NON-INVASIVE BLOOD GLUCOSE ANALYSIS BASED ON GALVANIC SKIN RESPONSE FOR DIABETIC PATIENTS

2018 ◽  
Vol 30 (02) ◽  
pp. 1850009 ◽  
Author(s):  
U. Snekhalatha ◽  
T. Rajalakshmi ◽  
C. H. Vinitha Sri ◽  
G. Balachander ◽  
K. S. Shankar
Keyword(s):  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Galvanic Skin Response ◽  
Skin Resistance ◽  
Measurement Techniques ◽  
Glucose Measurement ◽  
Diabetic Patients ◽  
Non Invasive ◽  
Skin Response

Diabetes is a chronic disease due to the lack of production of hormone insulin by the beta cells in the islets of Langerhans. Many diabetic patients often draw a small amount of blood to measure the glucose level every day. This vital information is needed to control their daily food intake. One such method could cause infection and discomfort to the patient. Non-invasive glucose measurement techniques overcome these challenges to monitor blood glucose level continuously. The aim and objective of this study are as follows: (i) to correlate the skin resistance based on Galvanic skin response (GSR) and blood glucose level for diabetic and non-diabetic subject and (ii) to estimate the blood glucose value based on GSR voltage and resistance using stepwise linear regression model. About 50 diabetic and 50 non-diabetic subjects were included in this study. Blood glucose level is recorded using the minimally invasive device called accu-chek for all the subjects. GSR resistance and GSR voltage were recorded using the designed instrumentation setup. In diabetic subjects, the measured blood glucose level shows negative correlation with the GSR voltage ([Formula: see text], [Formula: see text]) and GSR resistance ([Formula: see text], [Formula: see text]). The estimated blood glucose level can be predicted with good sensitivity (94%) and accuracy (92%) using age and GSR voltage, or by the combination of age and GSR resistance in the evaluation of diabetic subjects.

scholarly journals Biochemical markers in saliva of patients with diabetes mellitus

2012 ◽  
Vol 59 (4) ◽  
pp. 198-204 ◽  
Author(s):  
Biljana Andjelski-Radicevic ◽  
Radica Dozic ◽  
Tatjana Todorovic ◽  
Ivan Dozic
Keyword(s):  
Diabetes Mellitus ◽  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Diabetic Patients ◽  
Non Invasive ◽  
Stress Markers ◽  
Frequent Monitoring ◽  
Patients With Diabetes ◽  
Protein Components

Diabetes mellitus is metabolic syndrome characterized by disorder in metabolism of carbon hydrates, lipids and proteins. The diagnosis of diabetes is established by measuring the blood glucose level using standardized methods. Frequent monitoring of blood glucose level could be inconvenient for patients because of possible pain during blood sample taking. In the last few years biological materials with non invasive sampling, like saliva, have been analyzed. Research has confirmed that some organic and inorganic components of saliva are modified in diabetic patients (glucose, lipid and protein components, oxidative stress markers, electrolytes). Beside other markers, the analysis of glucose in saliva is an attempt to find a non-invasive and painless way for frequent monitoring of glucose concentration in diabetic patients. Collecting saliva is simple and economical, it neither requires expensive equipment nor specially trained staff. Saliva can be taken many times and in unlimited quantity. In regards to the data about the possibilities for using saliva as biological sample in monitoring diabetes mellitus, which could be alternative to blood serum or plasma, the conclusion is that saliva becomes more important in this context.

scholarly journals Intraoperative Hyperglycemia May Be Associated with an Increased Risk of Myocardial Injury after Non-Cardiac Surgery in Diabetic Patients

2021 ◽  
Vol 10 (22) ◽  
pp. 5219
Author(s):  
Sojin Kim ◽  
Jungchan Park ◽  
Hara Kim ◽  
Kwangmo Yang ◽  
Jin-ho Choi ◽  
...  
Keyword(s):  
Cardiac Surgery ◽  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Myocardial Injury ◽  
Postoperative Mortality ◽  
Glucose Measurement ◽  
Diabetic Patients ◽  
Close Monitoring ◽  
Increased Risk

