scholarly journals Noninvasive, wearable, and tunable electromagnetic multisensing system for continuous glucose monitoring, mimicking vasculature anatomy

2020 ◽  
Vol 6 (24) ◽  
pp. eaba5320
Author(s):  
Jessica Hanna ◽  
Moussa Bteich ◽  
Youssef Tawk ◽  
Ali H. Ramadan ◽  
Batoul Dia ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Artificial Pancreas ◽  
Time Lag ◽  
Life Quality ◽  
Glucose Monitoring ◽  
Physical Parameters ◽  
Diabetic Patients ◽  
Glucose Levels ◽  
Glycemic Monitoring ◽  
Animal Models Of Diabetes

Painless, needle-free, and continuous glucose monitoring sensors are needed to enhance the life quality of diabetic patients. To that extent, we propose a first-of-its-kind, highly sensitive, noninvasive continuous glycemic monitoring wearable multisensor system. The proposed sensors are validated on serum, animal tissues, and animal models of diabetes and in a clinical setting. The noninvasive measurement results during human trials reported high correlation (>0.9) between the system’s physical parameters and blood glucose levels, without any time lag. The accurate real-time responses of the sensors are attributed to their unique vasculature anatomy–inspired tunable electromagnetic topologies. These wearable apparels wirelessly sense hypo- to hyperglycemic variations with high fidelity. These components are designed to simultaneously target multiple body locations, which opens the door for the development of a closed-loop artificial pancreas.

Use of Continuous Glucose Monitoring in Patients with Diabetes Mellitus on Peritoneal Dialysis: Correlation with Glycated Hemoglobin and Detection of High Incidence of Unaware Hypoglycemia

2015 ◽  
Vol 41 (1-3) ◽  
pp. 18-24 ◽  
Author(s):  
Ahad Qayyum ◽  
Tahseen A. Chowdhury ◽  
Elizabeth Ley Oei ◽  
Stanley L. Fan
Keyword(s):  
Peritoneal Dialysis ◽  
Continuous Glucose Monitoring ◽  
Glycated Hemoglobin ◽  
Glucose Monitoring ◽  
Diabetic Control ◽  
Diabetic Patients ◽  
Glucose Levels ◽  
High Incidence ◽  
Patients With Diabetes ◽  
Interstitial Glucose

Introduction: Glycated hemoglobin is used to assess diabetic control although its accuracy in dialysis has been questioned. How does it compare to the Continuous Glucose Monitoring System (CGMS) in peritoneal dialysis (PD) patients? Methods: We conducted a retrospective analysis of 60 insulin-treated diabetic patients on PD. We determined the mean interstitial glucose concentration and the proportion of patients with hypoglycemia (<4 mmol/l) or hyperglycemia (>11 mmol/l). Results: The correlation between HbA1c and glucose was 0.48, p < 0.0001. Three of 15 patients with HbA1c >75 mmol/mol experienced significant hypoglycemia (14-144 min per day). The patients with frequent episodes of hypoglycemia could not be differentiated from those with frequent hyperglycemia by demographics or PD prescription. Conclusion: HbA1c and average glucose levels measured by the CGMS are only weakly correlated. On its own, HbA1c as an indicator of glycemic control in patients with diabetes on PD appears inadequate. We suggest that the CGMS technology should be more widely adopted.

scholarly journals Therapeutics of Diabetes Mellitus: Focus on Insulin Analogues and Insulin Pumps

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Vasiliki Valla
Keyword(s):  
Glycaemic Control ◽  
Diabetes Management ◽  
Treatment Options ◽  
Artificial Pancreas ◽  
Glucose Monitoring ◽  
Postprandial Glucose ◽  
Insulin Analogues ◽  
Diabetic Patients ◽  
Glycaemic Variability ◽  
Glucose Levels

