Non-invasive Blood Glucose Level Research Articles

Ultra-conformal epidermal antenna for multifunctional motion artifact-free sensing and point-of-care monitoring

Accurate acquisition of physiological and physical information from human tissue is essential for health monitoring, disease prevention and treatment. The existing antennas with traditional rigid or flexible substrates are susceptible to motion artifacts in wearable applications due to the miniaturization limitation and lack of proper adhesion and conformal interfaces with the skin. Recent advances in wearable radio frequency (RF) bioelectronics directly drawn on the skin are a promising solution for future skin-interfaced devices. Herein, we present a first-of-its kind epidermal antenna architecture with skin as the antenna substrate, which is ultra-low profile, ultra-conformal, ultra-compact, and simple fabrication without specialized equipment. The radiation unit and ground of antenna are drawn directly on the skin with the strong adhesion and ultra conformality. Therefore, this RF device is highly adaptable to motion. As a proof-of- feasibility, epidermal antenna can be freely drawn on demand at different locations on the skin for the development of temperature sensor, skin hydration sensor, strain sensor, glucose sensor and other devices. An epidermal antenna-based temperature sensor can offer accurate and real-time monitoring of human body temperature changes in the ultra-wideband (UWB) range. The results during the monitoring of hydration level with and without stretching show that the epidermal antenna drawn on the skin is motion artifact-free. We also designed an epidermal antenna array employing a horseshoe-shaped configuration for the precise identification of various gestures. In addition, the non-invasive blood glucose level (BGL) monitoring results during the in-vivo experiments report high correlation between the epidermal antenna responses and BGLs, without any time hysteresis. After the prediction of BGL by BP network, all the predicted BGL values are fallen 100% into the clinically acceptable zones. Together, these results show that epidermal antenna offers a promising new approach for biosensing platform.

Loopy Orthogonal Signal Correction Scatter Correction in Non-Invasive Blood Glucose

Spectroscopy is the study of matter based on light, sound, or particles emitted, absorbed, or reflected as well as the study of methods for generating and analyzing spectra. The spectrum has systematic diversity, namely the presence of light scattering and differences in the size of objects. The spectroscopic output allows for scattering shifts, because the same object measured several times does not exactly produce the same spectrum. Problems found in the spectrum can be overcome by pre-processing the data, namely the scatter correction method. Scatter correction is used to reduce the physical properties in the spectrum so that the information obtained is relatively the same for each spectrum, produces good estimates, and can be interpreted well. One of the spectroscopic tools that utilize infrared light is a non-invasive blood glucose level measuring device. The output of the tool is the time domain and intensity spectrum. Each object from the resulting spectrum still has noise, so scatter correction can be applied to this data. The purpose of this study was to perform a loopy Orthogonal Signal Correction (OSC) scatter correction method on time domain spectrum data on intensity on a non-invasive blood glucose level measuring device. The OSC method uses the concept of orthogonality to the mean by drawing the intensity value, weighting it, calculating the vector loading and then making corrections to the initial intensity. Based on the analysis, the loopy OSC method is better than OSC because the convergence is more accurate, the mean difference is smaller, the variance is smaller and the value converges on all the values tested. Based on exploration and the average difference, the loopy OSC method is better able to form the same pattern for each replication. This also shows that an object that is measured repeatedly has been able to be identified as the same object.

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

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

Stress fusion evaluation modeling and verification based on non-invasive blood glucose biosensors for live fish waterless transportation

