World Health Organization(WHO) estimates that there will be 300 million diabetic patients worldwide in 2025. The real-time monitoring and detection of blood glucose levels is considered a way to prevent the occurrence of complications.The scattering coefficient(μs), which can be used for noninvasive BGC monitoring, in the dermis layer of human skin can be obtained by optical coherence tomography(OCT), and it has a strong correlation with the blood glucose concentration (BGC). Unfortunately, the non-homogeneity in the skin may cause inaccuracies for the BGC analysis, and the different physical conditions on different people may also cause errors. In this paper, The 3D correlation analysis method is applied to identify the regions in the skin where the μs is sensitive to BGC variations. To reduce the error of the non-homogeneity regions and improve the accuracy of OCT-based BGC monitoring, the proposed method only uses the μs in the high correlation regions for building the blood glucose prediction model. Experiment shows that the proposed method is better than that obtained with the previously reported 2D correlation method. We believe that the method demonstrated in this paper is important for understanding the influence of BGC on μs in human skins and therefore for improving the accuracy of OCTbased noninvasive BGC monitoring, although further studies are required to validate its effectiveness.
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