Ridge Robust Regression Analysis on Measurement of Non-Invasive Blood Glucose Levels

2020 ◽  
Vol 10 (06) ◽  
pp. 913-917
Author(s):  
Linda Rassiyanti ◽  
Erfiani . ◽  
Indahwati .
Keyword(s):  
Regression Analysis ◽  
Blood Glucose ◽  
Robust Regression ◽  
Glucose Levels ◽  
Non Invasive ◽  
Blood Glucose Levels

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.

scholarly journals Non-Invasive Determination of Blood Glucose Levels by Optical Waveguide

2021 ◽  
Author(s):  
Mohsen Askarbioki ◽  
Mojtaba Mortazavi ◽  
Abdolhamid Amooee ◽  
Saeid Kargar ◽  
Mohammad Afkhami-Ardekani ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Optical Waveguide ◽  
Interstitial Fluid ◽  
Evanescent Waves ◽  
The Body ◽  
Statistical Population ◽  
Glucose Levels ◽  
Non Invasive ◽  
Blood Glucose Levels

Objective: Today, there are various non-invasive techniques available for the determination of blood glucose levels. In this study, the level of blood glucose was determined by developing a new device using near-infrared (NIR) wavelength, glass optical waveguide, and the phenomenon of evanescent waves. Materials and Methods: The body's interstitial fluid has made possible the development of new technology to measure the blood glucose. As a result of contacting the fingertip with the body of the borehole rod, where electromagnetic waves are reflected inside, evanescent waves penetrate from the borehole into the skin and are absorbed by the interstitial fluid. The electromagnetic wave rate absorption at the end of the borehole rod is investigated using a detection photodetector, and its relationship to the people's actual blood glucose level. Following precise optimization and design of the glucose monitoring device, a statistical population of 100 participants with a maximum blood glucose concentration of 200 mg/dL was chosen. Before measurements, participants put their index finger for 30 seconds on the device. Results: According to this experimental study, the values measured by the innovative device with Clark grid analysis were clinically acceptable in scales A and B. The Adjusted Coefficient of Determination of the data was estimated to be 0.9064. Conclusion: For future investigations, researchers are recommended to work with a larger statistical population and use error reduction trends to improve the accuracy and expand the range of measurements.

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

Sensors ◽  
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.

scholarly journals BREATH ACETONE-BASED NON-INVASIVE DETECTION OF BLOOD GLUCOSE LEVELS

2015 ◽  
Vol 8 (2) ◽  
pp. 1244-1260 ◽  
Author(s):  
Anand Thati ◽  
Arunangshu Biswas ◽  
Shubhajit Roy Chowdhury ◽  
Tapan Kumar Sau
Keyword(s):  
Blood Glucose ◽  
Glucose Levels ◽  
Non Invasive ◽  
Blood Glucose Levels ◽  
Breath Acetone

scholarly journals Risk factors for acute kidney injury and mortality in high risk patients undergoing cardiac surgery

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0252209
Author(s):  
Giuseppe Filiberto Serraino ◽  
Michele Provenzano ◽  
Federica Jiritano ◽  
Ashour Michael ◽  
Nicola Ielapi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acute Kidney Injury ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cardiac Surgery ◽  
Blood Glucose ◽  
Kidney Injury ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Risk Patients

Background Acute Kidney Injury (AKI) represents a clinical condition with poor prognosis. The incidence of AKI in hospitalized patients was about 22–57%. Patients undergoing cardiac surgery (CS) are particularly exposed to AKI because of the related oxidative stress, inflammation and ischemia-reperfusion damage. Hence, the risk profile of patients undergoing CS who develop AKI and who are consequently at increased mortality risk deserves further investigation. Methods We designed a retrospective study examining consecutive patients undergoing any type of open-heart surgery from January to December 2018. Patients with a history of AKI were excluded. AKI was diagnosed according to KDIGO criteria. Univariate associations between clinical variables and AKI were tested using logistic regression analysis. Variable thresholds maximizing the association with AKI were measured with the Youden index. Multivariable logistic regression analysis was performed to assess predictors of AKI through backward selection. Mortality risk factors were assessed through the Cox proportional hazard model. Results We studied 158 patients (mean age 51.2±9.7 years) of which 74.7% were males. Types of procedures performed were: isolated coronary artery bypass (CABG, 50.6%), valve (28.5%), aortic (3.2%) and combined (17.7%) surgery. Overall, incidence of AKI was 34.2%. At multivariable analysis, young age (p = 0.016), low blood glucose levels (p = 0.028), estimated Glomerular Filtration Rate (p = 0.007), pH (p = 0.008), type of intervention (p = 0.031), prolonged extracorporeal circulation (ECC, p = 0.028) and cross-clamp (p = 0.021) times were associated with AKI. The threshold for detecting AKI were 91 and 51 minutes for ECC and cross-clamp times, respectively. At survival analysis, the presence of AKI, prolonged ECC and cross-clamp times, and low blood glucose levels forecasted mortality. Conclusions AKI is common among CS patients and associates with shortened life-expectancy. Several pre-operative and intra-operative predictors are associated with AKI and future mortality. Future studies, aiming at improving prognosis in high-risk patients, by a stricter control of these factors, are awaited.

