6 March 2023Non-invasive quantification of changes in blood oxygen saturation of the internal jugular vein: theoretical evaluation and in-vivo demonstration
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A prediction model based on artificial neural networks was built to quantify changes in blood oxygen saturation of the internal jugular vein (dSijvO2) from diffuse reflectance measured at five wavelengths. The model was trained by Monte Carlo simulations with various tissue optical coefficients and subject-specific tissue structure determined by ultrasound imaging. Errors in dSijvO2 estimated from simulated data are below 2.2% and independent of the initial oxygen saturation. The model was further validated by excellent agreements between modeled and measured in-vivo reflectance spectra from a healthy volunteer undergoing hyperventilation, and the quantified trend of dSijvO2 followed expectations during and after hyperventilation. The proposed method is promising to provide non-invasive quantification of dSijvO2.
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