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Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 4 >Page 041701 > Article

Laser & Optoelectronics Progress
Vol. 56, Issue 4, 041701 (2019)

Comparison of Multi-Factor-Considered Blood Glucose Prediction Models by Near-Infrared Spectroscopy

Xiaofei Wang^*, Xinyi Zhang, and Xinhe Xu

Author Affiliations

School of Instrumentation Science and Optoelectronic Engineering, Beijing Information Science and Technology University, Beijing 100192, China

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DOI: 10.3788/LOP56.041701 Cite this Article Set citation alerts

Xiaofei Wang, Xinyi Zhang, Xinhe Xu. Comparison of Multi-Factor-Considered Blood Glucose Prediction Models by Near-Infrared Spectroscopy[J]. Laser & Optoelectronics Progress, 2019, 56(4): 041701 Copy Citation Text

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References

[1] Yang X, Ji Z, Yang L et al. The principles and research status of noninvasive glucose detection based on near-infrared spectrum[J]. Journal of Biomedical Engineering, 30, 204-207(2013).

[2] Wang X F, Zhao W J. Measurement of multi-wavelength pulse oxygen saturation based on dynamic spectroscopy[J]. Spectroscopy and Spectral Analysis, 34, 1323-1326(2014).

[3] Zhang Y, Ni J S, Zhang Y Z et al. Tissue intrinsic fluorescence spectrum recovery algorithm and its application in diabetes screening[J]. Chinese Journal of Lasers, 45, 0707001(2018).

[4] Li D M, Jia S H. Application of BP artificial neural network in blood glucose prediction based on multi-spectrum[J]. Laser & Optoelectronics Progress, 54, 031703(2017).

[5] Sun K, Zhou H, Yang Y K et al. Research advances in blood glucose monitoring system[J]. Chinese Journal of Lasers, 45, 0207003(2018).

[6] Li G, Li Z, Wang X F et al. Evolution of measure mode and proposition of “M+N” theory[J]. Journal of Beijing Information Science & Technology University, 28, 9-13(2013).

[7] Xu X H, Wang X F. Near-infrared spectra noninvasive measurement method of glucose based on the “M+N” theory[J]. Research and Exploration in Laboratory, 37, 5-9, 14(2018).

[8] Li L, Wang X F, Lu K. Near-infrared spectra noninvasive measurement method of blood oxygen saturation based on the “M+N” theory[J]. Journal of Biomedical Engineering, 33, 885-889(2016).

[9] Zhou Z H[M]. Machine learning, 121-145(2016).

[10] Li G, Wang H Q, Zhao Z et al. The quality evaluation of dynamic spectrum data[J]. Spectroscopy and Spectral Analysis, 30, 2802-2806(2010).

[12] Li G, Xiong C, Wang H Q et al. Single-trial estimation of dynamic spectrum[J]. Spectroscopy and Spectral Analysis, 31, 1857-1861(2011).

[13] Lin L, Li Y C, Wang M J et al. D-value estimation of dynamic spectrum based on the statistical methods[J]. Spectroscopy and Spectral Analysis, 32, 3098-3102(2012).

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Xiaofei Wang, Xinyi Zhang, Xinhe Xu. Comparison of Multi-Factor-Considered Blood Glucose Prediction Models by Near-Infrared Spectroscopy[J]. Laser & Optoelectronics Progress, 2019, 56(4): 041701

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