Current development in non-invasive glucose monitoring

Blood glucose monitoring devices for type 1 diabetes: a journey from the food and drug administration approval to market availability

Blood glucose monitoring constitutes a pivotal element in the clinical management of Type 1 diabetes (T1D), a globally escalating metabolic disorder. Continuous glucose monitoring (CGM) devices have demonstrated efficacy in optimizing glycemic control, mitigating adverse health outcomes, and augmenting the overall quality of life for individuals afflicted with T1D. Recent progress in the field encompasses the refinement of electrochemical sensors, which enhances the effectiveness of blood glucose monitoring. This progress empowers patients to assume greater control over their health, alleviating the burdens associated with their condition, and contributing to the overall alleviation of the healthcare system. The introduction of novel medical devices, whether derived from existing prototypes or originating as innovative creations, necessitates adherence to a rigorous approval process regulated by the Food and Drug Administration (FDA). Diverse device classifications, stratified by their associated risks, dictate distinct approval pathways, each characterized by varying timelines. This review underscores recent advancements in blood glucose monitoring devices primarily based on electrochemical sensors and elucidates their regulatory journey towards FDA approval. The advent of innovative, non-invasive blood glucose monitoring devices holds promise for maintaining stringent glycemic control, thereby preventing T1D-associated comorbidities, and extending the life expectancy of affected individuals.

Smart salt-responsive thread for highly sensitive microfluidic glucose detection in sweat

Thread-based microfluidic colorimetric sensors have been deemed a potential tool that may be incorporated into textiles for non-invasive sweat analysis. Nevertheless, their poor performance significantly limits their practical uses in sweat glucose detection down to 20 μM. Herein, a microfluidic glucose sensing device containing a salt-responsive thread is developed for the highly sensitive detection of glucose in human sweat. By grafting a zwitterionic polymer brush-which could react to ionic strength by changing the conformation of the polymer chains from the collapsing state to the stretching state-onto the cotton thread, the salt-responsive thread was created. Compared to the pristine cotton thread, the modified thread has better ion-capture capabilities, a more noticeable swelling effect, and a higher ability to absorb water. These enable a significant enrichment of glucose when the saline solution passes through it. The salt-responsive thread was employed to construct a thread/paper-based microfluidic sensing device for the monitoring of glucose in artificial sweat, exhibiting a sensitivity of -0.255 μM-1 and a detection limit of 14.7 μM. In comparison to the pristine cotton thread-based device, the performance is significantly superior. Using a hydrophobic fabric and salt-responsive threads, a glucose-sensing headband was prepared for on-body sweat glucose monitoring. With the use of a smartphone-based image analysis system, the headband can detect the concentration of glucose in a volunteer's perspiration. Using the thread-based salt-responsive zwitterionic polymer brush might offer a novel approach to creating wearable sweat sensors with extremely high sensitivity.

Non-invasive electrochemical immunosensor for reverse iontophoretic determination of cardiac troponins (cTnT & cTnI) in a simulated artificial skin model. Significance of raw DPV and CV data for chemometric discrimination

Electrochemical immunosensors coupled with reverse iontophoresis (RI) for noninvasive determination of cardiac troponins were developed and validated according to ICH Q2 (R1) guideline. Linearity was in 0.01-10 and 100-500 ng/mL ranges. LODs (ng/mL) were in 6-25 × 10-4, while LOQs (μg/mL) were in 18-7.5 × 10-4 range. Chemometric evaluation was performed on raw data simply by principle component analysis and cluster analysis to discriminate stages of immunosensors. This is the first demonstration of RI determination of cardiac troponins so far. Findings of the current manuscript have great potential to develop point of care diagnostic systems for major cardiac events, where high sensitivity and specificity are required.

Evaluation of a Continuous Blood Glucose Monitor: A Novel and Non-Invasive Wearable Using Bioimpedance Technology

BACKGROUND

Frequent blood glucose level (BGL) monitoring is essential for effective diabetes management. Poor compliance is common due to the painful finger pricking or subcutaneous lancet implantation required from existing technologies. There are currently no commercially available non-invasive devices that can effectively measure BGL. In this real-world study, a prototype non-invasive continuous glucose monitoring system (NI-CGM) developed as a wearable ring was used to collect bioimpedance data. The aim was to develop a mathematical model that could use these bioimpedance data to estimate BGL in real time.

METHODS

The prototype NI-CGM was worn by 14 adult participants with type 2 diabetes for 14 days in an observational clinical study. Bioimpedance data were collected alongside paired BGL measurements taken with a Food and Drug Administration (FDA)-approved self-monitoring blood glucose (SMBG) meter and an FDA-approved CGM. The SMBG meter data were used to improve CGM accuracy, and CGM data to develop the mathematical model.

RESULTS

A gradient boosted model was developed using a randomized 80-20 training-test split of data. The estimated BGL from the model had a Mean Absolute Relative Difference (MARD) of 17.9%, with the Parkes error grid (PEG) analysis showing 99% of values in clinically acceptable zones A and B.

CONCLUSIONS

This study demonstrated the reliability of the prototype NI-CGM at collecting bioimpedance data in a real-world scenario. These data were used to train a model that could successfully estimate BGL with a promising MARD and clinically relevant PEG result. These results will enable continued development of the prototype NI-CGM as a wearable ring.

A Concise and Systematic Review on Non-Invasive Glucose Monitoring for Potential Diabetes Management

The current standard of diabetes management depends upon the invasive blood pricking techniques. In recent times, the availability of minimally invasive continuous glucose monitoring devices have made some improvements in the life of diabetic patients however it has its own limitations which include painful insertion, excessive cost, discomfort and an active risk due to the presence of a foreign body under the skin. Due to all these factors, the non-invasive glucose monitoring has remain a subject of research for the last two decades and multiple techniques of non-invasive glucose monitoring have been proposed. These proposed techniques have the potential to be evolved into a wearable device for non-invasive diabetes management. This paper reviews research advances and major challenges of such techniques or methods in recent years and broadly classifies them into four types based on their detection principles. These four methods are: optical spectroscopy, photoacoustic spectroscopy, electromagnetic sensing and nanomaterial based sensing. The paper primarily focuses on the evolution of non-invasive technology from bench-top equipment to smart wearable devices for personalized non-invasive continuous glucose monitoring in these four methods. With the rapid evolve of wearable technology, all these four methods of non-invasive blood glucose monitoring independently or in combination of two or more have the potential to become a reality in the near future for efficient, affordable, accurate and pain-free diabetes management.

