Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Raman scattering-based biomedical detection has usually been proposed with near-infrared laser sources. However, a low-cost CMOS imager's quantum efficiency is optimum around green wavelength, and their sensitivity substantially decreases in near-infrared wavelengths. Additionally, since Raman scattering intensity is proportional to lambda(-4) , where lambda is the laser wavelength, the increase of wavelength directly results in less sensitive measurement. These facts contribute to limiting the transfer of detection methodologies based on Raman spectroscopy to portable and low-cost point-of-care medical devices. Therefore, here we propose 532 nm green laser-induced Raman spectroscopy for low human serum glucose level detection. However, in 532 nm Raman spectroscopy of carotenoid containing biological systems, such as human serum, resonance Raman occurs, and total carotenoids resonance bands dominate the spectra. To demonstrate serum glucose detection on concentration levels typical in severe hypoglycemic ranges, this study optimizes laser focal depth, laser excitation duration, and laser power to extend the sensitivity by exploiting the glucose Raman shift peak at 1125 +/- 7.5 cm(-1). By applying experimentally tuned parameters, our findings suggest sensitive detection of serum glucose in the range of 0-10 mmol/l with 1.2 mmol/l theoretical limit of detection (LOD) by using spontaneous (non-enhanced) Raman spectroscopy.
Roland Logé, Jamasp Jhabvala, Eric Boillat, Reza Esmaeilzadeh, Claire Navarre, Lucas Maximilian Schlenger, Milad Hamidi Nasab
Ileana-Cristina Benea-Chelmus, Alessandro Tomasino, Francesco Bertot, Zahra Basiri