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

Congcong Ma1... Jia Qin2, Qi Zhang1, Junsheng Lu1, Kexin Xu3 and Jingying Jiang1,* |Show fewer author(s)
Author Affiliations
  • 1Tianjin Key Laboratory of Biomedical, Detecting Techniques and Instruments, College of Precision Instruments & Opto-electronics Engineering, Tianjin University (TU), 92# Weijin Road, Nankai District, Tianjin 300072, P. R. China
  • 2San Francisco, Ophthalmology, University of California, 480 North Civic Drive 106, Walnut Creek, California 94596, United States
  • 3State Key Laboratory of Precision Measuring Technology and Instruments, College of Precision Instruments & Opto-electronics Engineering, Tianjin University (TU), 92# Weijin Road, Nankai District, Tianjin 300072, P. R. China
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    Previous results show that the floating reference theory (FRT) is an effective tool to reduce the influence of interference factors on noninvasive blood glucose sensing by near-infrared spectros-copy (NIRS). It is the key to measure the floating reference point (FRP) precisely for the application of FRT. Monte Carlo (MC) simulation has been introduced to quantitatively in-vestigate the effects of positioning errors and light source drifts on measuring FRP. In this article, thinning and calculating method (TCM) is proposed to quantify the positioning error. Mean-while, the normalization process (NP) is developed to significantly reduce the error induced by light source drift. The results according to TCM show that 7 m deviations in positioning can generate about 10.63% relative error in FRP. It is more noticeable that 1% fluctuation in light source intensity may lead to 12.21% relative errors. Gratifyingly, the proposed NP model can effectively reduce the error caused by light source drift. Therefore, the measurement system for FRPs must meet that the positioning error is less than 7 m, and the light source drift is kept within 1%. Furthermore, an improvement for measurement system is proposed in order to take advantage of the NP model.

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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

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    Paper Information

    Received: Dec. 25, 2015

    Accepted: May. 10, 2016

    Published Online: Dec. 27, 2018

    The Author Email: Jiang Jingying (jingying@tju.edu.cn)

    DOI:10.1142/s1793545816500413

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