Evaluation of blood glucose concentration measurement using photoacoustic spectroscopy in near-infrared region

2017 ◽  
Author(s):  
Takeshi Namita ◽  
Mitsuki Sato ◽  
Kengo Kondo ◽  
Makoto Yamakawa ◽  
Tsuyoshi Shiina
Keyword(s):  
Blood Glucose ◽  
Photoacoustic Spectroscopy ◽  
Glucose Concentration ◽  
Near Infrared ◽  
Blood Glucose Concentration ◽  
Infrared Region ◽  
Concentration Measurement ◽  
Glucose Concentration Measurement ◽  
Near Infrared Region

Quantitative Spectroscopic Tomography for Non-invasive Blood Glucose Concentration Measurement

2014 ◽  
Vol 1 ◽  
pp. 86-89
Author(s):  
Satoru Suzuki ◽  
Ryosuke Tsutsumi ◽  
Asuka Inui ◽  
Daisuke Kojima ◽  
Akira Nishiyama ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glucose Concentration ◽  
Blood Glucose Concentration ◽  
Concentration Measurement ◽  
Non Invasive ◽  
Glucose Concentration Measurement

Photoacoustic Measurement and Experiment of Glucose Concentrations in an Aqueous Matrix

2013 ◽  
Vol 456 ◽  
pp. 652-655
Author(s):  
Guo Dong Liu ◽  
Jian Dong ◽  
Zhong Ren ◽  
Lv Ming Zeng ◽  
Hao Xu
Keyword(s):  
Blood Glucose ◽  
Near Infrared ◽  
Glucose Solution ◽  
Generalized Least Squares ◽  
Infrared Region ◽  
Exponential Fitting ◽  
Non Invasive ◽  
Linear Polynomial ◽  
Invasive Method ◽  
Near Infrared Region

In the near-infrared region, we can test the blood glucose by non-invasive method. Based on this theory, combined photoacoustic principle, we had research about the simulated samples of blood glucose, measured the concentration of glucose solution. We have discussed the optimal wavelength in the near-infrared region (780-2400nm), and did the experiment repeatedly, and then analyzed data through the linear, polynomial and exponential fitting of the Generalized Least Squares, the measuring accuracy of the glucose solution had improved. These research results provide the guidance on the practice and experimental evidence for the further research of measuring.

Noninvasive Blood Glucose Assay by Near-Infrared Diffuse Reflectance Spectroscopy of the Human Inner Lip

1993 ◽  
Vol 47 (7) ◽  
pp. 875-881 ◽  
Author(s):  
R. Marbach ◽  
Th. Koschinsky ◽  
F. A. Gries ◽  
H. M. Heise
Keyword(s):  
Blood Glucose ◽  
Glucose Concentration ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Diffuse Reflectance Spectroscopy ◽  
Blood Glucose Concentration ◽  
Venous Blood ◽  
Time Lag ◽  
Blood Glucose Concentrations

Near-infrared (NIR) spectra of the human inner lip were obtained by using a special optimized accessory for diffuse reflectance measurements. The partial-least squares (PLS) multivariate calibration algorithm was applied for linear regression of the spectral data between 9000 and 5500 cm−1 (Λ = 1.1–1.8 μm) against blood glucose concentrations determined by a standard clinical enzymatic method. Calibration experiments with a single person were carried out under varying conditions, as well as with a population of 133 different patients, with capillary and venous blood glucose concentration values provided. A genuine correlation between the blood glucose concentrations and the NIR-spectra can be proven. A time lag of about 10 min for the glucose concentration in the spectroscopically probed tissue volume vs. the capillary concentration can be estimated. Mean-square prediction errors obtained by cross-validation were in the range of 45 to 55 mg/dL. An analysis of different variance factors showed that the major contribution to the average prediction uncertainty was due to the reduced measurement reproducibility, i.e., variations in lip position and contact pressure. The results demonstrate the feasibility of using diffuse reflectance NIR-spectroscopy for the noninvasive measurement of blood glucose.

scholarly journals Noninvasive Monitoring of Blood Glucose Using Color-Coded Photoplethysmographic Images of the Illuminated Fingertip Within the Visible and Near-Infrared Range: Opportunities and Questions

2018 ◽  
Vol 12 (6) ◽  
pp. 1169-1177 ◽  
Author(s):  
Thorsten Vahlsing ◽  
Sven Delbeck ◽  
Steffen Leonhardt ◽  
H. Michael Heise
Keyword(s):  
Blood Glucose ◽  
Glucose Concentration ◽  
Near Infrared ◽  
Molecular Spectroscopy ◽  
Blood Glucose Concentration ◽  
Noninvasive Monitoring ◽  
Infrared Range ◽  
Self Monitoring ◽  
Spectral Signatures ◽  
Near Infrared Range

Noninvasive blood glucose assays have been promised for many years and various molecular spectroscopy-based methods of skin are candidates for achieving this goal. Due to the small spectral signatures of the glucose used for direct physical detection, moreover hidden among a largely variable background, broad spectral intervals are usually required to provide the mandatory analytical selectivity, but no such device has so far reached the accuracy that is required for self-monitoring of blood glucose (SMBG). A recently presented device as described in this journal, based on photoplethysmographic fingertip images for measuring glucose in a nonspecific indirect manner, is especially evaluated for providing reliable blood glucose concentration predictions.

scholarly journals Noninvasive blood glucose monitoring system based on near-infrared method

2020 ◽  
Vol 10 (2) ◽  
pp. 1736
Author(s):  
Mustafa Ayesh Al-dhaheri ◽  
Nasr-Eddine Mekkakia-Maaza ◽  
Hassan Mouhadjer ◽  
Abdelghani Lakhdari
Keyword(s):  
Blood Glucose ◽  
Monitoring System ◽  
Glucose Concentration ◽  
Near Infrared ◽  
Blood Glucose Concentration ◽  
Blood Glucose Monitoring ◽  
Calibration Model ◽  
Invasive Monitoring ◽  
Analog Filter ◽  
Noninvasive Technique

Diabetes is considered one of the life-threatening diseases in the world which need continuous monitoring to avoid the complication of diabetes. There is a need to develop a non-invasive monitoring system that avoids the risk of infection problems and pain caused by invasive monitoring techniques. This paper presents a method for developing a noninvasive technique to predict the blood glucose concentration (BCG) based on the Near-infrared (NIR) light sensor. A prototype is developed using a finger sensor based on LED of 940 nm wavelength to collect photoplethysmography (PPG) signal which is variable depending on the glucose concentration variance, a module circuit to preprocess PPG signals is realized, which includes an amplifier and analog filter circuits, an Arduino UNO is used to analog-to-digital conversion. A digital Butterworth filterer is used to remove PPG signal trends, then detect the PPG data peaks to determine the relationship between the PPG signal and (BCG) and use it as input parameters to build the calibration model based on linear regression. Experiments show that the Root Mean Squares Error (RMSE) of the prediction is between 8.264mg/dL and 13.166 mg/dL, the average of RMSE is about 10.44mg/dL with a correlation coefficient (R^2) of 0.839, it is observed that the prediction of glucose concentration is in the clinically acceptable region of the standard Clark Error Grid (CEG).

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