Large Area Patterning of Highly Reproducible and Sensitive SERS Sensors Based on 10-nm Annular Gap Arrays

Applicable surface-enhanced Raman scattering (SERS) active substrates typically require low-cost patterning methodology, high reproducibility, and a high enhancement factor (EF) over a large area. However, the lack of reproducible, reliable fabrication for large area SERS substrates in a low-cost manner remains a challenge. Here, a patterning method based on nanosphere lithography and adhesion lithography is reported that allows massively parallel fabrication of 10-nm annular gap arrays on large areas. The arrays exhibit excellent reproducibility and high SERS performance, with an EF of up to 10⁷. An effective wearable SERS contact lens for glucose detection is further demonstrated. The technique described here extends the range of SERS-active substrates that can be fabricated over large areas, and holds exciting potential for SERS-based chemical and biomedical detection.

Imaging with Raman photons: a novel use of mixed-mode spectroscopy

Surface enhanced Raman spectroscopy is today an established technique used for chemical fingerprinting. Here, we showcase an engineered hierarchical substrate, in which the plasmonically active regions, restricted to a micron scale, two dimensional hexagonal pattern are examined. Spatial variation of the enhanced Raman signal from any analyte, uniformly coating the substrate, consequently bears a high registry with the underlying pattern. This spatially contrasted enhancement allows optical imaging of the 2D pattern solely using the Raman scattered photons from the analyte. While the pattern brightness and contrast determine analyte identification and detection sensitivity, hyperspectral imaging can be exploited for increasing specificity. Proof of concept demonstration of the technique is carried out via the acquisition of Raman images with rhodamine and fluorescein dyes and then applied to detect glucose in 40 mM concentration. The large area optical imaging and the requirement of long-range uniformity in the detected patterns for positive analyte detection, is implemented using a machine learning based pattern recognition protocol which also increases the statistical confidence of detection. This simultaneous, large area signal detection sacrifices continuous spectral information at the cost of speed, reproducibility and minimising human error via automation of detection in the hyperspectral imaging technique presented here.

Development of a Noninvasive Blood Glucose Monitoring System Prototype: Pilot Study

Background

Diabetes mellitus is a severe disease characterized by high blood glucose levels resulting from dysregulation of the hormone insulin. Diabetes is managed through physical activity and dietary modification and requires careful monitoring of blood glucose concentration. Blood glucose concentration is typically monitored throughout the day by analyzing a sample of blood drawn from a finger prick using a commercially available glucometer. However, this process is invasive and painful, and leads to a risk of infection. Therefore, there is an urgent need for noninvasive, inexpensive, novel platforms for continuous blood sugar monitoring.

Objective

Our study aimed to describe a pilot test to test the accuracy of a noninvasive glucose monitoring prototype that uses laser technology based on near-infrared spectroscopy.

Methods

Our system is based on Raspberry Pi, a portable camera (Raspberry Pi camera), and a visible light laser. The Raspberry Pi camera captures a set of images when a visible light laser passes through skin tissue. The glucose concentration is estimated by an artificial neural network model using the absorption and scattering of light in the skin tissue. This prototype was developed using TensorFlow, Keras, and Python code. A pilot study was run with 8 volunteers that used the prototype on their fingers and ears. Blood glucose values obtained by the prototype were compared with commercially available glucometers to estimate accuracy.

Results

When using images from the finger, the accuracy of the prototype is 79%. Taken from the ear, the accuracy is attenuated to 62%. Though the current data set is limited, these results are encouraging. However, three main limitations need to be addressed in future studies of the prototype: (1) increase the size of the database to improve the robustness of the artificial neural network model; (2) analyze the impact of external factors such as skin color, skin thickness, and ambient temperature in the current prototype; and (3) improve the prototype enclosure to make it suitable for easy finger and ear placement.

Conclusions

Our pilot study demonstrates that blood glucose concentration can be estimated using a small hardware prototype that uses infrared images of human tissue. Although more studies need to be conducted to overcome limitations, this pilot study shows that an affordable device can be used to avoid the use of blood and multiple finger pricks for blood glucose monitoring in the diabetic population.

Spectral Methods for Response Enhancement of Microwave Resonant Sensors in Continuous Non-Invasive Blood Glucose Monitoring

In this paper, the performance of three recent algorithms for the frequency-response enhancement of microwave resonant sensors are compared. The first one, a single-step algorithm, is based on a couple of direct-inverse Fourier transforms, giving a densely sampled response as a result. The second algorithm exploits an iterative procedure to progressively restricts the frequency response. The final one is based on the super-resolution MUSIC algorithm. The comparison is carried out through a Monte Carlo analysis. In particular, synthetic signals are firstly exploited to mimic the frequency response of a resonant microwave sensor. Then, experimental data collected from water-glucose solutions are adopted as validation test for potential applications in noninvasive blood-glucose monitoring.

Effect of caffeine on the possible amelioration of diabetic neuropathy: A spectroscopic study

IMPORTANCE

One of the consequential and alarming complications of diabetes mellitus is diabetic neuropathy (DN). DN is assured to be caused chiefly by excess sorbitol levels in the body. The harmful consequences of DN alike peripheral nerve damage with extremity ulcers may be dodged with timely detection and treatment. The therapeutic methods for DN are scarce and expensive. Therefore economic and user friendly methodologies to prevent acquiring the disease need proper attention.

