitive (sweat glucose is on average 30–50 times lower) detection is possible with biosensors based on the glucose oxidase enzyme coupled with a Prussian Blue transducer. Reliable glucose detection in just secreted sweat would allow noninvasive monitoring of the glycemia level in diabetic patients. Full article

The objective of the present study is to analyze the urinary metabolome profile of patients with obesity and overweight and relate it to different obesity profiles. This is a prospective, cross-sectional study in which patients with a body mass index (BMI) ≥25 kg/m were selected. Anthropometric data were assessed by physical examination and body composition was obtained by bioimpedance (basal metabolic rate, body fat percentile, skeletal muscle mass, gross fat mass and visceral fat). Urine was collected for metabolomic analysis. Patients were classified according to abdominal circumference measurements between 81 and 93, 94 and 104, and >104 cm; visceral fat up to 16 kilos and less than; and fat percentiles of <36%, 36–46% and >46%. Spectral alignment of urinary metabolite signals and bioinformatic analysis were carried out to select the metabolites that stood out. NMR spectrometry was used to detect and quantify the main urinary metabolites and to compare the groups. Seventy-five patients were included, with a mean age of 38.3 years, and 72% females. The urinary metabolomic profile showed no differences in BMI, abdominal circumference and percentage of body fat. Higher concentrations of trigonelline (p = 0.0488), sarcosine (p = 0.0350) and phenylalanine (p = 0.0488) were associated with patients with visceral fat over 16 kg. The cutoff points obtained by the ROC curves were able to accurately differentiate between patients according to the amount of visceral fat: sarcosine 0.043 mg/mL; trigonelline 0.068 mg/mL and phenylalanine 0.204 mg/mL. In conclusion, higher visceral fat was associated with urinary levels of metabolites such as sarcosine, related to insulin resistance; trigonelline, related to muscle mass and strength; and phenylalanine, related to glucose metabolism and abdominal fat. Trigonelline, sarcosine and phenylalanine play significant roles in regulating energy balance and metabolic pathways essential for controlling obesity. Our findings could represent an interesting option for the non-invasive estimation of visceral fat through biomarkers related to alterations in metabolic pathways involved in the pathophysiology of obesity. Full article

Non-invasive continuous health monitoring has become feasible with the advancement of biosensors. While monitoring certain biomarkers such as heart rate or skin temperature are now at a certain maturity, monitoring molecular biomarkers is still challenging. Progress has been shown in sampling, measurement, and interpretation of data toward non-invasive molecular sensors that can be integrated into daily wearable items. Toward this goal, this paper explores the potential of embroidered interdigitated transducer (IDT)-based sensors for non-invasive, continuous monitoring of human biomarkers, particularly glucose levels, in human sweat. The study employs innovative embroidery techniques to create flexible fabric-based sensors with gold-coated IDTs. In controlled experiments, we have shown the variation of glucose concentration in water can be wirelessly detected by tracking the resonant frequency of the embroidered sensors. The current sensors operate at 1.8 GHz to 2 GHz and respond to the change in glucose concentration with a sensitivity of $0.17$ MHz/(mg/dL). The embroidered IDT-based sensors with wireless sensing will be a new measurement modality for molecular wearable sensors. The establishment of a wireless sensing mechanism for embroidered IDT-based sensors will be followed by an investigation of sweat for molecular detection. This will require adding functionalities for sampling and interpretation of acquired data. We envisage the embroidered IDT-based sensors offer a unique approach for seamless integration into clothing, paving the way for personalised, continuous health data capture. Full article

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. Full article

Diabetes is a common disease that seriously endangers human health. Continuous glucose monitoring (CGM) is important for the prevention and treatment of diabetes. Glucose-sensing photonic nanochains (PNCs) have the advantages of naked-eye colorimetric readouts, short response time and noninvasive detection of diabetes, showing immense potential in CGM systems. However, the developed PNCs cannot disperse in physiological environment at the pH of 7.4 because of their poor hydrophilicity. In this study, we report a new kind of PNCs that can continuously and reversibly detect the concentration of glucose (C_g) in physiological environment at the pH of 7.4. Polyacrylic acid (PAA) added to the preparation of PNCs forms hydrogen bonds with polyvinylpyrrolidone (PVP) in Fe₃O₄@PVP colloidal nanoparticles and the hydrophilic monomer N-2-hydroxyethyl acrylamide (HEAAm), which increases the content of PHEAAm in the polymer shell of prepared PNCs. Moreover, 4-(2-acrylamidoethylcarbamoyl)-3-fluorophenylboronic acid (AFPBA), with a relatively low pKa value, is used as the glucose-sensing monomer to further improve the hydrophilicity and glucose-sensing performances of PNCs. The obtained Fe₃O₄@(PVP-PAA)@poly(AFPBA-co-HEAAm) PNCs disperse in artificial serum and change color from yellow-green to red when C_g increases from 3.9 mM to 11.4 mM, showing application potential for straightforward CGM. Full article