Non-invasive blood glucose level (BGL) evaluation technology in skin mucus is a wearable stress-detection means to indicate the health status of live fish for compensating the drawbacks using traditional invasive biochemical inspection. Nevertheless, the commonly used methods cannot accurately obtain the BGL variations owing to the influence of an uncertain glucose exudation rate, ambient effects, and individualized differences. Our study proposes a non-invasive multi-sensor-fusion-based method to evaluate the dynamic BGL variations using the enhanced gray wolf-optimized backpropagation network (EGWO-BP) to continuously acquire more accurate trends. Furthermore, the K-means++ (KMPP) algorithm is utilized to further improve the accuracy of BGL acquisition by clustering fish with full consideration of its size features. In the verification test, turbot (Scophthalmus Maximus) was selected as an experimental subject to perform the continuous BGL monitoring in waterless keep-alive transportation by acquiring comprehensive biomarker information from different parts of fish skin mucus, such as fins, body, and tails. The comparison of results indicates that the KMPP-EGWO-BP can effectively acquire more accurate BGL variation than the traditional gray wolf-optimized backpropagation network (GWO-BP), particle swarm-optimized backpropagation network (PSO-BP), backpropagation network (BP), and support vector regression (SVR) by mean absolute percentage error (MAPE), root mean square error (RMSE), and coefficient of determination (R2). Finally, the proposed BGL fusion evaluation model can precisely acquire the live fish's physiological stress states to substantially reduce the potential mortality for the live fish circulation industry.

Assessment of Finger Fat Pad Effect on CSRR-Based Sensor Scattering Parameters for Non-Invasive Blood Glucose Level Detection.

This paper examines the effect of finger fat pad thickness on the accuracy performance of complementary split-ring resonator (CSRR)-based microwave sensors for non-invasive blood glucose level detection. For this purpose, a simplified four-layer Cole-Cole model along with a CSRR-based microwave sensor have been comprehensively analyzed and validated through experimentation. Computed scattering parameter (S-parameter) responses to different fat layer thicknesses are employed to verify the concordance of the studied model with the measurement results. In this respect, a figure of merit (FM) based on the normalized squared difference is introduced to assess the accuracy of the considered Cole-Cole model. We have demonstrated that the analyzed model agrees closely with the experimental validation. In fact, the maximum error difference for all five fingertips does not exceed 1.73 dB over the entire frequency range of interest, from 1 GHz to 4 GHz.

OUTLIER DETECTION ON HIGH DIMENSIONAL DATA USING MINIMUM VECTOR VARIANCE (MVV)

High-dimensional data can occur in actual cases where the variable p is larger than the number of observations n. The problem that often occurs when adding data dimensions indicates that the data points will approach an outlier. Outliers are part of observations that do not follow the data distribution pattern and are located far from the data center. The existence of outliers needs to be detected because it can lead to deviations from the analysis results. One of the methods used to detect outliers is the Mahalanobis distance. To obtain a robust Mahalanobis distance, the Minimum Vector Variance (MVV) method is used. This study will compare the MVV method with the classical Mahalanobis distance method in detecting outliers in non-invasive blood glucose level data, both at p>n and n>p. The test results show that the MVV method is better for n>p. MVV shows more effective results in identifying the minimum data group and outlier data points than the classical method.

The effect of thoracic epidural analgesia on short-term outcome and mortality in geriatric patients undergoing open heart surgery.

In open-heart surgeries, many organ functions, particularly the respiratory system, are affected by post-operative pain, and so is mortality. Following open-heart surgery, geriatric patients have a higher risk of organ dysfunction and mortality. We aimed to compare the short-term outcomes and mortality of thoracic epidural analgesia (TEA) and intravenous (IV) analgesia in geri-atric patients undergoing open heart surgery. This study included patients over the age of 65 who had open-heart surgery between 2010 and 2020. The patients were divided into two groups: Those who received TEA (Group E) and those who received IV paracetamol or tramadol or dexmedetomi-dine (Group I). The patients' post-operative sedation and analgesia requirements, mechanical ventilation (MV) duration, blood glucose levels, liver and kidney function tests, complications, intensive care and hospital stay lengths, and mortality rates were all compared. The study included a total of 548 patients, with 408 in Group E and 140 in Group I. As a result of the comparisons be-tween the groups, sedation requirement, analgesia requirement, MV duration, post-extubation facial mask oxygen requirement, non-invasive MV need, re-intubation requirement, and blood glucose level were found to be lower in Group E than in Group I. Moreover, periods spent in intensive care and lengths of hospital stay were found to be lower in Group E than Group I. There was no difference found between the two groups in terms of hospital mortality. In elderly patients undergoing open-heart surgery, TEA reduced the length of time in intensive care and hospital stays by improving the respiratory status and blood glucose regulation by supplying analgesia and sedation.

