Application of SG-MSC-MC-UVE-PLS Algorithm in Whole Blood Hemoglobin Concentration Detection Based on Near Infrared Spectroscopy
SUN Dai-qing1, 2, XIE Li-rong1*, ZHOU Yan2, GUO Yu-tao1, CHE Shao-min2
1. School of Electrical Engineering, Xinjiang University, Urumqi 830047, China
2. School of Energy & Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Abstract：In order to improve the accuracy of the whole blood hemoglobin (Hb) concentration prediction model, the original whole blood transmission spectrum signals were first preprocessed by using centering, auto scaling, standard normal variate (SNV), multiplicative scatter correction (MSC), and Savitzky-Golay (SG) smoothing combined with MSC. And the best preprocessing effect was obtained with a R2 value of 0.9441 by using SG smoothing combined with MSC. The width of the SG smoothing window was discussed, and the optimal width is 27.The baseline shift of the whole blood absorbance signals was eliminated, and the signal-to-noise ratio was improved after data preprocessing. The 190 samples were divided into a calibration set (corresponding Hb concentrations from 10.6 to 17.3 g·dL-1) of 143 samples and a validation set (corresponding Hb concentrations from 10.3 to 17.3 g·dL-1) of 47 samples. The model’s applicability was ensured when two sets have a similar distribution and range of Hb concentrations. And then, the Monte Carlo uninformative variable elimination (MC-UVE) was used to select the informative wavelength, which simplified the model structure and increased the proportion of useful wavelengths. When the Monte Carlo iteration number was 1000, 191 wavelength points were selected from the 700 wavelengths of the whole blood absorbance spectrum to build the whole blood Hb concentration partial least squares (PLS) model. Finally, a comparison was performed among the model based on the original whole blood transmission spectrum, the model based on the whole blood absorbance spectrum, the SG-MSC-PLS model, the SG-MSC-MC-UVE-PLS model and an existing model. In addition to this, the number of selected wavelengths based on MC-UVE was much smaller than the total number, but the predictive effect was much better, which was beneficial to improve the calculation efficiency of the model. The results indicate that the SG-MSC-MC-UVE-PLS method effectively increases the signal-to-noise ratio of the whole blood absorption spectrum signal and simplifies the model. Besides, our procedure’s prediction accuracy and calculation efficiency of the model was improved by our procedure, which has reference significance for the development of hemoglobin concentration detection technology.
孙代青，谢丽蓉，周 延，郭煜涛，车少敏. 基于近红外光谱的SG-MSC-MC-UVE-PLS算法在全血血红蛋白浓度检测中的应用[J]. 光谱学与光谱分析, 2021, 41(09): 2754-2758.
SUN Dai-qing, XIE Li-rong, ZHOU Yan, GUO Yu-tao, CHE Shao-min. Application of SG-MSC-MC-UVE-PLS Algorithm in Whole Blood Hemoglobin Concentration Detection Based on Near Infrared Spectroscopy. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(09): 2754-2758.
[1] Zhang S Z, Li G, Wang J X, et al. Scientific Reports, 2018, 8: 1.
[2] Wang Y Y, Li G, Wang H Q, et al. Applied Spectroscopy Reviews, 2019, 54(9): 736.
[3] YE Cui-qing, LIANG Qi-long, HUANG Jie-wen, et al（叶翠清, 梁其隆, 黄洁雯, 等）. Shenzhen Journal of Integrated Traditional Chinese and Western Medicine（深圳中西医结合杂志）, 2019, 29(10): 74.
[4] Li G, Xu S J, Zhou M, et al. Spectroscopy Letters, 2017, 50(3): 164.
[5] Liu H Y, Peng F L, Hu M L, et al. Journal of Electrical and Computer Engineering, 2020: ID3034260.
[6] Yuan J Z, Lu Q P, Wang J L, et al. Chinese Journal of Analytical Chemistry, 2017, 45(9): 1291.
[7] Lee J, Song J, Choi J-H, et al. Scientific Reports, 2020, 1: 10.
[8] ZHANG Li-juan, XIA Qi-le, CHEN Jian-bing, et al（张丽娟, 夏其乐, 陈剑兵, 等）. Spectroscopy and Spectral Analysis（光谱学与光谱分析）, 2020, 40(7): 2246.
[9] Abd Rahima I M, Rahim H A, Ghazali R, et al. Jurnal Teknologi, 2016, 78(7-4): 85.
[10] Zifarelli A, Giglio M, Menduni G, et al. Analytical Chemistry, 2020, 11035: 11043.
[11] Beumers P, Engel D, Brands T, et al. Chemometrics and Intelligent Laboratory Systems, 2018, 172: 1.
[12] Zhou Y, Zheng C L, Cao H, et al. Biochemical and Biophysical Research Communications, 2012, 420(1): 205.
[13] LI Shang-ke, DU Guo-rong, LI Pao, et al(李尚科, 杜国荣, 李 跑, 等). Food Research and Development(食品研究与开发), 2020，41(17): 144.
[14] QIU Yan, ZHANG Xue-qin, GUO Yu-jun, et al(邱 彦, 张血琴, 郭裕钧, 等). High Voltage Engineering(高电压技术), 2019, 45(11): 3587.
[15] Kuenstner J, Norris K. Journal of Near Infrared Spectroscopy, 1995, 3(1): 11.
