There is an urgent need for a mass population screening tool for diabetes. Skin tissue contains a large number of endogenous fluorophores and physiological parameter markers related to diabetes. We built an excitation-emission spectrum measurement system with the excited light sources of 365, 395, 415, 430, and 455 nm to extract skin characteristics. The modeling experiment was carried out to design and verify the accuracy of the recovery of tissue intrinsic discrete three-dimensional fluorescence spectrum. Blood oxygen modeling experiment results indicated the accuracy of the physiological parameter extraction algorithm based on the diffuse reflectance spectrum. A community population cohort study was carried out. The tissue-reduced scattering coefficient and scattering power of the diabetes were significantly higher than normal control groups. The Gaussian multi-peak fitting was performed on each excitation-emission spectrum of the subject. A total of 63 fluorescence features containing information such as Gaussian spectral curve intensity, central wavelength position, and variance were obtained from each person. Logistic regression was used to construct the diabetes screening model. The results showed that the area under the receiver operating characteristic curve of the model for predicting diabetes was 0.816, indicating a high diagnostic value. As a rapid and non-invasive detection method, it is expected to have high clinical value.
Keywords: diabetes mellitus; diffuse reflectance; multi-peaks Gaussian fitting; spectrum recovery; tissue fluorescence spectrum.
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