KEYWORDS: Absorption, Tissues, Scattering, Signal attenuation, Temperature metrology, Skin, In vivo imaging, Monte Carlo methods, Optical fibers, Tissue optics
We present a scattering-independent measurement to monitor the pure near-infrared light absorption variation for scattering media, especially for in vivo tissue. We found a scattering variation independent source-detector separation (SVI-SDS), where the diffuse light intensity only varies with tissue absorption change but does not vary with scattering change. We applied the SVI-SDS setup to monitor the tissue spectra with a temperature modulation. We also proposed a method to simplify the measurement by using two fixed SDSs for all wavelengths. It makes the detection device easy to design and fit to the required SVI-SDSs. Monte Carlo simulation and experiments on intralipid solutions and in vitro pig skin samples are performed to test the method. The temperature absorption spectra were acquired, and the temperature insensitive wavelengths of the tissue are discussed. We believe this new method will guide many potential applications for the absorption-based tissue spectroscopy.
KEYWORDS: Glucose, Absorption, Skin, Signal attenuation, Blood, Scattering, Monte Carlo methods, Light scattering, Near infrared spectroscopy, Diffusion
In the non-invasive blood glucose sensing based on near-infrared spectroscopy, the skin scattering variation during the long-term blood glucose monitoring would be a big challenge to get an accurate measurement result. We present a scattering and absorption separating method for the near-infrared diffuse reflectance spectra of scattering media. And we use the extracted absorption part, which is the medium’s effective attenuation coefficient (EAC) spectrum, to improve the accuracy for long-term glucose monitoring. We optimized the light source-detector separation (SDS) setup to realize the maximum sensitivity for the EAC spectra-based measurement. The measurement uses two SDSs to perform a differential on their diffuse reflectance spectra, as the differential could help to reduce the light drift during the long-term in vivo tissue monitoring. The SDS setup optimization for the two positions was tested by the Monte-Carlo (MC) simulation of tissue. The human oral glucose tolerance test (OGTT) with the optimized SDSs also shows a satisfactory blood glucose prediction result. In conclusion, this method shows a good application potential in the non-invasive blood glucose sensing.
In the non-invasive blood glucose measurement based on near-infrared spectroscopy, the glucose signal is very weak and easy to be disturbed. Tissue temperature fluctuation is a primary disturbance source, since it would greatly affect the accuracy of blood glucose concentration results. We present a method called differential diffuse reflection spectroscopy, which makes a differential processing on the data from multiple source-detector distances (SDDs), and it can directly estimate the change in effective attenuation coefficient (EAC) of tissue. Using EAC spectra, we investigated the influence of temperature on the tissue spectra and then used a multivariable analysis of external parameters orthogonalization (EPO) to calibrate the spectra. The spectra of 1000-1800 nm caused by temperature and glucose are compared. Theoretical computing, Monte Carlo simulations and experiments were used to test this method. In conclusion, this proposed method using EAC spectrum to monitor the tissue change shows a promising application potential in non-invasive blood glucose measurement.
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