Study on the Best Detector-Distance of Noninvasive Biochemical Examination by Monte Carlo Simulation
DONG Yan-fei1, 2, LU Qi-peng1*, DING Hai-quan1, GAO Hong-zhi1
1. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China 2. University of Chinese Academy of Sciences, Beijing 100049, China
Abstract：The present paper studies the best detector-distance to improve the near-infrared spectrum signal intensity of the dermis layer and eliminate the interference of the epidermis and subcutaneous layer. First, we analyzed the organizational structure of the skin and calculated the tissue optical parameters of different layers. And we established the Monte Carlo model with the example of glucose absorption peak at 2 270 nm. Then, we used the Monte Carlo method to simulate the light transmission rules in the skin, obtaining the average path length, the average visit depth and the fractions of absorbed energy at each layer with the change in critical angle and detector-distance. The results show that when the photons are incident at an angle less than 45 degrees, you can ignore the effect of the incident angle on photon transmission path, and when the detector-distance is 1 mm, the fraction of absorbed photon energy by the dermis layer is the largest, while it can ensure more energy received by detector. We determined that the best detector-distance is 1mm, which successfully avoids the interference of the epidermis spectral information and obtains large amounts of blood in the dermis layer, which is conducive to the near-infrared non-invasive measurement of biochemical components and the subsequent experiments.
Key words：Near-infrared spectrum;Non-invasive biochemical detection;Monte Carlo simulation;Best detector-distance;Tissue optics
董艳飞1, 2，卢启鹏1*，丁海泉1，高洪智1 . 基于蒙特卡罗模拟的无创生化检测最佳探测距离的研究 [J]. 光谱学与光谱分析, 2014, 34(04): 942-946.
DONG Yan-fei1, 2, LU Qi-peng1*, DING Hai-quan1, GAO Hong-zhi1 . Study on the Best Detector-Distance of Noninvasive Biochemical Examination by Monte Carlo Simulation. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2014, 34(04): 942-946.
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