Non-invasive Monitoring Of Diabetes Research Articles

Enhanced Diabetes Detection and Blood Glucose Prediction Using TinyML-Integrated E-Nose and Breath Analysis: A Novel Approach Combining Synthetic and Real-World Data

Diabetes mellitus, a chronic condition affecting millions worldwide, necessitates continuous monitoring of blood glucose level (BGL). The increasing prevalence of diabetes has driven the development of non-invasive methods, such as electronic noses (e-noses), for analyzing exhaled breath and detecting biomarkers in volatile organic compounds (VOCs). Effective machine learning models require extensive patient data to ensure accurate BGL predictions, but previous studies have been limited by small sample sizes. This study addresses this limitation by employing conditional generative adversarial networks (CTGAN) to generate synthetic data from real-world tests involving 29 healthy and 29 diabetic participants, resulting in over 14,000 new synthetic samples. These data were used to validate machine learning models for diabetes detection and BGL prediction, integrated into a Tiny Machine Learning (TinyML) e-nose system for real-time analysis. The proposed models achieved an 86% accuracy in BGL identification using LightGBM (Light Gradient Boosting Machine) and a 94.14% accuracy in diabetes detection using Random Forest. These results demonstrate the efficacy of enhancing machine learning models with both real and synthetic data, particularly in non-invasive systems integrating e-noses with TinyML. This study signifies a major advancement in non-invasive diabetes monitoring, underscoring the transformative potential of TinyML-powered e-nose systems in healthcare applications.

Noninvasive Monitoring of Glycemia Level in Diabetic Patients by Wearable Advanced Biosensors.

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.

One step synthesis of Rh embedded hollow spherical WO₃ composite for enhanced acetone sensing: A promising approach for non-invasive diabetes monitoring

This study investigated the enhancement of WO₃/Rh composite gas sensors for improved acetone detection. WO₃/Rh composite samples (WO₃/Rh-1, WO₃/Rh-2, WO₃/Rh-3) were synthesized via spray pyrolysis, and materials were studied using XRD, SEM, and TEM. These analyses confirmed successful introduction of Rh nanoparticles and indicated favorable alterations in structure and morphology. Gas sensing tests with varying acetone concentrations (0.1–4 PPM, balanced with simulated exhaled gas with RH% of ∼30 %) demonstrated that Rh introduction significantly improved sensitivity and selectivity. Notably, WO₃/Rh-3 exhibited the highest performance, with enhanced response times and selectivity critical for diabetes monitoring. These results highlight the potential of WO₃/Rh sensors in medical diagnostics, offering a promising approach for the early detection of diabetes through breath analysis.

Enhanced acetone detection for non-invasive diabetes monitoring by atomic layer deposited WO3 nanoparticle on hierarchical In2O3 particles

This study addressed the critical need for non-invasive monitoring of diabetes by proposing an acetone gas sensor based on hierarchical In2O3 with atomic layer deposition (ALD)-deposited WO3 nanoparticles. The sensor fabrication involved a carefully designed process, leveraging ALD to control WO3 deposition, ensuring uniform distribution, and mitigating agglomeration. The resulting composite exhibited enhanced sensitivity, making it promising for detecting acetone, a key biomarker for diabetes. Material synthesis, including hydrothermal formation of In2O3 hierarchy particles and ALD of WO3, was meticulously conducted. Comprehensive characterizations, involving SEM, TEM, EDX, XRD, XPS, and BET, validated the successful synthesis and deposition. The sensor’s response to varying acetone concentrations (50–2000 ppb) was systematically investigated, revealing a positive correlation. The In2O3/WO3–2 sensor exhibited the highest sensitivity, attributed to the catalytic properties of WO3. The proposed sensor presented a cost-effective, sensitive, and selective solution, paving the way for non-invasive diabetes monitoring.

