scholarly journals An Intensive Longitudinal Study of the Association of Stress With Hyperglycemia Using Real-Time Data Collection

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 180-180
Author(s):  
Brent Mausbach
Keyword(s):  
Blood Glucose ◽  
Linear Models ◽  
Significant Risk ◽  
Low Grade ◽  
Time Data ◽  
Continuous Glucose Monitor ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Ecological Momentary ◽  
Low Grade Inflammation

Abstract Caregivers of persons with dementia (PWD) are at significantly elevated risk for cardiovascular disease (CVD)s. A higher risk for diabetes is one potential mechanism of morbidity in caregivers. Diabetes has been associated with dyslipidemia, hypertension, oxidative stress, increased low-grade inflammation, and endothelial dysfunction, which all place individuals at risk for CVD. Elevated blood glucose, even in the nondiabetic range, is a significant risk marker for the development of CVD. The current study examined the semi-continuous association between stress and glucose. Participants wore a continuous glucose monitor that measured blood glucose every 5 minutes for a period of 10 days (n = 2,880/participant). Ecological Momentary Assessment (EMA) was used to measure stress, positive affect, negative affect, and dietary intake 3x/day over the 10-day period. Hierarchical linear models indicated significant within-person associations between stress and blood glucose levels (t = 3.88, df = 3.92, p = .018; R2 = 26.2%).

scholarly journals 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 ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3319 ◽  
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.

scholarly journals Evaluation of Blood Glucose Level Control in Type 1 Diabetic Patients Using Deep Reinforcement Learning

2021 ◽  
Author(s):  
Phuwadol Viroonluecha ◽  
Esteban Egea-Lopez ◽  
Jose Santa
Keyword(s):  
Diabetes Mellitus ◽  
Reinforcement Learning ◽  
Blood Glucose ◽  
Insulin Pump ◽  
Diabetic Patients ◽  
Level Control ◽  
Continuous Glucose Monitor ◽  
Loop Control ◽  
Glucose Levels ◽  
Blood Glucose Levels

Abstract Diabetes mellitus is a disease associated with abnormally high levels of blood glucose due to lack of insulin. Combining an insulin pump and continuous glucose monitor with a control algorithm to deliver insulin is an alternative to patient self-management of insulin doses to control blood glucose levels in diabetes mellitus patients. In this work we propose a closed-loop control for blood glucose levels based on deep reinforcement learning. We describe the initial evaluation of several alternatives conducted on a realistic simulator of the glucoregulatory system and propose a particular implementation strategy based on reducing the frequency of the observations and rewards passed to the agent, and using a simple reward function. We train agents with that strategy for three groups of patient classes, evaluate and compare it with alternative control baselines. Our results show that our method is able to outperform baselines as well as similar recent proposals, by achieving longer periods of safe glycemic state and low risk.

Formal Verification of a Multi-Basal Insulin Infusion Control Model

10.29007/kcrp ◽  
2018 ◽  
Author(s):  
Xin Chen ◽  
Souradeep Dutta ◽  
Sriram Sankaranarayanan
Keyword(s):  
Blood Glucose ◽  
Insulin Infusion ◽  
Infusion Pump ◽  
Artificial Pancreas ◽  
Small Time ◽  
Time Interval ◽  
State Variables ◽  
Continuous Glucose Monitor ◽  
Glucose Levels ◽  
Blood Glucose Levels

The artificial pancreas concept automates the delivery of insulin to patients with type-1 diabetes, sensing the blood glucose levels through a continuous glucose monitor (CGM) and using an insulin infusion pump to deliver insulin. Formally verifying control algorithms against physiological models of the patient is an important challenge. In this paper, we present a case study of a simple hybrid multi-basal control system that switches to different preset insulin delivery rates over various ranges of blood glucose levels. We use the Dalla- Man model for modeling the physiology of the patient and a hybrid automaton model of the controller. First, we reduce the problem state space and replace nonpolynomial terms by approximations with very small errors in order to simplify the model. Nevertheless, the model still remains nonlinear with up to 9 state variables.Reachability analysis on this hybrid model is used to verify that the blood glucose levels remain within a safe range overnight. This poses challenges, including (a) the model exhibits many discrete jumps in a relatively small time interval, and (b) the entire time horizon corresponding to a full night is 720 minutes, wherein the controller time period is 5 minutes. To overcome these difficulties, we propose methods to effectively handle time- triggered jumps and merge flowpipes over the same time interval. The evaluation shows that the performance can be improved with the new techniques.