OBJECTIVE

The present research has been conducted (1) to analyse the levels of sorbitol in diabetic blood samples and compare them with non-diabetic ones and (2) to study the reduction in sorbitol levels upon addition of an important biochemical compounds caffeine in both sample groups.

RESEARCH DESIGN, SETTING, PARTICIPANTS AND METHOD

Sorbitol-caffeine interaction analysis of blood samples of 16 patients with type 2 diabetes from KPC Medical College, Kolkata, India was made. The spectroscopic analysis and their interpretations were compared with 16 healthy subjects.

MAIN OUTCOMES AND MEASURES

Present work describes that caffeine can be helpful in reducing the sorbitol level in diabetics, so the chances of development and progression of diabetic neuropathy can be controlled with the introduction of caffeine.

RESULTS

A total number of 32 blood samples of patients (aged 35-70 years); mean age ranges were 52.06 ± 2.68 and 53.50 ± 2.66 years for non-diabetic and diabetic ones respectively, glucose and sorbitol screening examination were done by enzymatic methodologies where concentrations were assessed by means of either absorption or fluorescence spectroscopy. The calibration range was 18.2-1119.3 mg/dL (Linear regression analysis r² = 0.996). The sensitivity of this screening program in detecting DN with the healthy adults has been inquired and found efficient. Results of fasting insulin analyses have also been analysed for HOMA-IR (homeostasis model assessment - insulin resistance) and HOMA-B (homeostasis model assessment - pancreatic β cell function) values. Statistical significance of the results in non-diabetic and diabetic groups were performed and found to be statistically significant.

CONCLUSIONS

We have defined the relationship between blood glucose level, insulin level, sorbitol and caffeine in human body and utilized them in the plausible remediation of DN.

Products for Monitoring Glucose Levels in the Human Body With Noninvasive Optical, Noninvasive Fluid Sampling, or Minimally Invasive Technologies

BACKGROUND

Conventional home blood glucose measurements require a sample of blood that is obtained by puncturing the skin at the fingertip. To avoid the pain associated with this procedure, there is high demand for medical products that allow glucose monitoring without blood sampling. In this review article, all such products are presented.

METHODS

In order to identify such products, four different sources were used: (1) PubMed, (2) Google Patents, (3) Diabetes Technology Meeting Startup Showcase participants, and (4) experts in the field of glucose monitoring. The information obtained were filtered by using two inclusion criteria: (1) regulatory clearance, and/or (2) significant coverage in Google News starting in the year 2016, unless the article indicated that the product had been discontinued. The identified bloodless monitoring products were classified into three categories: (1) noninvasive optical, (2) noninvasive fluid sampling, and (3) minimally invasive devices.

RESULTS

In total, 28 noninvasive optical, 6 noninvasive fluid sampling, and 31 minimally invasive glucose monitoring products were identified. Subsequently, these products were characterized according to their regulatory, technological, and consumer features. Products with regulatory clearance are described in greater detail according to their advantages and disadvantages, and with design images.

CONCLUSIONS

Based on favorable technological features, consumer features, and other advantages, several bloodless products are commercially available and promise to enhance diabetes management. Paths for future products are discussed with an emphasis on understanding existing barriers related to both technical and non-technical issues.

Development of red genetically encoded biosensor for visualization of intracellular glucose dynamics

Glucose is the main source of energy for organisms, and it is important to understand the spatiotemporal dynamics of intracellular glucose. Single fluorescent protein-based glucose indicators, named "Red Glifons" have been developed that apply to live-cell and dual-color imaging. These indicators exhibited more than 3-fold increase in fluorescence intensity in the presence of 10 mM glucose. The two Red Glifons developed have different half-maximal effective concentration (EC₅₀) values for glucose (300 μM and 3,000 μM) and are able to monitor a wide range of glucose dynamics. Red Glifon combined with green indicators allowing visualization of the interplay between glucose and ATP, lactate, or pyruvate. Glucose influx in the pharyngeal muscle of Caenorhabditis elegans, enteroendocrine cells, and human iPS cell-derived cardiac myocytes was observed using the Red Glifons. Thus these red glucose indicators serve as a multi-color imaging toolkit for investigating complex interactions in energy metabolism.

Catalytic effects of magnetic and conductive nanoparticles on immobilized glucose oxidase in skin sensors

Wearable skin sensors is a promising technology for real-time health care monitoring. They are of particular interest for monitoring glucose in diabetic patients. The concentration of glucose in sweat can be more than two orders of magnitude lower than in blood. In consequence, the scientific and technological efforts are focused in developing new concepts to enhance the sensitivity, decrease the limit of detection (LOD) and reduce the response time (RT) of glucose skin sensors. This work explores the effect of adsorbed superparamagnetic magnetite nanoparticles (MNPs) and conductive nanoparticles (CNPs) on carbon nanotube substrates (CNTs) used to immobilize glucose oxidase enzyme in the working electrode of skin sensors. MNPs and CNPs are made of magnetite and gold, respectively. The performance of the sensors was tested in standard buffer solution, artificial sweat, fresh sweat and on the skin of a healthy volunteer during an exercise session. In the case of artificial sweat, the presence of MNPs accelerated the RT from 7 to 5 s at the expense of increasing the LOD from 0.017 to 0.022 mM with slight increase of the sensitivity from 4.90 to 5.09μAm M^-1cm^-2. The presence of CNPs greatly accelerated the RT from 7 to 2 s and lowered the LOD from 0.017 to 0.014 mM at the expense of a great diminution of the sensitivity from 4.90 to 4.09μAm M^-1cm^-2. These effects were explained mechanistically by analyzing the changes in the concentration of free oxygen and electrons promoted by MNPs and CNPs in the CNTs and its consequences on the the glucose oxidation process.

