Monte Carlo simulation of near infrared autofluorescence measurements of in vivo skin

2011 ◽  
Vol 105 (3) ◽  
pp. 183-189 ◽  
Author(s):  
Shuang Wang ◽  
Jianhua Zhao ◽  
Harvey Lui ◽  
Qingli He ◽  
Haishan Zeng
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Near Infrared

Study of the Influence of Radionuclide Biokinetics on the Efficiency of In Vivo Counting Using Monte Carlo Simulation

2009 ◽  
Vol 96 (5) ◽  
pp. 558-567 ◽  
Author(s):  
Stephanie Lamart ◽  
Eric Blanchardon ◽  
Andrey Molokanov ◽  
Gary H. Kramer ◽  
David Broggio ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo

Noninvasive Alcohol Detection Using Near-Infrared Spectroscopy Based on Partial Least Squares and Monte-Carlo

2012 ◽  
Vol 229-231 ◽  
pp. 1308-1311
Author(s):  
Si Te Luo ◽  
Guo Qiang Chen ◽  
Ruo Fei Cui ◽  
Wei Wei Zhou ◽  
Li Qian Lu ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Blood Alcohol Concentration ◽  
Test Method ◽  
Calibration Model ◽  
Good Prediction ◽  
Good Prediction Accuracy

The objective of this study was to assess the feasibility of noninvasive alcohol testing in vivo with near-infrared (NIR) spectroscopy. The suitable distance between light source and detector was determined by Monte-Carlo simulation. The NIR spectra signals of alcohol in vitro and in vivo were measured, and the blood alcohol concentration (BAC) was measured with breath test method. Wavelet de-noising and partial least squares (PLS) method were used to establish the quantitative calibration model of alcohol. The results indicate that alcohol spectra had two absorption peaks at range of 2200nm～2400nm. The optimal principal component number of PLS model is 3, RMSEP=9.29, MREP=3.5%，R=0.9802. The model has good prediction accuracy. NIRS might provide a new method to the measurement of alcohol in vivo.

Investigation of the particle size-dependent near-infrared spectral features of binary mixture samples in conjunction with Monte Carlo simulation and the influence of particle size on the accuracy of quantitative analysis

The Analyst ◽  
2018 ◽  
Vol 143 (18) ◽  
pp. 4306-4315 ◽  
Author(s):  
Pham K. Duy ◽  
Seulah Chun ◽  
Yoonjeong Lee ◽  
Hoeil Chung
Keyword(s):  
Monte Carlo Simulation ◽  
Particle Size ◽  
Monte Carlo ◽  
Quantitative Analysis ◽  
Near Infrared ◽  
Spectral Variation ◽  
Spectral Features ◽  
Size Dependent ◽  
Infrared Spectral ◽  
Mixture Samples

The origin of particle size-induced near-infrared (NIR) spectral variation, which is fundamental for robust quantitative analysis, was systematically studied in conjunction with Monte Carlo simulation.

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