A Feasibility Study of Non-invasive Blood Glucose Level Detection Using Near-Infrared Optical Spectroscopy

Diabetes mellitus, a common disease of the modern era, is a glucose level disorder in the human body that affects the vital organs of the body and damages them gradually if left untreated. Regular blood glucose monitoring is one of the prescribed routines to control the complications of diabetes. Unfortunately, most available methods of blood glucose level measurement involve invasive ways. Invasive techniques are painful, make the finger skin calloused and the patients suffer from the risk of infectious diseases. Hence, there lies a need to develop an effective non-invasive blood sugar measurement technique to relieve the patients from the nuisance. In order to address the issue, a non-invasive technique has been designed and implemented using 940 nm near-infrared (NIR) LED and a corresponding photodiode. Initially, the in-vitro test was performed over the glucose solution of various concentrations to check the sensitivity of the device. After that pilot experiments were carried out on diabetic patients. The obtained results conformed the theory of near infra-red spectroscopic optical theory. The results also showed that the developed technique can be comparable with the conventional invasive glucometer based method. Furthermore, the implemented prototype is economically viable, especially for the low-income population. This promising results thus pledge the potentials, feasibility, and reliability of the NIR based non-invasive blood glucose detection devices.
 Bangladesh Journal of Medical Physics Vol.14 No.1 2021 P 1-13

A Simple Medical Record System of Non-Invasive Blood Glucose Level Measurement Results for Diabetes Care Using Graphical User Interface (GUI) MATLAB

We present a medical records system and reminders to patients of the measurement results of non-invasive blood glucose levels. Measuring blood glucose levels is vital in avoiding potential adverse health effects like diabetes. Diabetes is a chronic metabolic disorder caused by a decrease in the pancreas to produce insulin. Generally, measuring blood glucose levels using the conventional method is injure the patient's finger. Currently, the non-invasive method was famous as one of the detections of blood glucose by applying the physical properties of laser absorption. In this paper, we use the photodiode as a detector, the LED as a sensor, and a signal conditioning circuit. The results showed that non-invasive glucose monitoring has the potential to measure glucose levels with sensitivity and linearity of 3.21 mg/dL and 98%, respectively. As a result of measuring the blood glucose levels of the subject was displayed on the LCD module was designed. We designed a simple application and medical record using Blynk applications and GUI MATLAB for recording the measurement results of blood glucose level. In the future, applications that have been developed can be used by doctors for monitoring the measurement of the blood glucose level and provide information to patients by mobile applications, sending an email or message the measurement results, the decision of a disease or not, and reminds the re-measurement time.

PAIN AND HEMODYNAMIC STATUS ASSESSMENT IN CHILDREN UNDERGOING ORTHOPAEDIC TRAUMA SURGERIES AMID PERIOPERATIVE MULTIMODAL ANALGESIA