Blood glucose detection based on Teager-Kaiser main energy of photoacoustic signal

Real-time blood glucose detection is an essential tool for diabetes monitoring. Non-invasive blood glucose detection technology is one of the current research hotspots in this field. Previous research mainly focused on improving the system's detection capability to obtain signals with low signal-to-noise ratio and high quality, and simple methods are often used in signal processing. Moreover, photoacoustic signal simulation also simplifies the influence of the transmission medium on the signal. In the present study, we built a new simulation model which considers human skin, blood, and the detector's limitations, to obtain a more practical photoacoustic signal. We then proposed a blood glucose detection algorithm based on Teager-Kaiser main energy (TKME) to overcome noise and medium interference and achieve a high detection accuracy at low SNR. Finally, the simulation and actual data were utilised during the experiment, and the detection error was 15 mg/dL (SNR = 10 dB).

Review of Recent Microwave Planar Resonator-Based Sensors: Techniques of Complex Permittivity Extraction, Applications, Open Challenges and Future Research Directions

Recent developments in the field of microwave planar sensors have led to a renewed interest in industrial, chemical, biological and medical applications that are capable of performing real-time and non-invasive measurement of material properties. Among the plausible advantages of microwave planar sensors is that they have a compact size, a low cost and the ease of fabrication and integration compared to prevailing sensors. However, some of their main drawbacks can be considered that restrict their usage and limit the range of applications such as their sensitivity and selectivity. The development of high-sensitivity microwave planar sensors is required for highly accurate complex permittivity measurements to monitor the small variations among different material samples. Therefore, the purpose of this paper is to review recent research on the development of microwave planar sensors and further challenges of their sensitivity and selectivity. Furthermore, the techniques of the complex permittivity extraction (real and imaginary parts) are discussed based on the different approaches of mathematical models. The outcomes of this review may facilitate improvements of and an alternative solution for the enhancement of microwave planar sensors’ normalized sensitivity for material characterization, especially in biochemical and beverage industry applications.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Optimization of Extraction Parameters of Reverse Iontophoretic Determination of Blood Glucose in an Artificial Skin Model

Background:

Reverse İontophoresis (RI) is one of the promising non-invasive technologies. It relies on the transition of low magnitude current through the skin and thus glucose measurement becomes possible as it is extracted from the surface during this porter current flow.

Objective:

This paper deals with the development and optimization of an RI determination method for glucose. CE dialysis membrane based artificial skin model was developed and the dependence of RI extraction on various experimental parameters was investigated.

Method:

Dependence of RI extraction performance on noble electrodes (platinum, silver, palladium, ruthenium, rhodium) was checked with CA, CV and DPV, in a wide pH and ionic strength range. Optimizations on inter-electrode distance, potential type and magnitude, extraction time, gel type, membrane MWCO, usage frequency, pretreatment, artificial body fluids were performed.

Results:

According to the optimized results, the inter-electrode distance was 7.0 mm and silver was the optimum noble metal. Optimum pH and ionic strength were achieved with 0.05M PBS at pH 7.4. Higher glucose yields were obtained with DPV, while CA and CV achieved almost the same levels. During CA, +0.5V achieved the highest glucose yield and higher potential even caused a decrease. Glucose levels could be monitored for 24 hours. CMC gel was the optimum collection media. Pretreated CE membrane with 12kD MWCO was the artificial skin model. Pretreatment affected the yields while its condition caused no significant difference. Except PBS solution (simulated as artificial plasma), among the various artificial simulated body fluids, intestinal juice formulation (AI) and urine formulation U2 were the optimum extraction media, respectively.

Conclusion:

In this study, various experimental parameters (pretereatment procedure, type and MWCO values of membranes, inter-electrode distance, electrode material, extraction medium solvents, ionic strength and pH, collection medium gel type, extraction potential type and magnitude, extraction time and etc) were optimized for the non-invasive RI determination of glucose in a CE dialysis membrane-based artificial skin model and various simulated artificial body fluids.

Ultrasound-modulated optical glucose sensing using a 1645 nm laser

Regular and frequent blood glucose monitoring is vital in managing diabetes treatment plans and preventing severe complications. Because current invasive techniques impede patient compliance and are not infection-free, many noninvasive methods have been proposed. Among them, optical methods have drawn much attention for their rich optical contrast, but their resolution is degraded in deep tissue. Here, we present an ultrasound-modulated optical sensing (UOS) technique to noninvasively monitor glucose that uses an infrared laser (1645 nm) and a single-element focused ultrasound transducer. Focused ultrasound waves can acoustically localize diffused photons in scattering media, and thus optical contrast can be represented with much enhanced spatial resolution. To maximize the signal-to-noise ratio, we compared the modulation depths of UOS signals in both continuous and burst ultrasound transmission modes. Finally, UOS measurements of various glucose concentrations are presented and compared with those acquired in phantoms with a conventional diffuse optical sensing method. The UOS measurements in a 20 mm thick tissue-mimicking phantom show 26.6% accuracy in terms of mean absolute relative difference (MARD), which indicates the great potential of the proposed technique as a noninvasive glucose sensor.

Diabetes Management Experience and the State of Hypoglycemia: National Online Survey Study

BACKGROUND

Hypoglycemia, or low blood sugar levels, in people with diabetes can be a serious life-threatening condition, and serious outcomes can be avoided if low levels of blood sugar are proactively detected. Although technologies exist to detect the onset of hypoglycemia, they are invasive or costly or exhibit a high incidence of false alarms. Tremors are commonly reported symptoms of hypoglycemia and may be used to detect hypoglycemic events, yet their onset is not well researched or understood.

OBJECTIVE

This study aimed to understand diabetic patients' perceptions of hypoglycemic tremors, as well as their user experiences with technology to manage diabetes, and expectations from a self-management tool to ultimately inform the design of a noninvasive and cost-effective technology that detects tremors associated with hypoglycemia.

METHODS

A cross-sectional internet panel survey was administered to adult patients with type 1 diabetes using the Qualtrics platform in May 2019. The questions focused on 3 main constructs: (1) perceived experiences of hypoglycemia, (2) experiences and expectations about a diabetes management device and mobile app, and (3) beliefs and attitudes regarding intention to use a diabetes management device. The analysis in this paper focuses on the first two constructs. Nonparametric tests were used to analyze the Likert scale data, with a Mann-Whitney U test, Kruskal-Wallis test, and Games-Howell post hoc test as applicable, for subgroup comparisons to highlight differences in perceived frequency, severity, and noticeability of hypoglycemic tremors across age, gender, years living with diabetes, and physical activity.