scholarly journals Bioimpedance and NIR for non-invasive assessment of blood glucose

2019 ◽  
Vol 10 (1) ◽  
pp. 133-138 ◽  
Author(s):  
Jan-Hugo Andersen ◽  
Olav Bjerke ◽  
Fatos Blakaj ◽  
Vilde Moe Flugsrud ◽  
Fredrik Alstad Jacobsen ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Electrical Impedance ◽  
Near Infrared ◽  
Soft Drink ◽  
Electrical Impedance Spectroscopy ◽  
Electrical Measurements ◽  
High Blood Glucose ◽  
Glucose Levels ◽  
Non Invasive ◽  
Blood Glucose Levels

Abstract Sixteen volunteers each drank 700 ml sugar-containing soft drink during two successive periods and the blood sugar was measured at 10 min intervals together with electrical impedance spectroscopy and near infrared spectroscopy (NIR). A maximum correlation of 0.46 was found for the electrical measurements but no clear separation between low and high blood glucose levels were found in the NIR measurements. The latter was attributed to the experimental design where the NIR probe was removed from the skin between each measurement.

scholarly journals Pre-clinical test for non-invasive (in vitro) blood glucose levels measuring at visible light wavelengths

2021 ◽  
Author(s):  
Irzaman ◽  
R. P. Jenie ◽  
Y. Suryana ◽  
S. Prambudi ◽  
T. Widayanti ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Visible Light ◽  
Clinical Test ◽  
Glucose Levels ◽  
Non Invasive ◽  
Blood Glucose Levels

scholarly journals Self-Isolation Negatively Impacts Self-Management of Diabetes During the Coronavirus (COVID-19) Pandemic

2021 ◽  
Author(s):  
Shahina Pardhan ◽  
Md. Saiful Islam ◽  
Guillermo F. López-Sánchez ◽  
Tirthalal Upadhyaya ◽  
Raju Sapkota
Keyword(s):  
Regression Analysis ◽  
Blood Glucose ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Healthy Diet ◽  
Self Management ◽  
Outcome Variable ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
History Of

Abstract Background/Aim: People with diabetes are at a greater risk of serious complications from Coronavirus disease (COVID-19). Self-management of diabetes is therefore of paramount importance. The purpose of this study is to compare self-management of diabetes pre-COVID-19 and during COVID-19 pandemic. Methods: 679 participants with diabetes completed an online structured questionnaire. Outcome variables that were analysed were: (i) fluctuation of blood glucose levels, (ii) access to diabetes medicine, (iii) access to healthy diet, and (iv) physical activity. Adjusted multiple regression analysis ascertained significant associations for each outcome variable against exposure variables such as demographics (age/gender), history of diabetes (duration, treatment, and complications) and the need for self-isolation. Results: Multiple regression analysis showed that self-isolation was significantly associated with greater fluctuation in blood glucose levels (OR=1.8, 95% CI=1.2-2.6, p=0.005), worsened access to diabetes medicine (OR=1.9, 95% CI=1.1-3.1, p=0.02) and reduced access to healthy diet (OR=3.0, 95% CI= 2.0-4.6, p<0.001). Fluctuating blood glucose was also significantly associated with having at least one complication of diabetes (OR=2.2, 95 % CI=1.2-3.9, p=0.008) and worsened access to diabetes medicine was significantly higher in people who were on insulin (OR=2.1, 95% CI=1.3-3.3, p=0.001). Conclusions: Self-isolation impacted various factors that influence self-management of diabetes. A targeted approach to improved access to diabetes medicine and healthy diet for people needing to self-isolate is vital in order to ensure that they are able to self-manage their diabetes effectively.

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