Stable hemodynamic parameters are used as one of the criteria for adequacy of analgesia during the surgery. In order to provide reliable antinociceptive protection, it is necessary to reduce the flow of nociceptive stimuli from the peripheral to central receptors.
 Hence, pain and hemodynamic assessment is crucial for adequate perioperative analgesia and the choice of anesthetic technique in children undergoing orthopaedic trauma surgeries. 
 Purpose. This study aims to assess pain intensity and changes of hemodynamic parameters in orthopaedic trauma pediatric patients under perioperative multimodal analgesia.
 Materials and methods. A total of 61 patients with orthopaedic trauma were included in this study. Mean age was 9.3±4.5 years (range: 8-17). Open reduction was performed in 43 cases (70.5%), and 18 children (29.5%) underwent closed reduction. Mean duration of the surgery was 102.1±20.4 min. All patients have the premedication (atropine sulfate, diazepam, acetaminophen, intravenously) done 30-40 min. before the surgery in the surgical ward. Surgical procedures were performed under general anesthesia. Postoperative pain intensity was assessed by Individualized Numeric Rating Scale – NRS. Perioperative monitoring included peripheral pulse oximetry (SpO2), non-invasive blood pressure measurement (SBP, DBP, MAP), vital signs and blood glucose level control. Postoperative analgesia was maintained by IV acetaminophen, if necessary – by administration of divided dose of morphine. Results and conclusions. Mean pain intensity was 2.32±0.28 (6 hrs postop.), 12.06±0.16 (12 hrs postop.),
 2.78±0.24 (24 hrs postop.), 2.04±0.6 (48 hrs postop.) based on NRS, respectively (p<0.05). 26% patients required single dose administration of morphine during the first 24 hrs after the surgery.
 Significant decrease in blood glucose 12 hrs (4.3 mmol/l) and 24 hrs (4.6 mmol/l) after the surgery in comparison to the preoperative level (6.2 mmol/l) suggests of the severe stress resolution in the majority of the patients and adequate pain management. Preoperative stress is mainly caused by underlying disease and the surgical procedure itself.
 Heart rate (HR) monitoring shows that the vast majority of the patients (n=55, 86.5%) had mean pulse less than 110 bpm after IV Acetaminophen administration (20 mg/kg). 
 Minimal mean HR throughout the study was 87.3±5.3 bpm, maximal mean HR was 120±5.3 bpm. Mean SBP throughout the study was 100.2±5.3 mm Hg and mean DBP – 66.4±1.8 mm Hg, respectively. Oxygen saturation was within normal limits in all children. Hemodynamic parameters were within physiological surgical stressrelated limits, which suggests of the fluctuant course of postoperative pain syndrome.
 A traditional approach to perioperative pain management in children is associated with a moderate pain syndrome according to the results obtained with pain scales, hyperkinetic type of hemodynamics 6.24 hrs after the surgery, and the fluctuant course of postoperative pain.

Measurement of Non-Invasive Blood Glucose Level by UWB Transceiver in Diabetic Patient Type-1-

Diabetes is a silent killer and a rapidly increasing global epidemic worldwide. The change in healthy diabetes diet and life-style is only therapy as no permanent treatment. The measuring of the amount of Blood Glucose Level (BGL) continuously is important for diabetes management. In general terms, two types of diabetes can be identified as Type-1- and Type-2-. Type-1- is the most dangerous type and affects (5-10 percent) of the diabetic population; they have to inject or pump insulin themselves. The common method of measuring is glucometer which the sample of blood is taken by clipping patient’s finger and analysis this sample. This invasive method is painful and discomfort for the patient. This article presents a microwave sensor with frequency falls in the range of Ultra-wideband (UWB) spectrum to determine blood glucose level non-invasively (i, e. without giving any sample of blood). Ultra-wideband technology for the Wireless Body Area Network (WBAN) is an important technology due to its advantages in sensing and communication for biomedical applications. The proposed system consists of a piece of microwave resonator that can be placed on the arm of the patient. Then, the first frequency resonance of the sensor is modifying because of many changes are calculated in dielectric blood permittivity and frequency value transferred from the sensor. Relationship between the frequency response and the changing in blood permittivity is observed. This may result in a measurement phase in which the Blood Glucose Level present has a relation with the frequency response value of the sensor. This system showed a clear and accurate outcome. Besides, it is easy to use by patient himself in any time with multiple use without exchanging any part of it, and safe because no taking any drop of blood just put the sensor in touch with patient’s skin without pains, and low cost compared with other methods that measure the glucose level.

