Two-dimensional correlation (2D) method for improving the accuracy of OCT-based noninvasive blood glucose concentration (BGC) monitoring

AbstractThe optical scattering coefficient (μs) in the dermis layer of human skin obtained with optical coherence tomography (OCT) has shown to have a strong correlation with the blood glucose concentration (BGC), which can be used for noninvasive BGC monitoring. Unfortunately, the nonhomogeneity in the skin may cause inaccuracies for the BGC analysis. In this paper, we propose a 2D correlation analysis method to identify 2D regions in the skin withμs sensitive to BGC variations and only use data in these regions to calculateμs for minimizing the inaccuracy induced by nonhomogeneity and therefore improving the accuracy of OCT-based BGC monitoring. We demonstrate the effectiveness of the 2D method with OCT data obtained with in vivo human forearm skins of nine different human subjects. In particular, we present a 3D OCT data set in a two-dimensional (2D) map of depth vs. a lateral dimension and calculate the correlation coefficientR between theμs and the BGC in each region of the 2D map with the BGC data measured with a glucose meter using finger blood. We filter out theμs data from regions with lowR values and only keep theμs data withR values sufficiently high (R-filter). The filteredμs data in all the regions are then averaged to produce an averageμs data. We define a term called overall relevancy (OR) to quantify the degree of correlation between the filtered/averagedμs data and the finger-blood BGC data to determine the optimalR value for such an R-filter with th...
Source: Lasers in Medical Science - Category: Laser Surgery Source Type: research