Journal of Innovative Optical Health Sciences, Volume. 10, Issue 2, 1650041(2017)
Monte Carlo simulation-based thinning and calculating method for noninvasive blood glucose sensing by near-infrared spectroscopy
[1] [1] Tarumi M., Shimada M., Murakami T., Tamura M., Shimada M., Arimoto H. and Yamada Y., Simulation study of in vitro glucose measurement by NIR spectroscopy and a method of error reduction, Phys. Med. Biol. 48 (2003) 2373–2390.
[2] [2] Martelli F. and Zaccanti G., Calibration of scattering and absorption properties of a liquid diffusive medium at NIR wavelengths. CW method, Opt. Express 15 (2) (2007) 486–500.
[3] [3] Chen W. L., Ma Z., An L. and Xu K. X., Applying the floating-reference method to improve the precision of noninvasive blood glucose measurement, Proc. SPIE 6445 (2007) 64450M.
[4] [4] Yu H., Qi D., Li H. D., Xu K. X. and Yuan W. J., Study on the experimental application of floating reference method to noninvasive blood glucose sensing, Spectrosc. Spect. Anal. 32 (2012) 770–774.
[5] [5] Chen Y., Shi Z. Z., Xu K. X. and Chen W. L., Study on Temperature correction of near-infrared spectral of solution, Spectrosc. Spect. Anal. 29 (2009) 2966–2969.
[6] [6] Zhang W. J., Liu R., Zhang W., Jia H. and Xu K. X., Discussion on the validity of NIR spectral data in non-invasive blood glucose sensing, Biomed. Opt. Express 4 (2013) 789–802.
[7] [7] Min X. L., Liu R., Hu Y. X., Fu B. and Xu K. X., Double-beam near-infrared spectroscopy to correct light source drift in aqueous glucose solution experiments, Anal. Methods 6 (2014) 9831–9840.
[8] [8] Yang Y., Chen W. L., Shi Z. Z. and Xu K. X., Reference point of floating-reference method for blood glucose sensing, Chin. Opt. Lett. 8 (2010) 421–424.
[9] [9] Jiang J. Y., Rong X. Z., Zhang H. and Xu K. X., A device to improve the SNR of the measurement of the positional floating reference point, Proc. SPIE 8580 (2013) 858019.
[10] [10] Wang Z. L., Zhang W. J., Li C. X., Chen W. L. and Xu K. X., The validation of the effect of correcting spectral background changes based on floating reference method by simulation, Spectrosc. Spect. Anal. 35 (2015) 547–551.
[11] [11] Mao Y. T., Theory of Error and Precision Analysis (National Defense Industry Press, Beijing, 1982).
[12] [12] Li Y. H. and Guo Y. K., Design of Modern Precision Instruments, 2nd edn. (Tsinghua University Press, Beijing, 2010).
[13] [13] Wang L., Jacques S. L. and Zheng L., MCML-Monte Carlo modeling of light transport in multi-layered tissues, Comput. Meth. Prog. Bio. 47 (1995) 131–146.
[14] [14] Zhong X. W., Wen X. and Zhu D., Lookup-table-based inverse model for human skin reflectance spectroscopy: two-layered Monte Carlo simulations and experiments, Opt. Express 22 (1) (2014) 1852–1864.
[15] [15] Zonios G. and Dimou A., Modeling diffuse reflectance from homogeneous semi-infinite turbid media for biological tissue applications: A Monte Carlo study, Opt. Express 2 (12) (2011) 3284–3294.
[16] [16] Kanick S. C., Robinson D. J., Sterenborg H. J. C. M. and Amelik A., Monte Carlo analysis of single fiber reflection spectroscopy: photon path length and sampling depth, Phys. Med. Biol. 54 (2009) 6991–7008.
[17] [17] Wen X., Zhong X. W., Yu T. T. and Zhu D., A Monte Carlo based lookup table for spectrum analysis of turbid media in the reflectance probe regime, Quantum Electronics 44 (7) (2014) 641–645.
[18] [18] Bish S. F., Rajaram N., Nichols B. and Tunnell J. W., Development of a noncontact diffuse optical spectroscopy probe for measuring tissue optical properties, J. Biomed. Opt. 16 (12) (2011) 120505.
[19] [19] Xu K. X., Gao F. and Zhao H. J., Biomedical Photonics, 2nd edn. (Science Press, Beijing, 2011).
[20] [20] Troy T. L. and Thennadil S. N., Optical properties of human skin in the near infrared wavelength range from 1000 to 2200nm, J. Biomed. Opt. 6 (2001) 167–176.
[21] [21] Palmer G. M. and Ramanujam N., Monte Carlo-based inverse model for calculating tissue optical properties. Part I: Theory and validation on synthetic phantoms, Appl. Opt. 45 (5) (2006) 1062–1071.
[22] [22] Rajaram N., Nguyen T. H. and Tunnell J. W., Lookup table–based inverse model for determining optical properties of turbid media, J. Biomed. Opt. 13 (5) (2008) 050501.
[23] [23] Qian Z., Victor S. S., Gu Y. Q., Giller C. A. and Liu H. L., Look-Ahead Distance” of a fiber probe used to assist neurosurgery: Phantom and Monte Carlo study, Opt. Express 11 (16) (2003) 1844–1855.
[24] [24] Luo B and He S. L., An improved Monte Carlo diffusion hybrid model for light reflectance by turbid media, Opt. Express 15 (10) (2007) 5905–5918.
[25] [25] Jacques S. L., Optical properties of biological tissues: A review, Phys. Med. Biol. 58 (2013) R37–R61.
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Congcong Ma, Jia Qin, Qi Zhang, Junsheng Lu, Kexin Xu, Jingying Jiang. Monte Carlo simulation-based thinning and calculating method for noninvasive blood glucose sensing by near-infrared spectroscopy[J]. Journal of Innovative Optical Health Sciences, 2017, 10(2): 1650041
Received: Dec. 25, 2015
Accepted: May. 10, 2016
Published Online: Dec. 27, 2018
The Author Email: Jiang Jingying (jingying@tju.edu.cn)