scholarly journals A Noninvasive Accurate Measurement of Blood Glucose Levels with Raman Spectroscopy of Blood in Microvessels

Molecules ◽  
2019 ◽  
Vol 24 (8) ◽  
pp. 1500 ◽  
Author(s):  
Nan Li ◽  
Hang Zang ◽  
Huimin Sun ◽  
Xianzhi Jiao ◽  
Kangkang Wang ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Blood Glucose ◽  
Raman Spectra ◽  
Interstitial Fluid ◽  
Time Lag ◽  
Back Propagation ◽  
Principal Component ◽  
Oral Glucose ◽  
Multiple Characteristic ◽  
Non Invasive

Raman spectra of human skin obtained by laser excitation have been used to non-invasively detect blood glucose. In previous reports, however, Raman spectra thus obtained were mainly derived from the epidermis and interstitial fluid as a result of the shallow penetration depth of lasers in skin. The physiological process by which glucose in microvessels penetrates into the interstitial fluid introduces a time delay, which inevitably introduces errors in transcutaneous measurements of blood glucose. We focused the laser directly on the microvessels in the superficial layer of the human nailfold, and acquired Raman spectra with multiple characteristic peaks of blood, which indicated that the spectra obtained predominantly originated from blood. Incorporating a multivariate approach combining principal component analysis (PCA) and back propagation artificial neural network (BP-ANN), we performed noninvasive blood glucose measurements on 12 randomly selected volunteers, respectively. The mean prediction performance of the 12 volunteers was obtained as an RMSEP of 0.45 mmol/L and R2 of 0.95. It was no time lag between the predicted blood glucose and the actual blood glucose in the oral glucose tolerance test (OGTT). We also applied the procedure to data from all 12 volunteers regarded as one set, and the total predicted performance was obtained with an RMSEP of 0.27 mmol/L and an R2 of 0.98, which is better than that of the individual model for each volunteer. This suggested that anatomical differences between volunteer fingernails do not reduce the prediction accuracy and 100% of the predicted glucose concentrations fall within Region A and B of the Clarke error grid, allowing acceptable predictions in a clinically relevant range. The Raman spectroscopy detection of blood glucose from microvessels is of great significance of non-invasive blood glucose detection of Raman spectroscopy. This innovative method may also facilitate non-invasive detection of other blood components.

Non-invasive prediction of bloodstain age using the principal component and a back propagation artificial neural network

2017 ◽  
Vol 14 (9) ◽  
pp. 095601 ◽  
Author(s):  
Huimin Sun ◽  
Yaoyong Meng ◽  
Pingli Zhang ◽  
Yajing Li ◽  
Nan Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Back Propagation ◽  
Principal Component ◽  
Non Invasive ◽  
Artificial Neural

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.

Raman Spectroscopy System for Non-invasive Blood Glucose Detection

2017 ◽  
Vol 46 (8) ◽  
pp. 812005 ◽  
Author(s):  
郑毅 ZHENG Yi ◽  
朱香平 ZHU Xiang-ping ◽  
聂荣志 NIE Rong-zhi ◽  
高飞 GAO Fei ◽  
崔晓霞 CUI Xiao-xia ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Blood Glucose ◽  
Glucose Detection ◽  
Non Invasive ◽  
Spectroscopy System

Heating Effects of Desi Ghee Using Raman Spectroscopy

2018 ◽  
Vol 72 (6) ◽  
pp. 833-846 ◽  
Author(s):  
Naveed Ahmad ◽  
Muhammad Saleem ◽  
Mushtaq Ahmed ◽  
Shaukat Mahmood
Keyword(s):  
Principal Component Analysis ◽  
Raman Spectroscopy ◽  
Raman Spectra ◽  
Principal Component ◽  
Nondestructive Technique ◽  
Molecular Changes ◽  
Spectral Bands ◽  
Heating Effects ◽  
Excitation Laser ◽  
First Time