RESULTS

Data from 212 respondents (129 [60.8%] females) revealed statistically significant differences in perceived noticeability of tremors by gender, whereby males noticed their tremors more (P<.001), and age, with the older population reporting lower noticeability than the young and middle age groups (P<.001). Individuals living longer with diabetes noticed their tremors significantly less than those with diabetes for ≤1 year but not in terms of frequency or severity. Additionally, the majority of our participants (150/212, 70.7%) reported experience with diabetes-monitoring devices.

CONCLUSIONS

Our findings support the need for cost-efficient and noninvasive continuous monitoring technologies. Although hypoglycemic tremors were perceived to occur frequently, such tremors were not found to be severe compared with other symptoms such as sweating, which was the highest rated symptom in our study. Using a combination of tremor and galvanic skin response sensors may show promise in detecting the onset of hypoglycemic events.

Noninvasive blood glucose detection using a quantum cascade laser

A Quantum Cascade Laser (QCL) was invented in the late 90s as a promising mid-infrared light source and it has contributed to the fields of industry, military, medicine, and biology. The room temperature operation, watt-level output power, compact size, and wide tuning capability of this laser advanced the field of noninvasive blood glucose detection with the use of transmission, absorption, and photoacoustic spectroscopy. This review provides a complete overview of the recent progress and technical details of these spectroscopy techniques, using QCL as an infrared light source for detecting blood glucose concentrations in diabetic patients.

An Optimizing Dynamic Spectrum Differential Extraction Method for Noninvasive Blood Component Analysis

Dynamic spectra (DS) can greatly reduce the influence of individual differences and the measurement environment by extracting the absorbance of pulsating blood at multiple wavelengths, and it is expected to achieve noninvasive detection of blood components. Extracting high-quality DS is the prerequisite for improving detection accuracy. This paper proposed an optimizing differential extraction method in view of the deficiency of existing extraction methods. In the proposed method, the sub-dynamic spectrum (sDS) is composed by sequentially extracting the absolute differences of two sample points corresponding to the height of the half peak on the two sides of the lowest point in each period of the logarithm photoplethysmography signal. The study was based on clinical trial data from 231 volunteers. Single-trial extraction method, original differential extraction method, and optimizing differential extraction method were used to extract DS from the volunteers' experimental data. Partial least squares regression (PLSR) and radial basis function (RBF) neural network were used for modeling. According to the effect of PLSR modeling, by extracting DS using the proposed method, the correlation coefficient of prediction set (R_p) has been improved by 17.33% and the root mean square error of prediction set has been reduced by 7.10% compared with the original differential extraction method. Compared with the single-trial extraction method, the correlation coefficient of calibration set (R_c) has increased from 0.747659 to 0.8244, with an increase of 10.26%, while the correlation coefficient of prediction set (R_p) decreased slightly by 3.22%, much lower than the increase of correction set. The result of the RBF neural network modeling also shows that the accuracy of the optimizing differential method is better than the other two methods both in calibration set and prediction set. In general, the optimizing differential extraction method improves the data utilization and credibility compared with the existing extraction methods, and the modeling effect is better than the other two methods.

Modern noninvasive methods for monitoring glucose levels in patients: a review

This paper presents the current state of the art of noninvasive glucose monitoring. In recent years, we can observe constant increase in the incidence of diabetes. About 40% of all performed blood tests apply to the glucose tests. Formerly, this lifestyle disease occurred mainly in rich countries, but now it is becoming more common in poorer countries. It is related to the increase in life expectancy, unhealthy diet, lack of exercise, and other factors. Untreated diabetes may cause many complications or even death. For this reason, daily control of glucose levels in people with this disorder is very important. Measurements with a traditional glucometer are connected with performing finger punctures several times a day, which is painful and uncomfortable for patients. Therefore, researches on other methods are ongoing. A method that would be fast, noninvasive and cheap could also enable testing the state of the entire population, which is necessary because of the number of people currently living with undiagnosed type 2 diabetes. Although the first glucometer was made in 1966, the first studies on glucose level measurement in tear film were documented as early as 1937. This shows how much a noninvasive method of diabetes control is needed. Since then, there have been more and more studies on alternative methods of glucose measurement, not only from tear fluid, but also from saliva, sweat, or transdermally.

Noninvasive glucose detection in exhaled breath condensate

Two-thirds of patients with diabetes avoid regularly monitoring their blood glucose levels because of the painful and invasive nature of current blood glucose detection. As an alternative to blood sample collection, exhaled breath condensate (EBC) has emerged as a promising noninvasive sample from which to monitor glucose levels. However, this dilute sample matrix requires sensors capable of detecting glucose with high resolution at nanomolar and micromolar concentrations. Recent developments in EBC collection methods and highly sensitive glucose biosensors provide a path toward enabling robust and sensitive glucose detection in EBC. This review addresses current and emerging EBC collection and glucose sensing modalities capable of quantifying glucose in EBC samples. We highlight the opportunities and challenges for development and integration of EBC glucose detection systems that will enable clinically robust and accurate EBC glucose measurements for improved glycemic control.

Selective Collection and Condensation of Exhaled Breath for Glucose Detection

Exhaled breath condensate (EBC) is a promising non-invasive sample for the detection of various analytes, such as glucose. However, the methods used to collect EBC are highly inconsistent; the variable dilution factors associated with water vapor and the inclusion of dead space air significantly impact the reliability of reported analyte concentrations in EBC. For example, current EBC glucose measurements have resulted in dilution factors ranging from 1/1000 to 1/50000 [1]. There is a need for a systematic and selective EBC collection method to ensure accurate analyte detection and quantification. Herein, we develop and characterize a low-cost, portable condenser which selectively collects exhaled breath that has been exchanged with lung fluid in a temperature-based manner. We demonstrate that for ~15 L of exhaled air, our device can condense reproducible volumes of EBC $({\lt} 130~ {\mu } \mathrm {L})$ in under 3 minutes (p > 0.05, n = 3). Furthermore, our results indicate that a higher concentration of glucose can be detected in the collected sample with selective valve opening (p < 0.05, n = 3). The development of this device enables a repeatable and robust collection method to enable the evaluation of correlations between analytes in EBC and blood.