Aim. Inadequately controlled diabetes accounts for chronic complications and increases mortality. Its therapeutic management aims in normal HbA1C, prandial and postprandial glucose levels. This review discusses diabetes management focusing on the latest insulin analogues, alternative insulin delivery systems and the artificial pancreas.Results. Intensive insulin therapy with multiple daily injections (MDI) allows better imitation of the physiological rhythm of insulin secretion. Longer-acting, basal insulin analogues provide concomitant improvements in safety, efficacy and variability of glycaemic control, followed by low risks of hypoglycaemia. Continuous subcutaneous insulin infusion (CSII) provides long-term glycaemic control especially in type 1 diabetic patients, while reducing hypoglycaemic episodes and glycaemic variability. Continuous subcutaneous glucose monitoring (CGM) systems provide information on postprandial glucose excursions and nocturnal hypo- and/or hyperglycemias. This information enhances treatment options, provides a useful tool for self-monitoring and allows safer achievement of treatment targets. In the absence of a cure-like pancreas or islets transplants, artificial “closed-loop” systems mimicking the pancreatic activity have been also developed.Conclusions. Individualized treatment plans for insulin initiation and administration mode are critical in achieving target glycaemic levels. Progress in these fields is expected to facilitate and improve the quality of life of diabetic patients.

Interstitial fluid glucose time-lag correction for real-time continuous glucose monitoring

2013 ◽  
Vol 8 (1) ◽  
pp. 81-89 ◽  
Author(s):  
D. Barry Keenan ◽  
John J. Mastrototaro ◽  
Stuart A. Weinzimer ◽  
Garry M. Steil
Keyword(s):  
Real Time ◽  
Continuous Glucose Monitoring ◽  
Interstitial Fluid ◽  
Time Lag ◽  
Glucose Monitoring

Hand Prosthetic Design for Transradial Amputee by Using 3D Printing Technology to Enhance Life Quality

2021 ◽  
Vol 14 (2) ◽  
pp. 87-94
Author(s):  
Triwiyanto Triwiyanto ◽  
Torib Hamzah ◽  
Sari Luthfiyah ◽  
Bedjo Utomo
Keyword(s):  
3D Printing ◽  
Life Quality ◽  
Monitoring And Evaluation ◽  
Banana Peel ◽  
Physical Parameters ◽  
Prosthetic Hand ◽  
Printing Technology ◽  
3D Printing Technology ◽  
Glucose Levels ◽  
Prosthetic Hands

The target for this community service program is a resident of Jl. Parikesit RT 05 RW 03 Dusun Picis, Balongdowo Village, Candi District, Sidoarjo Regency. He had a work accident in one of the industries in the city of Sidoarjo in 2010 on the left wrist up to the fingers, so the doctor suggested amputation. He is actually still in his productive age (36 years old) but because of this situation, he is unable to carry out activities in the world of work and has decreased confidence in himself and avoids socializing in society. The purpose of this community partnership program (PKM) activity is to apply 3d printing technology in the manufacture of prosthetic hands for people who have transradial amputations as an effort to improve the quality of life. The implementation methods used are: a) the measurement of several physical parameters on the amputee such as the diameter of the arm circumference, the length of the amputated part, weight and height. In addition to physical parameters, we also carry out medical measurements, including obtaining information on health conditions such as blood pressure, heart health and blood glucose levels, b) designing prosthetic hands using 3D application programs and 3D printers, c) mechanical and functional testing for perform basic movements in the form of opening and closing the palms, d) monitoring and evaluation of the use of prosthetic hands. The results obtained from this activity are that the patient can use the prosthetic hand to assist with activities in carrying out daily activities. In this PKM activity, amputees have been tested, namely the movement of holding a mineral water bottle, holding a banana, peeling a banana peel and driving a two-wheeled motorized vehicle. Monitoring shows that patients need regular exercise in using prosthetic hands so that they are able to control and condition their use. In the future, several developments can be made, including in terms of control and size of the prosthetic hand so that patients can feel the benefits of a prosthetic hand that functions like a normal hand.

scholarly journals Assessment of Hyperglycemia, Hypoglycemia and Inter-Day Glucose Variability Using Continuous Glucose Monitoring among Diabetic Patients on Chronic Hemodialysis

