Independent Glucose Monitoring by Functionally Blind Diabetics

Self-monitoring of blood glucose levels is the preferred practice for diabetics who wish to control the disease through diet and medication. However, some persons are not able to perform this task independently because of severe vision loss. Glucometers (devices to measure blood glucose levels) with an auditory output may prove to be a viable alternative for these persons. The purpose of this study was to determine if functionally blind diabetics could indeed monitor their glucose levels independently using a talking glucometer. Although results indicate that this is possible, some individualized instruction is needed to ensure adequate coverage of the test strip and, therefore, accurate glucose readings.

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Flash Glucose Monitoring Technology Impact on Diabetes Self-Care Behavior

American Journal of Lifestyle Medicine ◽

10.1177/1559827619890955 ◽

2019 ◽

Vol 14 (2) ◽

pp. 130-132 ◽

Cited By ~ 1

Author(s):

Nicole D. White ◽

Emily Knezevich

Keyword(s):

Blood Glucose ◽

Glucose Monitoring ◽

Self Care ◽

Innovative Technology ◽

Future Research ◽

Self Monitoring ◽

Flash Glucose Monitoring ◽

Glucose Levels ◽

Blood Glucose Levels ◽

Care Behavior

Individuals with diabetes play a significant role in the control of their condition by participating in their own care. Self-monitoring of blood glucose is of particular importance in maintaining adequate glycemic control but when obtained using traditional fingerstick methods, is often limited with by cost, fear of needles or pain and inconvenience. Flash glucose monitoring is an innovative technology available to address these barriers and help people with diabetes better manage their blood glucose levels. Data demonstrating increased frequency in glucose monitoring, patient perspectives related to self-care behaviors, and implications for practice and future research are described.

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Enabling the Internet of Mobile Crowdsourcing Health Things: A Mobile Fog Computing, Blockchain and IoT Based Continuous Glucose Monitoring System for Diabetes Mellitus Research and Care

Sensors ◽

10.3390/s19153319 ◽

2019 ◽

Vol 19 (15) ◽

pp. 3319 ◽

Cited By ~ 20

Author(s):

Tiago M. Fernández-Caramés ◽

Iván Froiz-Míguez ◽

Oscar Blanco-Novoa ◽

Paula Fraga-Lamas

Keyword(s):

Blood Glucose ◽

Fog Computing ◽

Storage System ◽

Glucose Monitoring ◽

Continuous Glucose Monitor ◽

Self Monitoring ◽

Mobile Crowdsourcing ◽

Glucose Levels ◽

Blood Glucose Levels ◽

Diabetes Patients

Diabetes patients suffer from abnormal blood glucose levels, which can cause diverse health disorders that affect their kidneys, heart and vision. Due to these conditions, diabetes patients have traditionally checked blood glucose levels through Self-Monitoring of Blood Glucose (SMBG) techniques, like pricking their fingers multiple times per day. Such techniques involve a number of drawbacks that can be solved by using a device called Continuous Glucose Monitor (CGM), which can measure blood glucose levels continuously throughout the day without having to prick the patient when carrying out every measurement. This article details the design and implementation of a system that enhances commercial CGMs by adding Internet of Things (IoT) capabilities to them that allow for monitoring patients remotely and, thus, warning them about potentially dangerous situations. The proposed system makes use of smartphones to collect blood glucose values from CGMs and then sends them either to a remote cloud or to distributed fog computing nodes. Moreover, in order to exchange reliable, trustworthy and cybersecure data with medical scientists, doctors and caretakers, the system includes the deployment of a decentralized storage system that receives, processes and stores the collected data. Furthermore, in order to motivate users to add new data to the system, an incentive system based on a digital cryptocurrency named GlucoCoin was devised. Such a system makes use of a blockchain that is able to execute smart contracts in order to automate CGM sensor purchases or to reward the users that contribute to the system by providing their own data. Thanks to all the previously mentioned technologies, the proposed system enables patient data crowdsourcing and the development of novel mobile health (mHealth) applications for diagnosing, monitoring, studying and taking public health actions that can help to advance in the control of the disease and raise global awareness on the increasing prevalence of diabetes.

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Self-Monitoring of Blood Glucose Levels: Evaluating the Impact of a Policy of Quantity Limits on Test-Strip Use and Costs

Canadian Journal of Diabetes ◽

10.1016/j.jcjd.2016.03.003 ◽

2016 ◽

Vol 40 (5) ◽

pp. 431-435 ◽

Cited By ~ 4

Author(s):

Tara Gomes ◽

Diana Martins ◽

Mina Tadrous ◽

J. Michael Paterson ◽

Baiju R. Shah ◽

...