Polyazine nanoparticles as anchors of PQQ glucose dehydrogenase for its most efficient bioelectrocatalysis

We report on the drop-cast production of glucose biosensors based on the most efficient bioelectrocatalysis by pyrroloquinoline quinone dependent glucose dehydrogenase (PQQ GDH). To orient the enzyme upon immobilization we suggest using poly(Methylene Green) (p(MG)) nanoparticles acting as anchors. Synthesis of polymeric anchors has been carried out in course of Methylene Green electropolymerization, which allowed to tune polymer-to-monomer ratio in the drop-cast mixtures varying the monomer concentration and applying different number of potential sweep cycles. Except for elimination of electrochemical step for the electrode modification, opening the prospects for mass-production, the use of drop-cast enzyme anchors provides advantageous characteristics of the resulting biosensors. Catalytic current of PQQ GDH immobilized over p(MG) nanoparticles obtained in optimal conditions is increased only 2–2.5 times after addition of the freely diffusing mediator. Obviously, the lowest ratio of mediated-to-reagentless current points to the most efficient bioelectrocatalysis. The obtained ratio is 2.5 times lower than that for biosensors based on electropolymerized p(MG) films and practically an order of magnitude lower than that for the best reagentless sensors based on PQQ GDH immobilized over conductive nanomaterials. The achieved most efficient bioelectrocatalysis provides high sensitivity of the elaborated biosensors even at 0.0 V potential, which allows to operate them in power generation mode and control relative sweat glucose variation as a tool for non-invasive diabetes monitoring.

Zigzagging graphitic ribbons: Synthesis, characterization, and acetone vapor sensing

The fast sensing highly volatile and flammable liquids of organic compounds is an urgent scientific goal for developing devices aimed at health and safety monitoring. The high superficial area, high porosity, and electrochemical properties of carbon nanotube/fiber sponges make them promising materials for sensing organic compounds. In this study, we synthesized zigzagging graphitic ribbons (ZGR) sponges employing the aerosol-assisted chemical vapor deposition (AACVD) method at temperatures of 980 °C, 1020 °C, and 1050 °C. We characterized the morphology, composition, thermal stability, and surface chemistry of the ZGRs using various techniques. The ZGRs exhibited a defective, corrugated, and oxygen-functionalized surface. XPS characterizations revealed the presence of ether, carbonyl, carboxyl, aldehyde, and hydroxyl groups on the ZGR surface. TEM characterizations showed graphitic materials with unusual black zones attributed to sp3 carbon hybridization or strained graphite. Sensors based on ZGR sponges were used at room temperature for detecting acetone gas vapor. The electrical resistance response was monitored by varying the concentration of acetone gas vapor. The results revealed that the sensors remained stable over multiple cycles and exhibited fast response times (2–12 s). Interestingly, acetone serves as a selective breath marker for diabetes, suggesting that our sensors could be used for non-invasive diabetes monitoring. Finally, we performed van der Waals density functional theory calculations to elucidate the TEM black zones and the interaction of the acetone molecule with oxygen functional groups hosted in graphitic materials.

Pulse Power Generation Chronoamperometry as an Advanced Readout for (Bio)sensors: Application for Noninvasive Diabetes Monitoring.

We propose pulse power generation (PPG) amperometry as an advanced readout realized for Prussian blue (PB)-based (bio)sensors. In contrast to the conventional power generation mode, when the current response is generated upon continuous short-circuiting, the suggested pulse regime is fulfilled by periodic opening and shorting of the circuit. Despite PB being electroactive, the pulse readout is advantageous over conventional steady-state power generation, providing up to a 15-fold increased signal-to-background ratio as well as dramatically improved sensitivity exceeding 10 A·M-1·cm-2 for H2O2 sensors and 3.9 A·M-1·cm-2 for glucose biosensors. Such analytical performance characteristics are, most probably, achieved due to the enrichment of the diffusion layer by analyte mass transfer from the bulk upon opening of the circuit. Due to an improved sensitivity-to-background ratio, reduced flow-rate dependence, and enhanced operational stability, the regime allows reliable monitoring of blood glucose variations through sweat analysis with the on-skin device.