2021 ◽  
Vol 10 (18) ◽  
pp. 4116
Author(s):  
Maria Divani ◽  
Panagiotis I. Georgianos ◽  
Triantafyllos Didangelos ◽  
Vassilios Liakopoulos ◽  
Kali Makedou ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glycated Albumin ◽  
Glucose Monitoring ◽  
Area Under The Curve ◽  
Glucose Variability ◽  
Hemodialysis Patients ◽  
Chronic Hemodialysis ◽  
Diabetic Patients ◽  
Lower Efficiency ◽  
Target Glucose

Continuous glucose monitoring (CGM) facilitates the assessment of short-term glucose variability and identification of acute excursions of hyper- and hypo-glycemia. Among 37 diabetic hemodialysis patients who underwent 7-day CGM with the iPRO2 device (Medtronic Diabetes, Northridge, CA, USA), we explored the accuracy of glycated albumin (GA) and hemoglobin A1c (HbA1c) in assessing glycemic control, using CGM-derived metrics as the reference standard. In receiver operating characteristic (ROC) analysis, the area under the curve (AUC) in diagnosing a time in the target glucose range of 70–180 mg/dL (TIR70–180) in <50% of readings was higher for GA (AUC: 0.878; 95% confidence interval (CI): 0.728–0.962) as compared to HbA1c (AUC: 0.682; 95% CI: 0.508–0.825) (p < 0.01). The accuracy of GA (AUC: 0.939; 95% CI: 0.808–0.991) in detecting a time above the target glucose range > 250 mg/dL (TAR>250) in >10% of readings did not differ from that of HbA1c (AUC: 0.854; 95% CI: 0.699–0.948) (p = 0.16). GA (AUC: 0.712; 95% CI: 0.539–0.848) and HbA1c (AUC: 0.740; 95% CI: 0.570–0.870) had a similarly lower efficiency in detecting a time below target glucose range < 70 mg/dL (TBR<70) in >1% of readings (p = 0.71). Although the mean glucose levels were similar, the coefficient of variation of glucose recordings (39.2 ± 17.3% vs. 32.0 ± 7.8%, p < 0.001) and TBR<70 (median (range): 5.6% (0, 25.8) vs. 2.8% (0, 17.9)) were higher during the dialysis-on than during the dialysis-off day. In conclusion, the present study shows that among diabetic hemodialysis patients, GA had higher accuracy than HbA1c in detecting a 7-day CGM-derived TIR70–180 < 50%. However, both biomarkers provided an imprecise reflection of acute excursions of hypoglycemia and inter-day glucose variability.

Online Prediction of Blood Glucose Levels using Genetic Algorithm

2014 ◽  
pp. 299-310
Author(s):  
Khaled Eskaf ◽  
Tim Ritchings ◽  
Osama Bedawy
Keyword(s):  
Blood Glucose ◽  
Glucose Monitoring ◽  
Simulation Software ◽  
Machine Learning Techniques ◽  
Diabetic Patients ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Learning Techniques ◽  
Preliminary Study ◽  
Online Prediction

Diabetes mellitus is one of the most common chronic diseases. The number of cases of diabetes in the world is likely to increase more than two fold in the next 30 years: from 115 million in 2000 to 284 million in 2030. This chapter is concerned with helping diabetic patients to manage themselves by developing a computer system that predicts their Blood Glucose Level (BGL) after 30 minutes on the basis of their current levels, so that they can administer insulin. This will enable the diabetic patient to continue living a normal daily life, as much as is possible. The prediction of BGLs based on the current levels BGLs become feasible through the advent of Continuous Glucose Monitoring (CGM) systems, which are able to sample patients' BGLs, typically 5 minutes, and computer systems that can process and analyse these samples. The approach taken in this chapter uses machine-learning techniques, specifically Genetic Algorithms (GA), to learn BGL patterns over an hour and the resulting value 30 minutes later, without questioning the patients about their food intake and activities. The GAs were invested using the raw BGLs as input and metadata derived from a Diabetic Dynamic Model of BGLs supplemented by the changes in patients' BGLs over the previous hour. The results obtained in a preliminary study including 4 virtual patients taken from the AIDA diabetes simulation software and 3 volunteers using the DexCom SEVEN system, show that the metadata approach gives more accurate predictions. Online learning, whereby new BGL patterns were incorporated into the prediction system as they were encountered, improved the results further.

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