An IoT-Based Non-Invasive Glucose Level Monitoring System Using Raspberry Pi

Patients diagnosed with diabetes mellitus must monitor their blood glucose levels in order to control the glycaemia. Consequently, they must perform a capillary test at least three times per day and, besides that, a laboratory test once or twice per month. These standard methods pose difficulty for patients since they need to prick their finger in order to determine the glucose concentration, yielding discomfort and distress. In this paper, an Internet of Things (IoT)-based framework for non-invasive blood glucose monitoring is described. The system is based on Raspberry Pi Zero (RPi) energised with a power bank, using a visible laser beam and a Raspberry Pi Camera, all implemented in a glove. Data for the non-invasive monitoring is acquired by the RPi Zero taking a set of pictures of the user fingertip and computing their histograms. Generated data is processed by an artificial neural network (ANN) implemented on a Flask microservice using the Tensorflow libraries. In this paper, all measurements were performed in vivo and the obtained data was validated against laboratory blood tests by means of the mean absolute error (10.37%) and Clarke grid error (90.32% in zone A). Estimated glucose values can be harvested by an end device such as a smartphone for monitoring purposes.

Noninvasive in vivo glucose detection in human finger interstitial fluid using wavelength-modulated differential photothermal radiometry

We present a noninvasive and noncontacting biosensor using Wavelength Modulated Differential Photothermal Radiometry (WM-DPTR) to monitor blood glucose concentration (BGC) through interstitial fluid (ISF) probing in human middle fingers. WM-DPTR works in the interference-free mid-infrared range with differential wavelengths at the peak and baseline of the fundamental glucose molecule absorption band, giving rise to high glucose sensitivity and specificity. In vivo WM-DPTR measurements and simultaneous finger pricking BGC reference measurements were performed on diabetic and nondiabetic volunteers during oral glucose tolerance testing. The measurement results demonstrated high resolution and large dynamic range (~80 deg) change in phase signal in the normal-to-hyperglycemia BGC range (5 mmol/L to higher than 33.2 mmol/L), which were supported by negative control measurements. The immunity to temperature variation of WM-DPTR yields precise and accurate noninvasive glucose measurements in the ISF.

Generalized Modeling Framework of Metal Oxide-Based Non-Enzymatic Glucose Sensors: Concepts, Methods, and Challenges

Glucose sensors have transformed diabetes control. Most glucose sensors are enzymatic, but a non-enzymatic metal oxide-based glucose sensor on a nanostructured substrate is of considerable interest for future always-on wearable closed-loop sensing for hypoglycemia management. Recently, various research groups have demonstrated that different nanostructured substrates (fabricated by a variety of innovative techniques) boost the sensitivity of non-enzymatic glucose sensor. In this work, we develop a physics-based model to correlate the geometrical and chemical design parameters to the non-linear amperometric response of non-enzymatic glucose sensor on geometrically complex substrates. Using this model, we can interpret the scattered results in the literature within a common conceptual framework. Our results show that while non-enzymatic glucose sensor still does not have sufficient dynamic range to replace the classical blood glucose sensors, these sensors could be useful for low concentration glucose sensing applications involving sweat, saliva, and ocular fluid. Our model will predictably improve the design of non-enzymatic glucose sensors for the integration into a continuous glucose monitoring system embedded in wearable and implantable platforms.

Non-invasive blood glucose measurement of 95% certainty by pressure regulated Mid-IR

To fight against diabetes mellitus, from which more than 400 million people suffer in the world, the patients have to puncture their fingers 4-5 times a day for the blood glucose level checks when using a glucometer, causing invasive pain and the risk of infection. Therefore, non-invasive method has been urged for blood glucose monitoring, among which the mid-infrared spectroscopy (Mid-IR) response of interstitial fluid was found to be promising. However, despite the prolonged effort, the accuracy still falls below the FDA's requirement. To break this barrier which lasted for almost three decades, we discovered the finger contact pressure playing a critical role during the measurement, where the Mid-IR reading could be affected significantly by a small change of the finger posture. In addition, the Mid-IR absorption level was also found to be highly associated with individual, revealing the necessity of adjusting the calibration correlation for each patient. By imposing a certain contact pressure monitored by a pressure transducer, we were able to achieve over 95% certainty from the Mid-IR measurement of glucose concentration and 100% comparability to the "true" glucose concentration for the first time, which was mainly attributed to the morphological change of finger tissue under pressure. The previous works resulted in only about 70% accuracy on average, barely hitting 80 + %, whereas ours reaches 95%, finally exceeding the requirement of FDA.

Gaussian probe beam with high spherical aberration for glucose concentration measurement

We demonstrate that an optical probe beam with high spherical aberration used for glucose concentration measurements gives better sensitivity compared to a probe beam free of aberrations, under similar conditions. We place a singlet focusing lens at a large distance from a laser source with a Gaussian intensity profile to obtain a spherically aberrated probe beam with negligible truncation. The aberrated probe beam propagates through a transparent liquid sample. Intensity profiles of the transmitted beam are recorded by means of a homodyne profiler to perform the glucose concentration measurements accurately.