Simultaneous noninvasive monitoring of diabetes and hypoxia using core-shell nanozyme – oxidase enzyme biosensors

We report on advanced nanozyme-enzyme biosensors enabling noninvasive simultaneous monitoring of diabetes and hypoxia. Dip-coating with core-shell Prussian Blue – nickel hexacyanoferrate nanozymes results in both stable and sensitive hydrogen peroxide transducers. The best performance characteristics of the resulting biosensors are provided by nanoparticles of 50 nm in diameter containing 35–37 nm (ø) Prussian Blue core. The noninvasive monitor operated via continuous sweat analysis is based on a flow-through multibiosensor for the simultaneous detection of glucose and lactate. As shown, the elaborated glucose-lactate monitor being attached to the human skin surface returns the true concentration for both glucose and lactate in undiluted human sweat. The application of the wearable device incorporating developed biosensors would obviously open new horizons in noninvasive continuous monitoring of hypoxia and glycemia.

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.

Saliva Sensors

Saliva, an alternative body fluid that is easily accessible and contains trace amount of glucose can be potentially used for the noninvasive monitoring of diabetes. A positive correlation between blood glucose (BG) and stimulated salivary glucose (SG) in diabetics has been reported. The main goal of Self-Monitoring of Blood Glucose is to monitor a person's blood glucose at different time intervals which can aid a doctor in adjusting medication/insulin dose and is also useful to a patient in evaluating his/her response to therapy. Versions of saliva glucose (SG) sensor fabrication are reported. SG analysis with reference method was discussed. Salivary protein biomarkers are reported. Special strips or chips and saliva tests are presented.

Development of a Smart Glucose Monitoring Device

The prevalence of diabetes has been steadily increasing in the past few decades, in particular in low- and middle-income countries. This work develops a non-invasive diabetes monitoring device that is cost effective, stress and pain free which can measure glucose level on the spot. The developed glucose monitoring device consists of three parts; the transmitter section (light source) and the receiver section (photodiode) as well as the processor and the data display section. A Near Infrared (NIR) light is applied onto one side of the ear lobe, while a receiver on the other side receives the attenuated light and then converts the signal into a voltage signal. All these variables are then amplified, sampled, and processed inside the PIC16F877A microcontroller after which the glucose reading will be displayed on the LCD and communicated via the Bluetooth on an android application. From the results obtained, the device has successfully shown that the relationship between the output voltages from photodiode is directly proportional to the concentration of glucose. When the concentration of glucose increases, the output voltage from photodiode also increases. This proved that the concentration of glucose could be predicted using near-infrared light at a wavelength of 1550 nm.

Exhaled Breath Analysis for Diabetes Diagnosis and Monitoring: Relevance, Challenges and Possibilities.

With the global population prevalence of diabetes surpassing 463 million cases in 2019 and diabetes leading to millions of deaths each year, there is a critical need for feasible, rapid, and non-invasive methodologies for continuous blood glucose monitoring in contrast to the current procedures that are either invasive, complicated, or expensive. Breath analysis is a viable methodology for non-invasive diabetes management owing to its potential for multiple disease diagnoses, the nominal requirement of sample processing, and immense sample accessibility; however, the development of functional commercial sensors is challenging due to the low concentration of volatile organic compounds (VOCs) present in exhaled breath and the confounding factors influencing the exhaled breath profile. Given the complexity of the topic and the skyrocketing spread of diabetes, a multifarious review of exhaled breath analysis for diabetes monitoring is essential to track the technological progress in the field and comprehend the obstacles in developing a breath analysis-based diabetes management system. In this review, we consolidate the relevance of exhaled breath analysis through a critical assessment of current technologies and recent advancements in sensing methods to address the shortcomings associated with blood glucose monitoring. We provide a detailed assessment of the intricacies involved in the development of non-invasive diabetes monitoring devices. In addition, we spotlight the need to consider breath biomarker clusters as opposed to standalone biomarkers for the clinical applicability of exhaled breath monitoring. We present potential VOC clusters suitable for diabetes management and highlight the recent buildout of breath sensing methodologies, focusing on novel sensing materials and transduction mechanisms. Finally, we portray a multifaceted comparison of exhaled breath analysis for diabetes monitoring and highlight remaining challenges on the path to realizing breath analysis as a non-invasive healthcare approach.