Background: Hyperglycemia in surgical candidates is associated with increased mortality and morbidity. We aimed to evaluate the effect of intraoperative blood glucose level on the incidence of myocardial injury after non-cardiac surgery (MINS) in diabetic patients. Methods: Diabetic patients with available intraoperative blood glucose measurement during non-cardiac surgery were enrolled in this study. Based on the highest intraoperative blood glucose level, patients were stratified into two groups: the blood sugar glucose (BST) < 180 group (intraoperative peak glucose < 180 mg/dL) and BST ≥ 180 group (intraoperative peak glucose ≥ 180 mg/dL). The primary outcome was the incidence of MINS, and secondary outcomes were in-hospital and 30-day mortalities. Results: Of the 11,302 diabetic patients, 8337 were in the BST < 180 group (73.8%) and 2965 in the BST ≥ 180 group (26.2%). After adjustment with inverse probability weighting, MINS was significantly higher in the BST ≥ 180 group (24.0% vs. 17.2%; odds ratio (OR), 1.26; 95% confidence interval (CI), 1.14–1.40; p < 0.001). In addition, in-hospital and 30-day mortalities were also higher in the BST ≥ 180 group compared to the BST < 180 group (4.2% vs. 2.3%, hazard ratio (HR), 1.39; 95% CI, 1.07–1.81; p = 0.001, and 3.1% vs. 1.8%; HR, 1.76; 95% CI, 1.31–2.36; p < 0.001, respectively). Receiver-operating characteristic plots showed that the threshold of glucose level associated with MINS was 149 mg/dL. Conclusion: Intraoperative hyperglycemia was associated with an increased MINS incidence and postoperative mortality in diabetic patients. Close monitoring of intraoperative blood glucose level may be helpful in detection and management of MINS.

Indole as a new tentative marker in exhaled breath for non-invasive blood glucose monitoring of diabetic subjects

2021 ◽  
Author(s):  
Herbert Fink ◽  
Tim Maihöfer ◽  
Jeffrey Bender ◽  
Jochen Schulat
Keyword(s):  
Blood Glucose ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Blood Glucose Monitoring ◽  
Glucose Measurement ◽  
Diabetic Patients ◽  
Exhaled Breath ◽  
Invasive Approach ◽  
Test Strips ◽  
Non Invasive

Abstract Blood glucose monitoring (BGM) is the most important part of diabetes management. In classical BGM, glucose measurement by test strips involves invasive finger pricking. We present results of a clinical study that focused on a non-invasive approach based on volatile organic compounds (VOCs) in exhaled breath. Main objective was the discovery of markers for prediction of blood glucose levels (BGL) in diabetic patients. Exhaled breath was measured repeatedly in 60 diabetic patients (30 type 1, 30 type 2) in fasting state and after a standardized meal. Proton Transfer Reaction Time of Flight Mass Spectrometry (PTR-ToF-MS) was used to sample breath every 15 minutes for a total of six hours. BGLs were tested in parallel via BGM test strips. VOC signals were plotted against glucose trends for each subject to identify correlations. Exhaled indole (a bacterial metabolite of tryptophan) showed significant mean correlation to BGL (with negative trend) and significant individual correlation in 36 patients. The type of diabetes did not affect this result. Additional experiments of one healthy male subject by ingestion of lactulose and 13C-labeled glucose (n=3) revealed that exhaled indole does not directly originate from food digestion by intestinal microbiota. As indole has been linked to human glucose metabolism, it might be a tentative marker in breath for non-invasive BGM. Clinical studies with greater diversity are required for confirmation of such results and further investigation of metabolic pathways.

scholarly journals Comparison of the Effectiveness of Compassion-Focused Therapy and Attachment-Based Compassion Therapy on Blood Glucose Level and Medication Adherence in Diabetics

2020 ◽  
Keyword(s):  
Blood Glucose ◽  
Medication Adherence ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Blood Glucose Control ◽  
Analysis Of Covariance ◽  
Diabetic Patients ◽  
Training Course ◽  
Compassion Focused Therapy ◽  
Experimental Group

Background and Objectives: Diabetes is one of the most rampant chronic diseases that is accompanied by numerous psychological problems. The present study aimed to compare the effectiveness of compassion-focused therapy (CFT) and attachment-based compassion therapy (ABCT) on blood glucose level and medication adherence in diabetic patients. Materials and Methods: This quasi-experimental study was conducted based on a pretest and posttest design. At first, using the available voluntary sampling method, a number of 45 individuals were selected from 300 diabetic patients referred to Alborz Diabetes Association, Alborz, Iran. They were randomly divided into two experimental and one control groups. At the outset, in addition to the hemoglobin (Hb) A1c blood test, they completed a medication adherence questionnaire. Afterward, the first experimental group participated in eight two-h sessions of the compassionate therapy training course, and the second experimental group participated in 10 90-min sessions of the ABCT training course. All three groups received standard treatment for diabetic patients. At the end of the treatment, the HbA1c levels of blood in all three groups were re-evaluated, and again all patients completed the medication adherence questionnaire at the post-test stage. It should be mentioned that the collected data were analyzed using the analysis of covariance. Results: Based on the results, CFT and ABCT could reduce blood glucose level (HbA1c) (F=5.13, P<0.008, Eta= 0.20) and increase medication adherence (F=2.82, P<0.035, Eta= 0.12) in both of the experimental groups. Conclusion: The CFT and ABCT can be effective in improving medication adherence and blood glucose control (HbA1c) in diabetic patients. Therefore, it is suggested to provide such training together with other medical interventions as part of comprehensive therapy of diabetes.

scholarly journals Diabetes in COVID-19 patients: challenges and possible management strategies

