scholarly journals Ultraviolet to visible spectrophotometry observation to find appropriate wavelength for non-invasive blood glucose level measurement optical device

2021 ◽  
Author(s):  
R. P. Jenie ◽  
Y. Suryana ◽  
S. Pambudi ◽  
T. Widayanti ◽  
A. Audina ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Optical Device ◽  
Visible Spectrophotometry ◽  
Non Invasive ◽  
Level Measurement

Metrological support of individual blood glucose meters in telemedicine

2019 ◽  
pp. 52-56
Author(s):  
Yu.F. Glukhov ◽  
N.V. Krutikov ◽  
A.V. Ivanov ◽  
N.P. Muravskaya
Keyword(s):  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Measurement Data ◽  
Test Method ◽  
Level Measurement ◽  
Measurement Devices ◽  
Real Practice ◽  
Health Care Centers ◽  
Medical Measurement

We have studied and analyzed status and metrological supervision of blood glucose monitors, individual devices for a person’s blood glucose level measurement. It has been indicated that nowadays blood glucose monitors like other individual devices for medical measurement are not allowed to be involved in telemedicine public service. This accounts for absence of metrological supervision with these measurement devices in telemedicine. In addition, the key problem is absence of safe methods and means of remote verificaition, calibration and transmission of measurement data to health care centers. The article offers a remote test method for blood glucose monitors using a number of resistors with values correlating with measured blood glucose level. The available method has been successfully trialed in real practice.

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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