SiC RF Sensor for Continuous Glucose Monitoring

MRS Advances ◽  
2016 ◽  
Vol 1 (55) ◽  
pp. 3691-3696 ◽  
Author(s):  
Fabiola Araujo Cespedes ◽  
Gokhan Mumcu ◽  
Stephen E. Saddow
Keyword(s):  
Blood Glucose ◽  
Resonant Frequency ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Fatty Tissue ◽  
Glucose Levels ◽  
Active Sensor ◽  
Passive Sensor ◽  
Rf Antenna

ABSTRACTIt has been shown that changes in blood glucose can be sensed with an RF antenna made from silicon carbide (SiC) operating at 10 GHz. Therefore a SiC antenna patch could operate as an active sensor or as a passive sensor at 5.8 GHz for a continuous glucose monitoring system. The properties of SiC make this material ideal for biomedical applications and devices as it is not only biocompatible but also has great sensing capability. The permittivity and conductivity of the blood is glucose dependent. Thus implanting the antenna in the fatty tissue facing the muscle and blood results should result in a shift of the resonant frequency of the antenna with glucose levels. In the active sensor approach, a power supply and internal in-vivo circuitry with protection would be required. In the passive sensor approach, external circuitry sends a signal to the implanted antenna and is received back again, detecting any signal variations. Simulations in HFSS™ show that that an implanted sensor placed 2 mm from the muscle in fatty tissue would experience an approximate shift in resonant frequency of 12.3 MHz for a blood glucose change of 500 mg/dl.

scholarly journals Correlation between short- and mid-term hemoglobin A1c and glycemic control determined by continuous glucose monitoring

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jen-Hung Huang ◽  
Yung-Kuo Lin ◽  
Ting-Wei Lee ◽  
Han-Wen Liu ◽  
Yu-Mei Chien ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glycemic Control ◽  
Continuous Glucose Monitoring ◽  
Hemoglobin A1c ◽  
Glucose Monitoring ◽  
Mean Amplitude ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Before And After ◽  
Patients With Diabetes

Abstract Background Glucose monitoring is vital for glycemic control in patients with diabetes mellitus (DM). Continuous glucose monitoring (CGM) measures whole-day glucose levels. Hemoglobin A1c (HbA1c) is a vital outcome predictor in patients with DM. Methods This study investigated the relationship between HbA1c and CGM, which remained unclear hitherto. Data of patients with DM (n = 91) who received CGM and HbA1c testing (1–3 months before and after CGM) were retrospectively analyzed. Diurnal and nocturnal glucose, highest CGM data (10%, 25%, and 50%), mean amplitude of glycemic excursions (MAGE), percent coefficient of variation (%CV), and continuous overlapping net glycemic action were compared with HbA1c values before and after CGM. Results The CGM results were significantly correlated with HbA1c values measured 1 (r = 0.69) and 2 (r = 0.39) months after CGM and 1 month (r = 0.35) before CGM. However, glucose levels recorded in CGM did not correlate with the HbA1c values 3 months after and 2–3 months before CGM. MAGE and %CV were strongly correlated with HbA1c values 1 and 2 months after CGM, respectively. Diurnal blood glucose levels were significantly correlated with HbA1c values 1–2 months before and 1 month after CGM. The nocturnal blood glucose levels were significantly correlated with HbA1c values 1–3 months before and 1–2 months after CGM. Conclusions CGM can predict HbA1c values within 1 month after CGM in patients with DM.

Advantages and Disadvantages of Realtime Continuous Glucose Monitoring in People with Type 2 Diabetes

2012 ◽  
Vol 08 (01) ◽  
pp. 22 ◽  
Author(s):  
M Susan Walker ◽  
Stephanie J Fonda ◽  
Sara Salkind ◽  
Robert A Vigersky ◽  
◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glucose Levels ◽  
Advantages And Disadvantages ◽  
Blood Glucose Levels