Fourier Transform Infra-Red spectrophotometry observation to find appropriate wavelength for non-invasive blood glucose level measurement optical device

The appropriate wavelength is essential for non-invasive blood glucose level measurement optical device. We conducted this experimental observation to find the usable wavelength candidate for non-invasive blood glucose level measurement optical device in 1000 nm to 2500 nm range. We run this observation in Prodia Bogor and Food Processing and Crops Technology Lab, Faculty of Agricultural Engineering, IPB University, July 2019. We obtained fasting, 15 mnt postprandial, and 30 mnt postprandial blood sample from 10 randomly selected consenting non blinded healthy adult subjects between 18 to 60 years old. We measured spectrophotometric absorbance for each blood sample. We did the measurement using BUCHI NIR FLEX 500. We compared the result to blood glucose level by standard gold measurement. We also compared the Pearson correlation, and the standard deviation of all samples to then-existing wavelength source LED provided by Thorlabs. We found that the highest absorbance and standard deviation wavelength is at 1939 nm. Wavelength LEDs candidates that represent measuring blood glucose levels is 1200, 1300, 1450, 1750, and 1950 nm. We did not find a severe adverse effect from each participant. Researchers should confirm the trial results with in vivo human observation.

Comparison of Functional Regression and Functional Principal Component Regression for Estimating Non-Invasive Blood Glucose Level

The calibration method is an alternative method that can be used to analyze the relationship between invasive and non-invasive blood glucose levels. Calibration modeling generally has a large dimension and contains multicolinearities because usually in functional data the number of independent variables (p) is greater than the number of observations (p>n). Both problems can be overcome using Functional Regression (FR) and Functional Principal Component Regression (FPCR). FPCR is based on Principal Component Analysis (PCA). In FPCR, the data is transformed using a polynomial basis before data reduction. This research tried to model the equations of spectral calibration of voltage value excreted by non-invasive blood glucose level monitoring devices to predict blood glucose using FR and FPCR. This study aimed to determine the best calibration model for measuring non-invasive blood glucose levels with the FR and FPCR. The results of this research showed that the FR model had a bigger coefficient determination (R2) value and lower Root Mean Square Error (RMSE) and Root Mean Square Error Prediction (RMSEP) value than the FPCR model, which was 12.9%, 5.417, and 5.727 respectively. Overall, the calibration modeling with the FR model is the best model for estimate blood glucose level compared to the FPCR model.

Recent Advancements and Future Prospects on E-Nose Sensors Technology and Machine Learning Approaches for Non-Invasive Diabetes Diagnosis: A Review.

Diabetes mellitus, commonly measured through an invasive process which although is accurate, has manifold drawbacks especially when multiple reading are required at regular intervals. Accordingly, there is a need to develop a dependable non-invasive diabetes detection technique. Recent studies have observed that other human serums such as tears, saliva, urine and breath indicate the presence of glucose in them. These parameters open quite a few ways for non-invasive blood glucose level prediction. The analysis of a persons breath poses as a good non-invasive technique to monitor the glucose levels. It is seen that in breath, there are many bio-markers and monitoring the levels of these bio-markers indicate the possibility of various chronic diseases. Among these bio-markers, acetone a volatile organic compound found in breath has shown a good correlation to the glucose levels present in blood. Therefore, by evaluating the acetone levels in breath samples it is possible to monitor diabetes non-invasively. This paper reviews the various approaches and sensory techniques used to monitor diabetes though human breath samples.

