Multimode high-resolution DPWM for RF class-D amplifiers

Lichong, Sun; Zhu, Zhiwei; Yan, Na; Min, Hao

doi:10.1088/1674-4926/32/4/045001

Cited by 1 publication

(1 citation statement)

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“…To obtain the tissue's intrinsic fluorescence spectrum for characteristic analysis, some researchers employed the use of diffuse reflectance spectrum to correct for the effects of absorption and scattering [20,21]. Building upon the dual-band tissue fluorescence spectrum recovery method, this study introduces an excitation-emission spectrum recovery method, as shown in Equation (1).…”

Section: The Dual-band Wavelength Excitation-emission Spectrum Recove...mentioning

confidence: 99%

Noninvasive detection of diabetes mellitus based on skin fluorescence and diffuse reflectance spectroscopy

Zhang,

Liu,

Zhu

et al. 2023

Journal of Biophotonics

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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.

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Section: The Dual-band Wavelength Excitation-emission Spectrum Recove...mentioning

confidence: 99%