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Riyan Al Islam Reshad ◽  
Sumaiya Hafiz Riana ◽  
Mohammad Al-baruni Chowdhury ◽  
Abu Tayab Moin ◽  
Faruque Miah ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Healthy Lifestyle ◽  
Management Strategies ◽  
Diabetic Patients ◽  
Main Body ◽  
High Blood Glucose ◽  
High Blood Glucose Level ◽  
Global Population

Abstract Background The recent pandemic of coronavirus disease 19 (COVID-19) has been causing intense stress among the global population. In the case of hospitalized and ICU-admitted COVID-19 patients with comorbidities, it has been observed that a major portion of them are diabetic. Therefore, researchers had indicated a link between diabetes mellitus (DM) and COVID-19. Furthermore, DM is a potential risk factor for the severity of COVID-19 cases. Thus, in this study, the correlation existing between diabetic patients and COVID-19 was summarized. Main body of the abstract Diabetic patients have a weaker immune system, less viral clearance rate, malfunctions of metabolic activity due to their high blood glucose level, and other associated problems. This does not increase the susceptibility for the patients to be infected with COVID-19. However, the severity of COVID-19 can worsen due to the comorbidity of DM. Short conclusion Proper management, appropriate use of drugs that do not increase the ACE2 expression, lowering blood glucose level, decreasing the susceptibility of SARS-CoV-2, and maintaining a healthy lifestyle could be effective.

scholarly journals Treatment of Diabetic Condition in Streptozotocin Induced Diabetic Wister Rats Using Food Blends Such as Unripe Plantain, Soybean and Ginger

2019 ◽  
pp. 1-12
Author(s):  
I. Iwanegbe ◽  
M. Suleiman ◽  
A. Jimah
Keyword(s):  
Body Weight ◽  
Blood Glucose ◽  
Blood Glucose Level ◽  
Lipid Profile ◽  
Cell Volume ◽  
Glucose Level ◽  
Normal Control ◽  
Packed Cell Volume ◽  
Diabetic Rats ◽  
Diabetic Patients

Aims: To investigate the effect of food blends (plantain, soybean and ginger) on the blood glucose, lipid profile and haematological indices on streptozotocin induced diabetic rats. Methodology: A total of 35 rats of mean body weight 219.07 g separated into7 groups (5 per group) where induced by a single intraperitoneal (I.P) injection of streptozotocin (0.1 g dissolved in 5 ml of freshly prepared sodium citrate buffer 0.1 M, pH 4.5) at a dose of 40 mg/kg body weight after fasting for 12 hours and fed with flours/blends. The flours were produced from plant materials for different treatments/blends (blend A=100% unripe plantain, B=80% unripe plantain, 14% soybean, 6% ginger, C=70% unripe plantain, 26% soybean, 4% ginger, D= 60% unripe plantain, 38% soybean, 2% ginger, E= 50% unripe plantain, 50% soybean) and the phytochemicals and minerals content were determined. Blood glucose was determined at 5 days interval for 25 days. Diabetes was confirmed in rats with blood glucose concentrations >200 mg/dl. After 25 days rats were anaesthetized with chloroform vapour and blood samples collected by cardiac puncture for haematology and lipid profile determination. Results: The results showed that unripe plantain, soya beans and ginger in adequate proportion(C=70% unripe plantain, 26% soybean, 4% ginger or D= 60% unripe plantain, 38% soybean, 2% ginger) could help to reduce blood glucose, improve haematological parameters and lipid profile. Significant reduction was observed in the blood glucose level of rats fed blends C and D from 286 to 85 mg/dl and 307 to 90 mg/dl respectively at the end of experiment. These results also demonstrated that the inclusion of ginger at 6% causes rise in blood glucose level. Total cholesterol (TC) increased in all the blends. However, the lowest concentration of TC was observed in blends C and D. The highest packed cell volume (60%) and Haemoglobin (20 g/dl) level observed in rats fed blend C was significantly higher than the normal control fed conventional feeds. The increase in packed cell volume (PCV) (50%) and Hb (17 g/dl) in diabetic rats demonstrated that the formulated blend C was able to raise PCV and Hb above 50% and 17 g/dl (Normal control NC) respectively. Significant increase (P<0.05) in low density lipoprotein cholesterol (LDLc) was also observed in all the blends with blend C having the least (4.0 mg/dl) close to NC (2.0 mg/dl). Conclusion: From the results it is evident that blend C will manage and improve the health status of diabetic patients.

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

2021 ◽  
Vol 5 (1) ◽  
pp. 14-25
Author(s):  
Nurul Fadhilah ◽  
Erfiani Erfiani ◽  
Indahwati Indahwati
Keyword(s):  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Principal Component Regression ◽  
Principal Component ◽  
Functional Regression ◽  
Glucose Levels ◽  
Non Invasive ◽  
Blood Glucose Levels ◽  
Functional Principal Component

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.

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