Development of Non-Invasive Blood Glucose Level Monitoring System using Phone as a Patient Data Storage

Glucose levels that accumulate in the blood can cause other organ disorders and even cause death. To prevent such occurrence, continuous and regular glucose measuring and monitoring is required for diabetes mellitus (DM) patients. Glucose measurement for DM patients are generally performed several times a day, so be required easy, harmless method of measuring the DM patients, and monitoring data are well recorded. Thus in this research, an android non-invasive glucose level system with wireless communication and automatic data storage on the phone’s memory was developed. The study was begun with the built of electronic and software systems as the central part of the measuring system. The electronic section consists of laser and light sensors that respond to a change in blood glucose (BG) levels, the microcontroller that controlled all of the measuring processes, and Bluetooth modules as transceiver on data communication of the android. The software section is built using an App Inventor developed by the Massachusetts Institute of Technology (MIT) to display and store data measurement on the mobile phone. The calibration process of light sensors is done with the standard tool and at last, the wireless communication systems testing and BG levels measurement. The result shows that 94 mg/dl of BG levels by standard tools equals 2.86 volts of voltage measured by the design system. The higher the BG level, the lower the voltage be. Increase the BG level causes the resistance between the transmitter and the receiver to raise and the voltage becomes low.

Blood Glucose Level Monitoring Using an FMCW Millimeter-Wave Radar Sensor

In this article, a novel sensing approach is presented for glucose level monitoring where a robust low-power millimeter(mm)-wave radar system is used to differentiate between blood samples of disparate glucose concentrations in the range 0.5 to 3.5 mg/mL. The proposed radar sensing mechanism shows greater capabilities for remote detection of blood glucose inside test tubes through detecting minute changes in their dielectric properties. In particular, the reflected mm-waves that represent unique signatures for the internal synthesis and composition of the tested blood samples, are collected from the multi-channels of the radar and analyzed using signal processing techniques to identify different glucose concentrations and correlate them to the reflected mm-wave readings. The mm-wave spectrum is chosen for glucose sensing in this study after a set of preliminary experiments that investigated the dielectric permittivity behavior of glucose-loaded solutions across different frequency bands. In this regard, a newly-developed commercial coaxial probe kit (DAK-TL) is used to characterize the electromagnetic properties of glucose-loaded samples in a broad range of frequencies from 300 MHz to 67 GHz using two different 50 Ω open-coaxial probes. This would help to determine the portion of the frequency spectrum that is more sensitive to slight variations in glucose concentrations as indicated by the amount of change in the dielectric constant and loss tangent parameters due to the different concentrations under test. The mm-wave frequency range 50 to 67 GHz has shown to be promising for acquiring both high sensitivity and sufficient penetration depth for the most interaction between the glucose molecules and electromagnetic waves. The processed results have indicated the reliability of using mm-wave radars in identifying changes in blood glucose levels while monitoring trends among those variations. Particularly, blood samples of higher glucose concentrations are correlated with reflected mm-wave signals of greater energy. The proposed system could likely be adapted in the future as a portable non-invasive continuous blood glucose level monitoring for daily use by diabetics.

Sensitivity and Specificity of Non-Invasive Blood Glucose Level Measurement Optical Device to Detect Hypoglycaemia.

Hypoglycemia is related to lethargy, psychiatric disorders, and impaired brain metabolism. Hypoglycemia is one of the leading factors of death in blood glucose level (BGL) metabolism disorders. Optical methods have been heavily researched due to its potential to eliminate drawbacks of conventional hypoglycemia detection; however, clinical data are still scarce. This study objective was to measure the sensitivity and specificity of non-invasive BGL Measurement Optical Device (NI-BGL-MOD) to detect hypoglycemia. The reference standard is venipuncture spectrophotometry. Researcher has developed NI-BGL-MOD, which we have used in a clinical trial in December 2015. The researchers have used spectral data collected from the device to measure the BGL of randomly selected 110 participants who were older than 17 y old. Each participant was measured five times. There are a total of 550 data sets that were then compared to BGL measurement using the reference standard. The spectral data were optimized using Discrete Fourier Transform and inferred to BGL prediction using the Fast Artificial Neural Network. Researchers have defined hypoglycemia case with BGL level at 75 mg/dL or lower. The researchers have calculated sensitivity and specificity using epiR in Rstudio. Respondents' BGL values were between 67 to 96 mg/dL. Researchers have classified eighty-nine cases as hypoglycemia. There are 461 cases classified as not hypoglycemia. The sensitivity was 54%, and the specificity was 97%. Diagnostic accuracy was 86%, and the number to diagnose was 1.96. The newly developed method NI-BGL-MOD could be used to detect hypoglycemia.

