• Laser & Optoelectronics Progress
  • Vol. 54, Issue 3, 31703 (2017)
Li Dongming1、2、* and Jia Shuhai2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3788/lop54.031703 Cite this Article Set citation alerts
    Li Dongming, Jia Shuhai. Application of BP Artificial Neural Network in Blood Glucose Prediction Based on Multi-Spectrum[J]. Laser & Optoelectronics Progress, 2017, 54(3): 31703 Copy Citation Text show less
    References

    [1] Guariguata L, Whiting D R, Hambleton I, et al. Global estimates of diabetes prevalence for 2013 and projections for 2035[J]. Diabetes Research and Clinical Practice, 2014, 103(2): 137-149.

    [2] So C F, Choi K S, Wong T K, et al. Recent advances in noninvasive glucose monitoring[J]. Medical Devices: Evidence and Research, 2012, 5: 45-52.

    [3] Goodarzi M, Saeys W. Selection of the most informative near infrared spectroscopy wavebands for continuous glucose monitoring in human serum[J]. Talanta, 2016, 146(1): 155-165.

    [4] Goodarzi M, Sharma S, Ramon H, et al. Multivariate calibration of NIR spectroscopic sensors for continuous glucose monitoring[J]. TrAC Trends in Analytical Chemistry, 2015, 67: 147-158.

    [5] Vezouviou E, Lowe C R. A near infrared holographic glucose sensor[J]. Biosensors and Bioelectronics, 2015, 68(15): 371-381.

    [6] Yadava J, Rania A, Singh V, et al. Prospects and limitations of non-invasive blood glucose monitoring using near-infrared spectroscopy[J]. Biomedical Signal Processing and Control, 2015, 18: 214-227.

    [7] Cheng C, Cheng X S, Dai N, et al. Prediction of facial deformation after complete denture prosthesis using BP neural network[J]. Computers in Biology and Medicine, 2015, 66(1): 103-112.

    [8] Duan Chengpeng, Liu Wei, Chen Yaohong, et al. Multiple background sampling adaptive non-uniform correction algorithm[J]. Acta Optica Sinica, 2016, 36(10): 1020001.

    [9] Cheng Yuqiong, Lu Wei, Luo Hui, et al. Study on prediction of rice seed germination rate by using continuous polarization spectroscopy and inlaid grey neural network[J]. Acta Optica Sinica, 2015, 35(12): 1230001.

    [10] Cui Rixian, Liu Yadong, Fu Jindong. Estimation of winter wheat leaf nitrogen accumulation using machine learning algorithm and visible spectral[J]. Spectroscopy and Spectral Analysis, 2016, 36(6): 1837-1842.

    [11] Caduff A, Mueller M, Megej A, et al. Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation[J]. Biosensors and Bioelectronics, 2011, 26(9): 3794-3800.

    [12] Li D M, Jia S H, Wang J. Study on continuous monitoring glucose concentration with terbium gallium garnet crystal[C]. International Conference on Advanced Design and Manufacturing Engineering, 2011, 317-319: 53-57.

    [13] Dong J, Zhuang D F, Huang Y H, et al. Advances in multi-sensor data fusion: algorithms and applications[J]. Sensors, 2009, 9(10): 7771-7784.

    [14] Wu B, Han S J, Xiao J, et al. Error compensation based on BP neural network for airborne laser ranging[J]. Optik, 2016, 127(8): 4083-4088.

    [15] Sivananthan S, Naumova V, Man C D, et al. Assessment of blood glucose predictors: the prediction-error grid analysis[J]. Diabetes Technology Therapeutics, 2011, 13(8): 787-796.

    Li Dongming, Jia Shuhai. Application of BP Artificial Neural Network in Blood Glucose Prediction Based on Multi-Spectrum[J]. Laser & Optoelectronics Progress, 2017, 54(3): 31703
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