基于近红外三波长的无创血糖测量系统

Yaqin Chen, G. Bai, Jun Xiao, Long Wang, Qingming Luo
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引用次数: 2

摘要

近红外光谱范围为0.7 ~ 2.5μm,可用于有机官能团的定量测定,特别是C- h、O- h、N-H和C=O。近红外光谱分析样品浓度的重点是光学传感器的设计和光谱数据的处理。采用近红外光谱法的无创血糖测量方法通常是用一束光照射人体的血液区域,然后从光谱中提取血糖信息。关键是要提高信噪比,以便可以检测到非常低的葡萄糖吸收。本文根据葡萄糖的吸收特性,设计了一种基于近红外三波长的无创血糖测量系统。该系统包括光源、光斩波器、检测器和锁相放大器等几个重要部分。为了消除干扰效应,在泛音波段葡萄糖吸收峰的信号波长1610nm和参考波长1200/1350nm处分别选择三个波长。光探头采用环形光束,大大提高了入射光强度,提高了信噪比。在正常人体生理血糖范围(0-500mg/dL)内,对不同浓度间隔的葡萄糖水溶液进行了两组实验,以评价该系统的预测性能。在这些组实验中,采用偏最小二乘算法预测葡萄糖浓度。初步结果表明,当测定区间为100mg/dL时,相关系数(R)为0.998,预测均方根误差(RMSEP)为17.08mg/dL;当间隔为20mg/dL时,R值为0.959,RMSEP值为23.22mg/dL。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Noninvasive blood glucose measurement system based on three wavelengths in near-infrared region
Near-infrared region of optical spectrum extends from 0.7 to 2.5μm and can be used for quantitative measurement of organic functional groups, especially C-H, O-H, N-H and C=O. Analyzing sample concentration by near infrared spectroscopy focuses on the design of the optical sensor and the spectral data processing. Noninvasive blood glucose measurement methods using near-infrared spectroscopy usually apply a beam of light to irradiate the blood region of human, and then extract the information of blood glucose from the spectrum. The key is to improve the signal to noise ratio so that very low glucose absorption can be detected. In this paper, according to the absorption of glucose, a noninvasive blood glucose measurement system based on three wavelengths in the near-infrared region was designed. The system included several important parts such as the light source, the optical chopper, the detector and the lock-in amplifier. The three wavelengths were respectively chosen at the signal wavelength 1610nm by glucose absorption peak in the overtone band and the reference wavelengths 1200/1350nm to eliminate the interference effect. The optical probe used an annular light bundle to greatly increase the intensity of incidence light and improve the signal-noise ratio. Two group experiments of glucose aqueous solutions with different concentration interval in the normal human physiological blood glucose range (0-500mg/dL) have been done to evaluate the predictive performance of the system. In these group experiments, the partial least square algorithm was used to predict the glucose concentration. The preliminary results showed when the interval was 100mg/dL, the correlation coefficient (R) was 0.998 and the root mean square error of prediction (RMSEP) was 17.08mg/dL; and when the interval was 20mg/dL, the values of R and RMSEP were 0.959 and 23.22mg/dL, respectively.
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