Previous research has shown that realtime continuous glucose monitoring (RT-CGM) is a useful clinical and lifestyle aid for people with type 1 diabetes. However, its usefulness and efficacy for people with type 2 diabetes is less known and potentially controversial, given the continuing controversy over the efficacy of self-monitoring of blood glucose (SMBG) in this cohort. This article reviews theextantliterature on RT-CGM for people with type 2 diabetes, and enumerates several of the advantages and disadvantages of this technology from the perspective of providers and patients. Even patients with type 2 diabetes who are not using insulin and/or are relatively well controlled on oral medications have been shown to spend a significant amount of time each day in hyperglycemia. Additional tools beyond SMBG are necessary to enable providers and patients to clearly grasp and manage the frequency and amplitude of glucose excursions in people with type 2 diabetes who are not on insulin. While SMBG is useful for measuring blood glucose levels, patients do not regularly check and SMBG does not enable many to adequately manage blood glucose levels or capture marked and sustained hyperglycemic excursions. RT-CGM systems, valuable diabetes management tools for people with type 1 diabetes or insulin-treated type 2 diabetes, have recently been used in type 2 diabetes patients. Theextantstudies, although few, have demonstrated that the use of RT-CGM has empowered people with type 2 diabetes to improve their glycemic control by making and sustaining healthy lifestyle choices.

scholarly journals Self-measurement of Blood Glucose and Continuous Glucose Monitoring – Is There Only One Future?

2018 ◽  
Vol 14 (2) ◽  
pp. 24 ◽  
Author(s):  
Lutz Heinemann ◽  
Andreas Stuhr
Keyword(s):  
Blood Glucose ◽  
Continuous Glucose Monitoring ◽  
Subcutaneous Tissue ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Management Options ◽  
Measurement Quality ◽  
Glucose Levels ◽  
Wide Range ◽  
Patients With Diabetes

Monitoring glycaemic control in patients with diabetes has evolved dramatically over the past decades. The introduction of easy-to-use systems for self-monitoring of blood glucose (SMBG) utilising capillary blood samples has resulted in the availability of a wide range of systems, providing different measurement quality. Systems for continuous glucose monitoring (CGM) – used mainly in patients with type 1 diabetes (T1D) – were made possible by the development of glucose sensors that measure glucose levels in the interstitial fluid (ISF) in the subcutaneous tissue of the skin. CGM readings might not correspond exactly to SMBG measurement results taken at the same time, especially during rapid changes in either blood glucose or ISF glucose levels. The mean absolute relative difference is the most popular method used for characterising the measurement performance of CGM systems. Unlike the International Organization for Standardization 15197:2013 criteria for SMBG systems, no accuracy standards for CGM systems exist. Measurement quality of CGM systems can vary based on several factors, limiting their safety and effective use in managing diabetes. Patients have to be trained adequately to make safe and efficient use of CGM systems (like with SMBG systems). Also, systems for CGM must be evaluated in terms of patient safety and the ability to provide accurate measurements regardless of the fluctuation of glucose levels. As new technological advancements in glucose monitoring are essential for improved management options of diabetes, such as automated insulin dosing systems, there is a need for a critical view of all such developments. It is likely that both, SMBG and CGM systems, will play important future roles in the treatment of diabetes.

scholarly journals Assessment of a Noninvasive Chronic Glucose Monitoring System in Euglycemic and Diabetic Swine (Sus scrofa)

2020 ◽  
Author(s):  
Rebecca A Ober ◽  
Gail E Geist
Keyword(s):  
Blood Glucose ◽  
Monitoring System ◽  
Continuous Glucose Monitoring ◽  
Point Of Care ◽  
Glucose Monitoring ◽  
Continuous Glucose Monitoring System ◽  
Serum Chemistry ◽  
Continuous Glucose Monitor ◽  
Glucose Levels ◽  
Skin Patch

Models of type-I diabetes are well-characterized and commonly used in the preclinical evaluation of drugs and medical devices. The diabetic minipig is an excellent example of a translational model. However, chronic glucose monitoring in this species can be challenging; frequent blood sampling can be technically difficult and poorly tolerated in conscious swine. Skin-patch continuous blood glucose monitors are FDA-approved for human use and offer a potential refinement to cageside blood collection. However, this modality has not been evaluated in pigs. In this study, young adult male STZ-induced diabetic Yucatan minipigs (n = 4) and healthy York pigs (n = 4) were implanted with a 14-d skin-patch continuous glucose monitor. Readings from continuous glucose monitors were time-matched to whole blood samples, with glucose measurements performed using point-of-care blood glucose monitors, serum chemistry or both. The aims of the study were to assess if a continuous glucose monitoring system could accurately detect glucose levels in swine, and to compare the readings toboth point-of-care glucometers and serum chemistry results. We hypothesized that a continuous glucose monitoring system would accurately detect glucose levels in swine in comparison with a validated analyzer and could serve as an animal welfarerefinement for studies of diabetes. We found that the continuous glucose monitor used in this study provided an adequateadjunct for clinical management in the stable diabetic pig and a minimally invasive and inexpensive option for colony maintenanceof chronically diabetic swine.