Advances in Biosensors for Continuous Glucose Monitoring Towards Wearables.

Continuous glucose monitors (CGMs) for the non-invasive monitoring of diabetes are constantly being developed and improved. Although there are multiple biosensing platforms for monitoring glucose available on the market, there is still a strong need to enhance their precision, repeatability, wearability, and accessibility to end-users. Biosensing technologies are being increasingly explored that use different bodily fluids such as sweat and tear fluid, etc., that can be calibrated to and therefore used to measure blood glucose concentrations accurately. To improve the wearability of these devices, exploring different fluids as testing mediums is essential and opens the door to various implants and wearables that in turn have the potential to be less inhibiting to the wearer. Recent developments have surfaced in the form of contact lenses or mouthguards for instance. Challenges still present themselves in the form of sensitivity, especially at very high or low glucose concentrations, which is critical for a diabetic person to monitor. This review summarises advances in wearable glucose biosensors over the past 5 years, comparing the different types as well as the fluid they use to detect glucose, including the CGMs currently available on the market. Perspectives on the development of wearables for glucose biosensing are discussed.

Hydrothermally Grown Porous Cobalt Oxide Nanostructures for Enzyme-Less Glucose Detection

Porous transition metal oxide nanostructures are very attractive electrode materials for electrochemical glucose sensing owing to their high surface area and excellent catalytic activity. Development of a low-cost electrode with high sensitivity and selectivity towards glucose sensing is attractive for non-invasive diabetes monitoring. In this work, porous CoO nanostructured electrodes were grown on fluorine doped tin oxide (FTO) coated glass substrates using hydrothermal synthesis for enzyme-less glucose sensing. CoO porous electrodes showed glucose sensitivity ~887.49 µAmM-1cm-2, within glucose concentration range ~ 5 µM–0.425 mM. Such porous electrodes demonstrated lower detection limit ~ 1.76 µM with fast response time. To demonstrate non-invasive glucose detection, salivary glucose sensing experiments were also carried out in this study and showed glucose sensitivity ~ 854.30 µAmM-1cm-2.

Glucose biosensors for clinical and personal use

This mini-review considers the most significant achievements in glucose-sensitive electrochemical biosensors, as well as their role in clinical diagnostics and personal testing. The application of various biorecognition elements, from glucose oxidase to glucose dehydrogenases, is critically compared. The transduction principles at the heart of different types of glucose biosensors, up to third-generation biosensors (based on direct bioelectrocatalysis), are reviewed. Special attention is paid to second-generation biosensors, which provide the basis for commercial personal glucose tests (glucometers). The current challenges in non-invasive diabetes monitoring are presented.

Noninvasive monitoring of diabetes and hypoxia by wearable flow-through biosensors

Abstract Noninvasively collected sweat via clinically relevant procedure can be used for assessing the human condition, particularly for monitoring of diabetes and hypoxia. Positive correlations in variation rates, claimed as sufficient requirements for diagnostics, between glucose and lactate concentrations in sweat and the corresponding values in blood are shown. Continuous monitoring of human condition is possible only with the use of flow-through wearable devices providing a delivery of sweat to the biosensor almost immediately after excretion. Owing to both low sweat glucose content and inactivation of platinum by sweat components, the use of Prussian blue–based biosensors for wearable devices is preferable. Operation of the latter in power generation mode allows significant noise reduction and clear readout of the signal. Evaluating blood glucose through sweat analysis upon glucose tolerance test, we clearly show that humans can actually be monitored reliably via noninvasive approach.

