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光学无创血糖浓度检测方法的研究进展

郭帅 苏杭 黄星灿 刘剑

郭帅, 苏杭, 黄星灿, 刘剑. 光学无创血糖浓度检测方法的研究进展[J]. 中国光学(中英文), 2019, 12(6): 1235-1248. doi: 10.3788/CO.20191206.1235
引用本文: 郭帅, 苏杭, 黄星灿, 刘剑. 光学无创血糖浓度检测方法的研究进展[J]. 中国光学(中英文), 2019, 12(6): 1235-1248. doi: 10.3788/CO.20191206.1235
GUO Shuai, SU Hang, HUANG Xing-can, LIU Jian. Research progress in optical methods for noninvasive blood glucose detection[J]. Chinese Optics, 2019, 12(6): 1235-1248. doi: 10.3788/CO.20191206.1235
Citation: GUO Shuai, SU Hang, HUANG Xing-can, LIU Jian. Research progress in optical methods for noninvasive blood glucose detection[J]. Chinese Optics, 2019, 12(6): 1235-1248. doi: 10.3788/CO.20191206.1235

光学无创血糖浓度检测方法的研究进展

doi: 10.3788/CO.20191206.1235
基金项目: 

国家自然科学基金资助项目 61801256

山东省重点研发计划资助项目 2018GGX109016

山东省自然科学基金 ZR2019MEE051

北京市自然科学基金 4182075

详细信息
    作者简介:

    郭帅(1993—), 男, 山西朔州人, 硕士研究生, 2016年于大连理工大学获得学士学位, 主要从事智能光学分析仪器开发方面的研究。E-mail:gxsld@foxmail.com

    刘剑(1977—), 男, 山东莱芜人, 博士, 副教授, 2008年于中国科学院电子学研究所获得博士学位, 主要从事生物医学传感与检测方面的研究。E-mail:lj@sdu.edu.cn

  • 中图分类号: R318.51

Research progress in optical methods for noninvasive blood glucose detection

Funds: 

Natural Science Foundation of China 61801256

Key Research and Development Projects of Shandong Province 2018GGX109016

Shandong Natural Science Foundation ZR2019MEE051

Natural Science Foundation of Beijing 4182075

More Information
  • 摘要: 连续监测血糖浓度是控制糖尿病及其并发症的前提,无创伤性血糖浓度检测方法备受关注。近几十年来,随着测量精度的不断提高,基于光学的无创伤性血糖浓度检测方法呈现出巨大发展潜力,有望在未来实现临床应用。本文详细介绍了偏振光旋光法、光学相干断层成像法、红外光谱法等主流光学无创血糖检测方法,重点对其基本原理、测量优势、测量精度、存在问题与可能解决方法等进行了综述和分析,对比发现红外光谱法在测量精度方面具有明显优势。最后指出未来还需从提高仪器信噪比、消除背景干扰以及建立更加普适的校正模型等方面展开研究。

     

  • 图 1  光纤式迈克尔逊干涉仪结构示意图[37]

    Figure 1.  Structural schematic of fiber-optic Michelson interferometer[37]

    图 2  红外光谱法原理图[46]

    Figure 2.  Principle schematic of detection method of infrared spectroscopy[46]

    图 3  通过ATR-FTIR获得的40~400 mg/dL葡萄糖溶液中红外光谱图[16]

    Figure 3.  Mid-infrared spectra for nine aqueous glucose concentrations between 40 and 400 mg/dL obtained by ATR-FTIR spectroscopy[16]

    图 4  受试者手掌散射光谱图(a)及预测血糖浓度曲线与预期血糖浓度曲线对比(b)[58]

    Figure 4.  Spectra of backscattered light from the palm of a human subject(a); comparison between the predicted and the expected blood glucose concentrations(b)[58]

    图 5  光声光谱法系统示意图[23]

    Figure 5.  Schematic of photoacoustic spectroscopy system[23]

    表  1  光学无创血糖浓度检测的精度

    Table  1.   The accuracies of optical methods for noninvasive blood glucose detection  SEP:mg/dL

    Optical methods Glucosesolution Bloodserum Blood plasma Livingrabbit/pig Humansubject
    Polarimetry Stationary:4.30[35] 20.63(SD)[32] 11.66(MARD)[30]
    Moving:13.50[35]
    OCT 17.00[10]Note1 8.21(RMSE)[38]
    NIR spectroscopy 8.10[48] 9.00[47] 20.38[49] 10.00(RMSE)[78]
    Mid-IR spectroscopy 3.50(RMSE)[17] 7.38(SD)[79] 17.10[80] 9.60[81]
    Raman spectroscopy 20.71(SD)[18] 7.80%±1.80%[19]Note2
    Photoacoustic spectroscopy 12.14(RMSE)[82] 10.97(RMSE)[83]
          Note 1:Minimum prediction uncertainty is 17.00 mg/dL; Note 2:MAE of blood glucose is 7.8%±1.8%.
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  • 收稿日期:  2018-11-29
  • 修回日期:  2019-01-09
  • 刊出日期:  2019-12-01

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