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

2019 ◽  
Vol 9 (15) ◽  
pp. 3046 ◽  
Author(s):  
Antonio Alarcón-Paredes ◽  
Victor Francisco-García ◽  
Iris P. Guzmán-Guzmán ◽  
Jessica Cantillo-Negrete ◽  
René E. Cuevas-Valencia ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glucose Monitoring ◽  
Absolute Error ◽  
Blood Glucose Monitoring ◽  
Raspberry Pi ◽  
Glucose Levels ◽  
Non Invasive ◽  
Blood Glucose Levels ◽  
Artificial Neural Network Ann

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.

scholarly journals Correlation Between Short- and Mid-Term Hemoglobin A1c and Glycemic Control Determined by Continuous Glucose Monitoring

2021 ◽  
Author(s):  
Jen-Hung Huang ◽  
Yung-Kuo Lin ◽  
Ting-Wei Lee ◽  
Han-Wen Liu ◽  
Yu-Mei Chien ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glycemic Control ◽  
Continuous Glucose Monitoring ◽  
Hemoglobin A1c ◽  
Glucose Monitoring ◽  
Mean Amplitude ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Before And After ◽  
Patients With Diabetes

Abstract Background: Glucose monitoring is vital for glycemic control in patients with diabetes mellitus (DM). Continuous glucose monitoring (CGM) measures whole-day glucose levels. Hemoglobin A1c (HbA1c) is a vital outcome predictor in patients with DM. Methods: This study investigated the relationship between HbA1c and CGM, which remained unclear hitherto. Data of patients with DM (n = 91) who received CGM and HbA1c testing (1-3 months before and after CGM) were retrospectively analyzed. Diurnal and nocturnal glucose, highest CGM data (10%, 25%, and 50%), mean amplitude of glycemic excursions (MAGE), percent coefficient of variation (%CV), and continuous overlapping net glycemic action were compared with HbA1c values before and after CGM. Results: The CGM results were significantly correlated with HbA1c values measured 1 (r = 0.69) and 2 (r = 0.39) months after CGM and 1 month (r = 0.35) before CGM. However, glucose levels recorded in CGM did not correlate with the HbA1c values 3 months after and 2-3 months before CGM. MAGE and %CV were strongly correlated with HbA1c values 1 and 2 months after CGM, respectively. Diurnal blood glucose levels were significantly correlated with HbA1c values 1-2 months before and 1 month after CGM. The nocturnal blood glucose levels were significantly correlated with HbA1c values 1-3 months before and 1-2 months after CGM.Conclusions: CGM can predict HbA1c values within 1 month after CGM in patients with DM.

scholarly journals Interstitium versus Blood Equilibrium in Glucose Concentration and its Impact on Subcutaneous Continuous Glucose Monitoring Systems

2010 ◽  
Vol 10 (1) ◽  
pp. 36 ◽  
Author(s):  
Cosimo Scuffi ◽  
Keyword(s):  
Blood Glucose ◽  
Continuous Glucose Monitoring ◽  
Glucose Concentration ◽  
Interstitial Fluid ◽  
Glucose Monitoring ◽  
Foreign Body Response ◽  
Monitoring Systems ◽  
Glucose Levels ◽  
Consequent Reduction ◽  
The Impact

The relationship between both interstitial and blood glucose remains a debated topic, on which there is still no consensus. The experimental evidence suggests that blood and interstitial fluid glucose levels are correlated by a kinetic equilibrium, which as a consequence has a time and magnitude gradient in glucose concentration between blood and interstitium. Furthermore, this equilibrium can be perturbed by several physiological effects (such as foreign body response, wound-healing effect, etc.), with a consequent reduction of interstitial fluid glucose versus blood glucose correlation. In the present study, the impact of operating in the interstitium on continuous glucose monitoring systems (CGMs) will be discussed in depth, both for the application of CGMs in the management of diabetes and in other critical areas, such as tight glycaemic control in critically ill patients.