Critical-depth Raman spectroscopy enables home-use non-invasive glucose monitoring

One of the most ambitious endeavors in the field of diabetes technology is non-invasive glucose sensing. In the past decades, a number of different technologies have been assessed, but none of these have found its entry into general clinical use. We report on the development of a table-top confocal Raman spectrometer that was used in the home of patients with diabetes and operated for extended periods of time unsupervised and without recalibration. The system is based on measurement of glucose levels at a ‘critical depth’ in the skin, specifically in the interstitial fluid located below the stratum corneum but above the underlying adipose tissue layer. The region chosen for routine glucose measurements was the base of the thumb (the thenar). In a small clinical study, 35 patients with diabetes analyzed their interstitial fluid glucose for a period of 60 days using the new critical-depth Raman (CD-Raman) method and levels were correlated to reference capillary blood glucose values using a standard finger-stick and test strip product. The calibration of the CD-Raman system was stable for > 10 days. Measurement performance for glucose levels present at, or below, a depth of ~250μm below the skin surface was comparable to that reported for currently available invasive continuous glucose monitors. In summary, using the CD-Raman technology we have demonstrated the first successful use of a non-invasive glucose monitor in the home.

A Flexible Interdigital Electrode Used in Skin Penetration Promotion and Evaluation with Electroporation and Reverse Iontophoresis Synergistically

Skin penetration is related to efficiencies of drug delivery or ISF extraction. Normally, the macro-electrode is employed in skin permeability promotion and evaluation, which has the disadvantages of easily causing skin damage when using electroporation or reverse iontophoresis by alone; furthermore, it has large measurement error, low sensitivity, and difficulty in integration. To resolve these issues, this paper presents a flexible interdigital microelectrode for evaluating skin penetration by sensing impedance and a method of synergistical combination of electroporation and reverse iontophoresis to promote skin penetration. First, a flexible interdigital microelectrode was designed with a minimal configuration circuit of electroporation and reverse iontophoresis for future wearable application. Due to the variation of the skin impedance correlated with many factors, relative changes of it were recorded at the end of supply, different voltage, or constant current, times, and duration. It is found that the better results can be obtained by using electroporation for 5 min then reverse iontophoresis for 12 min. By synergistically using electroporation and reverse iontophoresis, the penetration of skin is promoted. The results tested in vivo suggest that the developed microelectrode can be applied to evaluate and promote the skin penetration and the designed method promises to leave the skin without damage. The electrode and the method may be beneficial for designing noninvasive glucose sensors.

Glucose-sensitive silicone hydrogel contact lens toward tear glucose monitoring

Accurate and reliable monitoring of blood glucose is needed for the treatment of diabetes, which has many challenges, including lack of patient compliance. Measuring tear glucose is an alternative to traditional finger-stick tests used to track blood sugar levels, but glucose sensing using tears has yet to be achieved. We report a methodology for possible tear glucose monitoring using glucose-sensitive silicone hydrogel (SiHG) contact lenses, the primary type of lenses available in today's market. Initially, we assessed the interpenetrating polymer network, with nearly pure silicone and water regions, existing in the SiHGs using a polarity-sensitive probe Prodan. We then synthesized a glucose-sensitive fluorophore Quin-C18 with a hydrophobic side chain for localization of probe at the interfacial region. Using our glucose-sensing contact lens, we were able to measure varying concentrations of glucose in an in-vitro system. The Quin-C18 strongly bound to the lenses with insignificant leaching even after multiple rinses. The lenses displayed a similar response to glucose after three months of storage in water. This study demonstrates that it may be possible to develop a contact lens for continuous glucose monitoring in the near term, using our concept of fluorophore binding at the silicone-water interface.

Design of non-invasive glucose meter using near-infrared technique

Diabetics need to keep track of their blood glucose level and measure it regularly to determine their insulin dose intake and to ensure that glucose level is always within the normal range. In this article, a system that enables the measurement of blood glucose level non-invasively is designed. This article uses a near infra-red (NIR) transmittance spectroscopy, without drawing blood, puncturing the skin, or causing pain. It involves a light source and light detector circuits positioned on a certain region of the body. The attenuated received infra-red signal by the detector is a measure of the blood glucose level of that region. Data are collected from the receiving circuit and sent to a microcontroller using CoolTerm application, then exporting it to Excel Sheet, in which mean values and graphs are obtained. The performance of the circuit with and without Filtering is examined. A downward pattern was noticed, as the glucose concentration in the solution increased, the voltage output decreased, meaning that a less intensity light was detected by the receiving circuit. An improvement in the accuracy of measurements by 17% was achieved, when a notch filter is implemented to cut the voltage components corresponding to the power line noisy signals.

Verification of Non-Invasive Blood Glucose Measurement Method Based on Pulse Wave Signal Detected by FBG Sensor System

This paper describes and verifies a non-invasive blood glucose measurement method using a fiber Bragg grating (FBG) sensor system. The FBG sensor is installed on the radial artery, and the strain (pulse wave) that is propagated from the heartbeat is measured. The measured pulse wave signal was used as a collection of feature vectors for multivariate analysis aiming to determine the blood glucose level. The time axis of the pulse wave signal was normalized by two signal processing methods: the shortest-time-cut process and 1-s-normalization process. The measurement accuracy of the calculated blood glucose level was compared with the accuracy of these signal processing methods. It was impossible to calculate a blood glucose level exceeding 200 mg/dL in the calibration curve that was constructed by the shortest-time-cut process. In the 1-s-normalization process, the measurement accuracy of the blood glucose level was improved, and a blood glucose level exceeding 200 mg/dL could be calculated. By verifying the loading vector of each calibration curve to calculate the blood glucose level with a high measurement accuracy, we found the gradient of the peak of the pulse wave at the acceleration plethysmogram greatly affected.

Glucose sensing in oral mucosa simulating phantom using differential absorption based frequency domain low-coherence interferometry

The superluminescent diode based differential absorption frequency domain low-coherence interferometry (FD-DALCI) technique is proposed and demonstrated for sensing physiological concentrations of glucose (0-250 mg/dl) in oral mucosa simulating phantoms (intralipid of concentrations 0.25-0.50%) with wavelengths at 1589 and 1310 nm. The proposed technique allows simultaneous measurements of refractive index based spectral shift and estimation of physiological concentration of glucose in intralipid with scattering characteristics using the differential absorption approach. The sensitivity of the glucose concentration obtained by spectral shift measurement was ≈0.016  nm/(mg/dl), irrespective of the intralipid concentration. The resolution of the glucose level was estimated to be ≈15  mg/dl in 0.25% intralipid and ≈19  mg/dl in 0.5% intralipid using the FD-DALCI technique.