A Prototype of a Portable Gas Analyzer for Exhaled Acetone Detection

The paper presents the development of a portable gas analyzer prototype for exhaled acetone detection, employing an application-suited gas sensor array and 3D printing technology. The device provides the functionality to monitor exhaled acetone levels, which could be used as a potential tool for non-invasive diabetes monitoring. The relationship between exhaled acetone concentrations and glucose in blood is confirmed in the literature, including research carried out by the authors. The design process is presented including a general consideration for the sensor array construction, which is the core for sensing gases, as well as requirements for the measurement chamber it is to be placed in. Moreover, the mechanical design of the 3D-printed housing is discussed to ensure the ergonomics of use as a hand-held device while keeping the hardware integrity. Also, the processing hardware is discussed to provide sufficient computing power to handle the stand-alone operation while being energy efficient, enabling long battery-powered operation. Finally, calibration and measurement, as well as the analyzer operation, are shown, validating the proposed class of exhaled acetone-detection capable meters.

Co3O4 needles on Au honeycomb as a non-invasive electrochemical biosensor for glucose in saliva

While glucose monitoring technology is widely available, the continued prevalence of diabetes around the world coupled with its debilitating effects continues to grow. The significant limitations which exist in the current technology, instils the need for materials capable of non-invasive glucose detection. In this study a unique non-enzymatic electrochemical glucose sensor was developed, utilising a gold honeycomb-like framework upon which sharp Co3O4 needles are anchored. This composite nanomaterial demonstrates excellent sensing performance in glucose concentrations ranging between 20 μM and 4 mM, exceeding the range required for non-invasive glucose sensing. In conjunction with this high sensitivity (2.014 mA mM−1·cm−2), the material possesses excellent selectivity towards glucose for commonly interfering physiological species such as uric acid and ascorbic acid. Glucose detection in synthetic saliva was then performed showing excellent capability in the low concentration range (20 μM–1 mM) for non-invasive sensing performance. Further tests showed good selectivity of the sensor in physiological contaminants commonly found in saliva such as cortisol and dopamine. This development provides excellent scope to create next-generation non-invasive diabetes monitoring platforms, with excellent performance when detecting low glucose concentrations in complex solutions such as saliva.

Noninvasive Diabetes Monitoring through Continuous Analysis of Sweat Using Flow-Through Glucose Biosensor.

We propose monitoring of diabetes through continuous analysis of undiluted sweat immediately after its excretion using a flow-through glucose biosensor. The used biosensors are based on Prussian Blue and glucose oxidase immobilized in perfluorosulfonated ionomer or gel of alkoxysilane; the resulting sensitivity with the latter reaches in batch mode 0.23 A M-1 cm-2, and the calibration range is from 1 μM to 1 mM (flow-through mode). On the basis of the glucose tolerance test known to be a clinically relevant procedure to mimic hyperglycemia, a positive correlation between the rates of glucose concentration increase in blood and in noninvasively collected sweat has been observed ( r = 0.75). The observed correlation between sweat and blood considering low-molecular weight metabolites is even better than that observed previously between capillary and vein blood, confirming diagnostic value of sweat for diabetes monitoring. The dynamics of sweat glucose concentration, recorded by means of the proposed biosensor, is in a good accordance with the dynamics of blood glucose content without any time delay, thus offering a prospect for noninvasive monitoring of diabetes.

Highly selective and stable acetone sensor based on chemically prepared bismuth ferrite nanoparticles

Excellent acetone sensing property with high selectivity and long-term stability has been observed in single phase crystalline bismuth ferrite (BFO) nanoparticles. This phase pure BFO nanoparticles were synthesised via a simple sol-gel method and well characterized using various sophisticated instruments. BFO nanoparticles exhibit remarkable response (S = 1.8) towards 1 ppm of acetone at an operating temperature of 350 °C. The prepared sensor is extremely selective towards acetone among different gas analyte and also insensitive to moisture which can be attributed to a particular operating temperature (350 °C). Additionally, other important features of the sensor include high reproducibility and long-term stability for around 1 year. Displayed efficient sensing performance of these BFO nanoparticles-based sensors could be a potential candidate for different application e. g non-invasive monitoring of diabetes.