scholarly journals Continuous glucose monitoring in obese pregnant women with no hyperglycemia on glucose tolerance test

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253047
Author(s):  
Rosa Maria Rahmi ◽  
Priscila de Oliveira ◽  
Luciano Selistre ◽  
Paulo Cury Rezende ◽  
Gabriela Neuvald Pezzella ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glucose Tolerance ◽  
Pregnant Women ◽  
Continuous Glucose Monitoring ◽  
Glucose Tolerance Test ◽  
Glucose Monitoring ◽  
Tolerance Test ◽  
Oral Glucose ◽  
Glucose Levels ◽  
Blood Glucose Levels

Objective The objective of the present study was to compare 24-hour glycemic levels between obese pregnant women with normal glucose tolerance and non-obese pregnant women. Methods In the present observational, longitudinal study, continuous glucose monitoring was performed in obese pregnant women with normal oral glucose tolerance test with 75 g of glucose between the 24th and the 28th gestational weeks. The control group (CG) consisted of pregnant women with normal weight who were selected by matching the maternal age and parity with the same characteristics of the obese group (OG). Glucose measurements were obtained during 72 hours. Results Both the groups were balanced in terms of baseline characteristics (age: 33.5 [28.7–36.0] vs. 32.0 [26.0–34.5] years, p = 0.5 and length of pregnancy: 25.0 [24.0–25.0] vs. 25.5 [24.0–28.0] weeks, p = 0.6 in the CG and in the OG, respectively). Pre-breakfast glycemic levels were 77.77 ± 10.55 mg/dL in the CG and 82.02 ± 11.06 mg/dL in the OG (p<0.01). Glycemic levels at 2 hours after breakfast were 87.31 ± 13.10 mg/dL in the CG and 93.48 ± 18.74 mg/dL in the OG (p<0.001). Daytime blood glucose levels were 87.6 ± 15.4 vs. 93.1 ± 18.3 mg/dL (p<0.001) and nighttime blood glucose levels were 79.3 ± 15.8 vs. 84.7 ± 16.3 mg/dL (p<0.001) in the CG and in the OG, respectively. The 24-hour, daytime, and nighttime values of the area under the curve were higher in the OG when compared with the CG (85.1 ± 0.16 vs. 87.9 ± 0.12, 65.6 ± 0.14 vs. 67.5 ± 0.10, 19.5 ± 0.07 vs. 20.4 ± 0.05, respectively; p<0.001). Conclusion The results of the present study showed that obesity in pregnancy was associated with higher glycemic levels even in the presence of normal findings on glucose tolerance test.

scholarly journals Blood glucose and subcutaneous continuous glucose monitoring in critically ill horses: A pilot study

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247561
Author(s):  
Valentina Vitale ◽  
Lise C. Berg ◽  
Bettina Birch Larsen ◽  
Andrea Hannesdottir ◽  
Preben Dybdahl Thomsen ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Critically Ill ◽  
Continuous Glucose Monitoring ◽  
Interstitial Fluid ◽  
Point Of Care ◽  
Glucose Monitoring ◽  
Relevant Information ◽  
Glucose Levels ◽  
Interstitial Glucose ◽  
Blood Gas Analyzer

This pilot prospective study reports the feasibility, management and cost of the use of a continuous glucose monitoring (CGM) system in critically ill adult horses and foals. We compared the glucose measurements obtained by the CGM device with blood glucose (BG) concentrations. Neonatal foals (0–2 weeks of age) and adult horses (> 1 year old) admitted in the period of March-May 2016 with clinical and laboratory parameters compatible with systemic inflammatory response syndrome (SIRS) were included. Glucose concentration was monitored every 4 hours on blood samples with a point-of-care (POC) glucometer and with a blood gas analyzer. A CGM system was also placed on six adults and four foals but recordings were successfully obtained only in four adults and one foal. Glucose concentrations corresponded fairly well between BG and CGM, however, there appeared to be a lag time for interstitial glucose levels. Fluctuations of glucose in the interstitial fluid did not always follow the same trend as BG. CGM identified peaks and drops that would have been missed with conventional glucose monitoring. The use of CGM system is feasible in ill horses and may provide clinically relevant information on glucose levels, but there are several challenges that need to be resolved for the system to gain more widespread usability.

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