Silicon nanotubes (Si NTs) have a unique structure among the silicon nanostructure family, which is useful for diverse applications ranging from therapeutics to lithium storage/recycling. Their well-defined structure and high surface area make them ideal for sensing applications. In this work, we demonstrate the formation of Au nanoparticles (NPs) functionalized with 4-Mercaptophenylboronic acid (MPBA) on porous Si NTs (pSi NTs) fabricated using ZnO nanowires as a template. The system was characterized, and the proposed structure was confirmed using scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). Varying glucose concentrations in phosphate-buffered saline (PBS) (0.5–80 mM) were introduced to the Si NT nanocomposite system. The glucose is detectable at low concentrations utilizing surface-enhanced Raman spectroscopy (SERS), which shows a concentration-dependent peak shift in the benzene ring breathing mode (~1071 cm⁻¹) of MPBA. Complementing these measurements are simulations of the Raman hot spots associated with plasmonic enhancement of the Au NPs using COMSOL. This biocompatible system is envisioned to have applications in nanomedicine and microfluidic devices for real-time, non-invasive glucose sensing. Full article

Background and Objectives: The physiological changes that take place after the ingestion of a meal are largely controlled by insulin and can reflect changes in the response to this hormone. Different studies have reported metabolic differences among groups of subjects in the postprandial state, while failing at detecting differences in the fasted state. Dry blood spots (DBS) are a non-invasive tool for sampling and storing small volumes of biological fluids, useful in biomarker discovery studies or the analysis of responses to interventions. The aim of this study was to identify markers of dysregulated glucose postprandial metabolism in a clinical study conducted remotely, using DBS as a sampling strategy. Methods: 100 males and females (18–60 y.o., BMI: 18.5–34.9 kg/m²) went through a dietary challenge based on the intake of an energy-dense meal (75 g glucose, 60 g canola oil and 20 g casein) and blood sampling (as DBS) at 0, 30, 60, 90, 120 and 150 min. Capillary glycaemia was monitored using a portable glucometer. DBS samples were analyzed in an untargeted metabolomic platform using gas chromatography coupled to mass spectrometry. Results: The outcomes of the study confirm the viability of the remotely executed clinical study. Performing the dietary challenges at the homes of the study subjects did not interfere with the quality of the data collected. The subjects were sorted according to glucose AUC and divided into two groups. The blood levels of markers of insulin resistance such as branched-chain amino acids and tyrosine were increased in the subjects with the larger glucose AUC. The concentration of metabolites associated with glucose metabolism (monosaccharides, lactate and Krebs cycle metabolites) were also increased is the blood of individuals with higher AUC, in comparison to those with lower AUC values. Moreover, 30 other unidentified metabolites also displayed higher concentrations in the DBS collected from individuals with larger AUC of glucose, indicating a number of compounds with marker quality that remain to be identified. Discussion: This is the first clinical study that employed DBS as a sampling strategy during a dietary challenge and successfully described a metabolic signature of glucose metabolism dysregulation. Full article

Diabetes mellitus is a widespread chronic metabolic disorder that requires regular blood glucose level surveillance. Current invasive techniques, such as finger-prick tests, often result in discomfort, leading to infrequent monitoring and potential health complications. The primary objective of this study was to design a novel, portable, non-invasive system for diabetes detection using breath samples, named DiabeticSense, an affordable digital health device for early detection, to encourage immediate intervention. The device employed electrochemical sensors to assess volatile organic compounds in breath samples, whose concentrations differed between diabetic and non-diabetic individuals. The system merged vital signs with sensor voltages obtained by processing breath sample data to predict diabetic conditions. Our research used clinical breath samples from 100 patients at a nationally recognized hospital to form the dataset. Data were then processed using a gradient boosting classifier model, and the performance was cross-validated. The proposed system attained a promising accuracy of 86.6%, indicating an improvement of 20.72% over an existing regression technique. The developed device introduces a non-invasive, cost-effective, and user-friendly solution for preliminary diabetes detection. This has the potential to increase patient adherence to regular monitoring. Full article

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