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Spectral analysis of multiple scattering factors of turbid media for glucose measurement using near-infrared spectroscopy

SIGNIFICANCE: Near-infrared (NIR) diffuse reflectance spectroscopy has been widely used for non-invasive glucose measurement in humans, as glucose can induce a significant and detectable optical signal change in tissue. However, the scattering-dominated glucose spectrum in the range of 1000 to 1700 ...

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Detalles Bibliográficos
Autores principales: Yue, Lu, Tongshuai, Han, Wenbo, Liu, Qing, Ge, Jin, Liu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10272419/
https://www.ncbi.nlm.nih.gov/pubmed/37334208
http://dx.doi.org/10.1117/1.JBO.28.6.065005
Descripción
Sumario:SIGNIFICANCE: Near-infrared (NIR) diffuse reflectance spectroscopy has been widely used for non-invasive glucose measurement in humans, as glucose can induce a significant and detectable optical signal change in tissue. However, the scattering-dominated glucose spectrum in the range of 1000 to 1700 nm is easily confused with many other scattering factors, such as particle density, particle size, and tissue refractive index. AIM: Our aim is to identify the subtle distinctions between glucose and these factors through theoretical analysis and experimental verification, in order to employ suitable methods for eliminating these interferences, thus increasing the accuracy of non-invasive glucose measurement. APPROACH: We present a theoretical analysis of the spectra of 1000 to 1700 nm for glucose and some scattering factors, which is then verified by an experiment on a 3% Intralipid solution. RESULTS: We found that both the theoretical and experimental results show that the effective attenuation coefficient of glucose has distinct spectral characteristics, which are distinct from the spectra caused by particle density and refractive index, particularly in the range of 1400 to 1700 nm. CONCLUSIONS: Our findings can offer a theoretical foundation for eliminating these interferences in non-invasive glucose measurement, aiding mathematical methods to model appropriately and enhance the accuracy of glucose prediction.