Keyword(s):

Blood Glucose ◽

Test Strip ◽

Self Monitoring ◽

Glucose Levels ◽

Blood Glucose Levels ◽

The Impact

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Use of real-time continuous glucose monitoring versus traditional self-monitoring of blood glucose levels improves glycaemic control in patients with type 1 diabetes

Evidence-Based Nursing ◽

10.1136/ebn.2011.100247 ◽

2011 ◽

Vol 15 (1) ◽

pp. 7-8 ◽

Cited By ~ 1

Author(s):

Cynthia Fritschi

Keyword(s):

Type 1 Diabetes ◽

Blood Glucose ◽

Glycaemic Control ◽

Real Time ◽

Continuous Glucose Monitoring ◽

Glucose Monitoring ◽

Self Monitoring ◽

Glucose Levels ◽

Blood Glucose Levels

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Self-monitoring of Blood Glucose Levels and Intensified Insulin Therapy

JAMA ◽

10.1001/jama.1983.03330450043023 ◽

1983 ◽

Vol 249 (21) ◽

pp. 2913 ◽

Cited By ~ 6

Author(s):

Mitchell E. Geffner

Keyword(s):

Blood Glucose ◽

Insulin Therapy ◽

Self Monitoring ◽

Glucose Levels ◽

Intensified Insulin Therapy ◽

Blood Glucose Levels

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A Review of Non-Invasive Optical Systems for Continuous Blood Glucose Monitoring

Sensors ◽

10.3390/s21206820 ◽

2021 ◽

Vol 21 (20) ◽

pp. 6820

Author(s):

Bushra Alsunaidi ◽

Murad Althobaiti ◽

Mahbubunnabi Tamal ◽

Waleed Albaker ◽

Ibraheem Al-Naib

Keyword(s):

Blood Glucose ◽

Glucose Monitoring ◽

Daily Basis ◽

Glucose Sensing ◽

Blood Glucose Monitoring ◽

Optical Systems ◽

Glucose Levels ◽

Non Invasive ◽

Blood Glucose Levels ◽

Continuous Blood Glucose Monitoring

The prevalence of diabetes is increasing globally. More than 690 million cases of diabetes are expected worldwide by 2045. Continuous blood glucose monitoring is essential to control the disease and avoid long-term complications. Diabetics suffer on a daily basis with the traditional glucose monitors currently in use, which are invasive, painful, and cost-intensive. Therefore, the demand for non-invasive, painless, economical, and reliable approaches to monitor glucose levels is increasing. Since the last decades, many glucose sensing technologies have been developed. Researchers and scientists have been working on the enhancement of these technologies to achieve better results. This paper provides an updated review of some of the pioneering non-invasive optical techniques for monitoring blood glucose levels that have been proposed in the last six years, including a summary of state-of-the-art error analysis and validation techniques.

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Modern technologies in diabetes management - continuous glucose monitoring and insulin pump therapy

Public health of the Far East Peer-reviewed scientific and practical journal ◽

10.33454/1728-1261-2021-1-50-55 ◽

2021 ◽

Vol 87 (1) ◽

pp. 50-55

Author(s):

E.Yu. Pyankova ◽

◽

L.A. Anshakova ◽

I.A. Pyankov ◽

S.V. Yegorova ◽

...

Keyword(s):

Blood Glucose ◽

Diabetes Management ◽

Insulin Pump ◽

Glucose Monitoring ◽

Insulin Pump Therapy ◽

Pump Therapy ◽

Glucose Levels ◽

Blood Glucose Levels ◽

The Individual ◽

Glucose Lowering Therapy

The problems of complications of diabetes mellitus cannot be solved without constant monitoring of blood glucose levels. The evolution of additional technologies for the determination of glucose in the blood of the last decades makes it possible to more accurately predict the risks of complications, both in the individual and in the patient population as a whole. The article provides an overview of the methods used in modern diabetology, facilitating control over the variability of blood glucose levels and helping in a more accurate selection of glucose-lowering therapy. All presented methods are currently working in real clinical practice in the Khabarovsk Krai

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Online Prediction of Blood Glucose Levels using Genetic Algorithm

Advances in Data Mining and Database Management - Biologically-Inspired Techniques for Knowledge Discovery and Data Mining ◽

10.4018/978-1-4666-6078-6.ch014 ◽

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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A Novel Five-Microlitre Capillary System for Home Glucose Monitoring

Annals of Clinical Biochemistry International Journal of Laboratory Medicine ◽

10.1177/000456328101800507 ◽

1981 ◽

Vol 18 (5) ◽

pp. 304-307 ◽

Cited By ~ 2

Author(s):

C P Williams ◽

G K Davies ◽

D F Child

Keyword(s):

Blood Glucose ◽

Capillary Tube ◽

Glucose Monitoring ◽

Diabetic Patients ◽

Collection System ◽

Patient Acceptability ◽

Glucose Levels ◽

Capillary System ◽

Blood Glucose Levels ◽

High Degree

Improvement in the control of diabetic patients is aided by a knowledge of blood glucose levels during a ‘normal’ (non-hospitalised) day. We have devised a 5 μl capillary tube collection system as a ‘kit’ for home use by diabetics. Blood collected into 5 μl capillary tubes is washed into a protein precipitant by the patient. The completed kit is posted to the laboratory for analysis. The technique has achieved a high degree of patient acceptability. Subsequent analysis involves the addition of a single reagent. Reagents, patient samples, and standards are stable, and the precision of the technique compares favourably with our routine glucose procedure.

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