Raman spectroscopy as a fast and nondestructive technique has been used to investigate heating effects on Desi ghee during frying/cooking of food for the first time. A temperature in the range of 140–180℃ has been investigated within which Desi ghee can be used safely for cooking/frying without much alteration of its natural molecular composition. In addition, heating effects in case of reuse, heating for different times, and cooking inside pressure cookers are also presented. An excitation laser at 785 nm has been used to obtain Raman spectra and the range of 540–1800 cm−1 is found to contain prominent spectral bands. Prominent variations have been observed in the Raman bands of 560–770 cm−1, 790–1160 cm−1, and 1180–1285 cm−1 with the rise in temperature. The spectral variations have been verified using classifier principal component analysis. It has been found that Desi ghee can be reused if heated below 180℃ and it can be heated up to 30 min without any appreciable molecular changes if a controlled heating can be managed.

scholarly journals Detection of Age-Related Changes in Tendon Molecular Composition by Raman Spectroscopy—Potential for Rapid, Non-Invasive Assessment of Susceptibility to Injury

2020 ◽  
Vol 21 (6) ◽  
pp. 2150
Author(s):  
Nai-Hao Yin ◽  
Anthony W. Parker ◽  
Pavel Matousek ◽  
Helen L. Birch
Keyword(s):  
Raman Spectroscopy ◽  
Raman Spectra ◽  
Flexor Tendon ◽  
Biological Tissues ◽  
Ring Structure ◽  
Total N ◽  
Non Invasive ◽  
Age Related ◽  
Superficial Digital Flexor Tendon

The lack of clinical detection tools at the molecular level hinders our progression in preventing age-related tendon pathologies. Raman spectroscopy can rapidly and non-invasively detect tissue molecular compositions and has great potential for in vivo applications. In biological tissues, a highly fluorescent background masks the Raman spectral features and is usually removed during data processing, but including this background could help age differentiation since fluorescence level in tendons increases with age. Therefore, we conducted a stepwise analysis of fluorescence and Raman combined spectra for better understanding of the chemical differences between young and old tendons. Spectra were collected from random locations of vacuum-dried young and old equine tendon samples (superficial digital flexor tendon (SDFT) and deep digital flexor tendon (DDFT), total n = 15) under identical instrumental settings. The fluorescence-Raman spectra showed an increase in old tendons as expected. Normalising the fluorescence-Raman spectra further indicated a potential change in intra-tendinous fluorophores as tendon ages. After fluorescence removal, the pure Raman spectra demonstrated between-group differences in CH2 bending (1450 cm−1) and various ring-structure and carbohydrate-associated bands (1000–1100 cm−1), possibly relating to a decline in cellular numbers and an accumulation of advanced glycation end products in old tendons. These results demonstrated that Raman spectroscopy can successfully detect age-related tendon molecular differences.

scholarly journals Raman Spectroscopy in Colorectal Cancer Diagnostics: Comparison of PCA-LDA and PLS-DA Models

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Wenjing Liu ◽  
Zhaotian Sun ◽  
Jinyu Chen ◽  
Chuanbo Jing
Keyword(s):  
Colorectal Cancer ◽  
Raman Spectroscopy ◽  
Discriminant Analysis ◽  
Diagnostic Accuracy ◽  
Raman Spectra ◽  
Principal Component ◽  
Cancer Diagnostics ◽  
Analysis Model ◽  
Tissue Samples ◽  
Linear Discriminant

Raman spectra of human colorectal tissue samples were employed to diagnose colorectal cancer. High-quality Raman spectra were acquired from normal and cancerous colorectal tissues from 81 patients. Subtle Raman variations, such as for peaks at 1134 cm−1 (protein, C-C/C-N stretching) and 1297 cm−1 (lipid, C-H2 twisting), were observed between normal and cancerous colorectal tissues. The average peak intensity at 1134 and 1297 cm−1 was increased from approximately 235 and 72 in the normal group, respectively, to 315 and 273 in the cancer group. The variations of Raman spectra reflected the changes of cell molecules during canceration. The multivariate statistical methods of principal component analysis-linear discriminant analysis (PCA-LDA) and partial least-squares-discriminant analysis (PLS-DA), together with leave-one-patient-out cross-validation, were employed to build the discrimination model. PCA-LDA was used to evaluate the capability of this approach for classifying colorectal cancer, resulting in a diagnostic accuracy of 79.2%. Further PLS-DA modeling yielded a diagnostic accuracy of 84.3% for colorectal cancer detection. Thus, the PLS-DA model is preferable between the two to discriminate cancerous from normal tissues. Our results demonstrate that Raman spectroscopy can be used with an optimized multivariate data analysis model as a sensitive diagnostic alternative to identify pathological changes in the colon at the molecular level.

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