Glucose Sensing for Diabetes Monitoring: Recent Developments

This review highlights recent advances towards non-invasive and continuous glucose monitoring devices, with a particular focus placed on monitoring glucose concentrations in alternative physiological fluids to blood.

Deep learning framework for detection of hypoglycemic episodes in children with type 1 diabetes

Most Type 1 diabetes mellitus (T1DM) patients have hypoglycemia problem. Low blood glucose, also known as hypoglycemia, can be a dangerous and can result in unconsciousness, seizures and even death. In recent studies, heart rate (HR) and correct QT interval (QTc) of the electrocardiogram (ECG) signal are found as the most common physiological parameters to be effected from hypoglycemic reaction. In this paper, a state-of-the-art intelligent technology namely deep belief network (DBN) is developed as an intelligent diagnostics system to recognize the onset of hypoglycemia. The proposed DBN provides a superior classification performance with feature transformation on either processed or un-processed data. To illustrate the effectiveness of the proposed hypoglycemia detection system, 15 children with Type 1 diabetes were volunteered overnight. Comparing with several existing methodologies, the experimental results showed that the proposed DBN outperformed and achieved better classification performance.

Smart Devices for Older Adults Managing Chronic Disease: A Scoping Review

BACKGROUND

The emergence of smartphones and tablets featuring vastly advancing functionalities (eg, sensors, computing power, interactivity) has transformed the way mHealth interventions support chronic disease management for older adults. Baby boomers have begun to widely adopt smart devices and have expressed their desire to incorporate technologies into their chronic care. Although smart devices are actively used in research, little is known about the extent, characteristics, and range of smart device-based interventions.

OBJECTIVE

We conducted a scoping review to (1) understand the nature, extent, and range of smart device-based research activities, (2) identify the limitations of the current research and knowledge gap, and (3) recommend future research directions.

METHODS

We used the Arksey and O'Malley framework to conduct a scoping review. We identified relevant studies from MEDLINE, Embase, CINAHL, and Web of Science databases using search terms related to mobile health, chronic disease, and older adults. Selected studies used smart devices, sampled older adults, and were published in 2010 or after. The exclusion criteria were sole reliance on text messaging (short message service, SMS) or interactive voice response, validation of an electronic version of a questionnaire, postoperative monitoring, and evaluation of usability. We reviewed references. We charted quantitative data and analyzed qualitative studies using thematic synthesis. To collate and summarize the data, we used the chronic care model.

RESULTS

A total of 51 articles met the eligibility criteria. Research activity increased steeply in 2014 (17/51, 33%) and preexperimental design predominated (16/50, 32%). Diabetes (16/46, 35%) and heart failure management (9/46, 20%) were most frequently studied. We identified diversity and heterogeneity in the collection of biometrics and patient-reported outcome measures within and between chronic diseases. Across studies, we found 8 self-management supporting strategies and 4 distinct communication channels for supporting the decision-making process. In particular, self-monitoring (38/40, 95%), automated feedback (15/40, 38%), and patient education (13/40, 38%) were commonly used as self-management support strategies. Of the 23 studies that implemented decision support strategies, clinical decision making was delegated to patients in 10 studies (43%). The impact on patient outcomes was consistent with studies that used cellular phones. Patients with heart failure and asthma reported improved quality of life. Qualitative analysis yielded 2 themes of facilitating technology adoption for older adults and 3 themes of barriers.

CONCLUSIONS

Limitations of current research included a lack of gerontological focus, dominance of preexperimental design, narrow research scope, inadequate support for participants, and insufficient evidence for clinical outcome. Recommendations for future research include generating evidence for smart device-based programs, using patient-generated data for advanced data mining techniques, validating patient decision support systems, and expanding mHealth practice through innovative technologies.

State-of-the-Art Methods for Skeletal Muscle Glycogen Analysis in Athletes-The Need for Novel Non-Invasive Techniques

Muscle glycogen levels have a profound impact on an athlete’s sporting performance, thus measurement is vital. Carbohydrate manipulation is a fundamental component in an athlete’s lifestyle and is a critical part of elite performance, since it can provide necessary training adaptations. This paper provides a critical review of the current invasive and non-invasive methods for measuring skeletal muscle glycogen levels. These include the gold standard muscle biopsy, histochemical analysis, magnetic resonance spectroscopy, and musculoskeletal high frequency ultrasound, as well as pursuing future application of electromagnetic sensors in the pursuit of portable non-invasive quantification of muscle glycogen. This paper will be of interest to researchers who wish to understand the current and most appropriate techniques in measuring skeletal muscle glycogen. This will have applications both in the lab and in the field by improving the accuracy of research protocols and following the physiological adaptations to exercise.

Characterization of micro-resonator based on enhanced metal insulator semiconductor capacitor for glucose recognition

We present a concept for the characterization of micro-fabricated based resonator incorporating air-bridge metal-insulator-semiconductor (MIS) capacitor to continuously monitor an individual's state of glucose levels based on frequency variation. The investigation revealed that, the micro-resonator based on MIS capacitor holds considerable promise for implementation and recognition as a glucose sensor for human serum. The discrepancy in complex permittivity as a result of enhanced capacitor was achieved for the detection and determination of random glucose concentration levels using a unique variation of capacitor that indeed results in an adequate variation of the resonance frequency. Moreover, the design and development of micro-resonator with enhanced MIS capacitor generate a resolution of 112.38 × 10^-3pF/mg/dl, minimum detectable glucose level of 7.45mg/dl, and a limit of quantification of 22.58mg/dl. Additionally, this unique approach offers long-term reliability for mediator-free glucose sensing with a relative standard deviation of less than 0.5%.