【摘要】 近红外光谱属于分子振动光谱，溶液温度变化会造成O-H等分子振动及氢键等分子间作用力改变，进而引起吸收光谱的强度及谱峰变化，影响血糖等微弱成分检测精度。为解决温度扰动对于光谱检测及建模分析的影响，提出一种基于水光谱组学与双光谱二维相关光谱（2T2D-COS）的温度扰动判别方法。对仿体溶液在温度扰动及葡萄糖浓度扰动下的漫反射吸收光谱进行2T2D-COS分析，提取温度和糖浓度变化造成的光谱变化特征，得到不同扰动下的水光谱模式。实验结果表明，温度变化0.1℃与葡萄糖浓度变化45 mg/dL强度相当。进一步建立基于原始光谱、水光谱特征和2T2D-COS异步谱的温度扰动异常光谱判别模型，其中基于2T2D-COS异步谱特征的判别模型准确率达到95.83%，剔除异常样本后葡萄糖浓度预测均方根误差降低了51.89%，为提高近红外光谱在体血糖检测的精度提供了基础。更多还原

【Abstract】 Near-infrared spectroscopy is a type of molecular vibration spectroscopy. Temperature variations cause changes in molecular vibrations such as O-H and inter molecular forces such as hydrogen bonding, which lead to absorption spectral intensity and peaks changes, affecting the prediction accuracy of minor components such as blood glucose. To address the impact of temperature perturbation on spectral detection and modeling analysis, a method of temperature perturbation discrimination based on aquaphotomics and two-trace two-dimensional correlation spectroscopy(2 T2 DCOS) was proposed. The 2T2D-COS analysis was applied to diffuse reflectance spectra of simulated solutions under temperature perturbation and varying glucose concentrations. Spectral features induced by changes in temperature and glucose concentration were successfully extracted, revealing distinct water spectral patterns under different perturbations. Quantitative analysis shows that temperature changes of 0. 1 °C is equivalent to glucose concentration changes of 45 mg/dL in terms of intensity. A temperature perturbation outliers discrimination model was further established based on raw spectra, water spectral features, and 2T2D-COS asynchronous spectra. The accuracy rates of the model based on 2T2D-COS asynchronous spectra is 95. 83%. After removing outliers, the root mean square error of glucose concentration prediction is reduced by 51. 89%. This work provides a foundation for improving the accuracy of in vivo blood glucose detection using near-infrared spectroscopy.更多还原