Blood glucose level has important significance for medical diagnosis. Blood glucose measurement in traditional methods requires collecting blood samples several times a day, which causes discomfort, environmental pollution and so on. As a "fingerprint" spectrum for molecular recognition, Raman spectroscopy has attracted attention in blood glucose measurement. However, blood glucose level is low and spectral signal of glucose is easy to be influenced by noise and other components. To improve accuracy of blood glucose concentration estimation by Raman spectroscopy, we carried out the Raman blood glucose measurement in vitro, the interferograms of blood samples in different glucose concentrations were measured by the self-developed Spatial Heterodyne Raman Spectrometer (SHRS), and converted the interferograms to one-dimensional spectroscopic data using Fourier transform. In order to get data with higher quality, we used wavelet decomposition to remove the noise and sparse representation to remove the signal baseline. Then, selected the spectroscopy at 500-2500 cm-1 as input, and the corresponding blood glucose concentration value as label, use particle swarm optimization-support vector regression (PSO-SVR) algorithm to construct the blood glucose concentration estimation model. The results show that the R2 of test set is 0.8041 and the RMSE is 1.8580. And the accuracy of blood glucose concentration estimation was evaluated by the Clark Error Grid. The model based on PSO-SVR can achieve accurate estimation of blood glucose concentration. This method has important research significance and application potential for blood glucose measurement.
Fluorescent bioimaging technology has been widely used in clinic because of its high sensitivity, quick feedback, and no radiation. Among them, NIR-II imaging has lower absorption, tissue scattering, self-fluorescence, and higher signal-to-noise ratio. As a precursor of nanoprobe, BaYF5 is an excellent material due to its low phonon energy, which makes it easy to achieve rare earth ion energy level transition and obtain strong upconversion luminescence. A near-infrared II (NIR-II) rare earth fluoride nanoparticle (NP) BaYF5 : Yb3 + , Er3 + @ BaYF5 has been constructed. The luminescence principle of the material was deeply analyzed, and the influence of different doping ion ratio on fluorescence intensity was explored. Finally, the optimal doping ratio for this matrix material was obtained. In addition, according to the surface properties of the materials, the water solubility and biocompatibility of the NPs were significantly improved by the modification. Our work also systematically tested and analyzed the cytotoxicity, hematotoxicity, and tissue toxicity of the NPs and finally realized the high-resolution fluorescence imaging in living mice. This NP can be used as an effective and safe NIR-II contrastive agent, which provides the possibility for the detection and monitoring of physiological activity under deep tissue in vivo.
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