Intraoperative Changes in Blood Glucose Levels Increase the Risk of Death in Cardiac Surgery

2006 ◽  
Vol 31 (03) ◽  
Author(s):  
H Hager ◽  
E Giorni ◽  
A Felli ◽  
B Mora ◽  
M Hiesmayr ◽  
...  
Keyword(s):  
Cardiac Surgery ◽  
Blood Glucose ◽  
Glucose Levels ◽  
Risk Of Death ◽  
Blood Glucose Levels

2167-PUB: Effect of Low-Available Carbohydrate Diet Containing Okara and Konjac on Blood Glucose Levels in Spontaneous Diabetic Torii Fatty Rats

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 2167-PUB
Author(s):  
KOHEI SURUGA ◽  
TSUYOSHI TOMITA ◽  
MASAKAZU KOBAYASHI ◽  
TADAHIKO MITSUI ◽  
KAZUNARI KADOKURA
Keyword(s):  
Blood Glucose ◽  
Carbohydrate Diet ◽  
Glucose Levels ◽  
Blood Glucose Levels

776-P: Characteristics of Overnight Blood Glucose Levels Are Related to Sleep Quality in People with Type 1 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 776-P
Author(s):  
RACHEL BRANDT ◽  
MINSUN PARK ◽  
LAURIE T. QUINN ◽  
MINSEUNG CHU ◽  
YOUNGKWAN SONG ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Sleep Quality ◽  
Glucose Levels ◽  
Blood Glucose Levels

Study of Diabetic Mellitus and Knowledge of Lotion Foot Care on the Community

2018 ◽  
Vol 9 (3) ◽  
Author(s):  
Hariyadi DM ◽  
Athiyah U ◽  
Hendradi E ◽  
Rosita N ◽  
Erawati T ◽  
...  
Keyword(s):  
Blood Glucose ◽  
T Test ◽  
Small Scale ◽  
Scale Production ◽  
Foot Care ◽  
Diabetic Mellitus ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Before And After ◽  
History Of

The prevention of Diabetic Mellitus (DM) and its complications is the main aim of this study, in addition to the training of lotion foot care application and the development of small scale industry. The research team delivered knowledge in the form of training on Diabetic Mellitus, healthy food, treatment and prevention of complications, and small-scale production of cosmetic products. The aim of this study was to determine the correlation between training on diabetic and lotion foot care application as preventive measures against diabetic complications on the patient's blood glucose levels in the community of residents in Banyuurip Jaya, Surabaya. It was expected from this training that the knowledge of the residents increases and people living with diabetic undergo lifestyle changes and therefore blood sugar levels can be controlled. The parameters measured in this research were blood glucose levels, the anti diabetic drug types consumed, and compliance on diabetics. This study used the data taken from 60 patients with DM over a period of one month. Questionnaires and log books was used to retrieve data and changes in blood glucose levels in diabetic patients. The results showed the demographic data of patients with type 2 diabetic of 85% female and 15% male, with the range of patients aged of 61-70 years of 46.67% and had history of diabetic (90%). The history of drugs consumed by respondents was anti diabetic drugs such as metformin (40%), glimepiride (33.37%) and insulin (6.67%). In addition, the increased knowledge of DM patients after being given the training compared to before training was shown in several questions in the questionnaire. A statistical analysis using t-test analyzed a correlation between training provided in order to enhance understanding of the patient, as well as correlation with blood glucose levels. A paired T-test showed that there was a relationship between the knowledge of trainees before and after training (p less than 0.05). An interesting result was that there was no relationship between blood glucose levels before and after training provided (p> 0.05).

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