Feasibility study of portable microwave microstrip open-loop resonator for non-invasive blood glucose level sensing: proof of concept.

Self-management of blood glucose level is part and parcel of diabetes treatment, which involves invasive, painful, and uncomfortable methods. A proper non-invasive blood glucose monitor (NIBGM) is therefore desirable to deal better with it. Microwave resonators can potentially be used for such a purpose. Following the positive results from an in vitro previous work, a portable device based upon a microwave resonator was developed and assessed in a multicenter proof of concept. Its electrical response was analyzed when an individual's tongue was placed onto it. The study was performed with 352 individuals during their oral glucose tolerance tests, having four measurements per individual. The findings revealed that the accuracy must be improved before the diabetes community can make real use of the device. However, the relationship between the measuring parameter and the individual's blood glucose level is coherent with that from previous works, although with higher data dispersion. This is reflected in correlation coefficients between glycemia and the measuring magnitude consistently negative, although small, for the different datasets analyzed. Further research is proposed, focused on system improvements, individual calibration, and multitechnology approach. The study of the influence of other blood components different to glucose is also advised. Graphical abstract.

Non-Invasive Optical Blood Glucose Measurement based on Discrete Fourier Transform and Fast Artificial Neural Network: Fasting Normal Glucose Participants Case Study

A prototype non-invasive blood glucose level measurement optical device (NI-BGL-MOD) has been developed. The NI-BGL-MOD uses a discrete Fourier transform (DFT) method and a fast artificial neural network algorithm to optimize device performance. The appropriate light-emitting diode for the sensory module was selected based on near-infrared spectrophotometry of a blood glucose model and human blood. DFT is implemented in an analog-to-digital converter module. An in vitro trial using the blood glucose model along with a clinical trial involving 110 participants were conducted to evaluate the performance of the prototype. The root-mean-square error of the prototype was 10.8 mg/dl in the in vitro trial and 3.64 mg/dl in the clinical trial, which is lower than the ISO-15197:2016 mandated value of 10 mg/dl. In each trial, consensus error grid analysis indicated that the measurement error was within the safe range. The sensitivity and specificity of the prototype were 0.83 (0.36, 1.00) and 0.90 (0.55, 1.00) in the in vitro trial and 0.81 (0.75, 0.85) and 0.83 (0.78, 0.87) in the clinical trial, respectively. In general, the proposed NI-BGL-MOD demonstrated good performance than gold-standard measurement. Key words: Non-invasive blood glucose measurement, optical device, discrete Fourier transform, multi-formulatric regression, fast artificial neural network

VLSI design of intelligent, Self-monitored and managed, Strip-free, Non-invasive device for Diabetes mellitus patients to improve Glycemic control using IoT

To overcome the problems of existing invasive blood glucose monitoring, like pain while pricking, uncomfortable test strips, possibilities of infections, a real-time display and 24 hours non-invasive intelligent blood glucose level monitoring system is proposed. The proposed architecture acquires data with high speed and accuracy regarding levels of blood and tissue glucose concentration in the peripheral or central blood resulting in improved glycemic control. Furthermore, the substantial random noise is filtered before the results are displayed in the real–time display monitor. The device will provide accurate readings and generate alert signals using IoT so that untoward events can be prevented due to extreme fluctuations in the blood glucose levels. The system consists of a pulsed laser diode, a photoelectric transducer, low noise amplifier, high-speed analog to digital converter (ADC), and field programmable gate array (FPGA) and the LCD. The signal to noise ratio and sampling speed are maximized. The proposed system is realized using FPGA and produces maximum efficiency and high throughput with low energy consumption.