High accuracy of predicted postprandial plasma glucose using two coefficients of GH.f-modulus and GH.p-modulus from linear elastic glucose behavior theory based on GH-Method: math-physical medicine, Part 5 (No. 357)

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This article is Part 5 of the author’s linear elastic glucose behavior study, which focuses on the predicted postprandial plasma glucose (PPG). This study is the combination and continuation of his previous four studies, Parts 1, 2, 3, and 4, on linear elastic glucose behaviors Listed below are his two recently developed linear elastic glucose equations with two defined coefficients of GH-modulus and his third equation for the predicted PPG from combining these two equations together: (1) FPG = GH.f-modulus * Weight Where Weight is the input component (similar to stress) and FPG is the output component (similar to strain). (2) Incremental PPG= GH.p-modulus * Carbs&sugar Where Incremental PPG= Predicted PPG - (0.97 * FPG)+ (post-meal walking k-steps * 5) When he combines the above two linear elastic equations into one, he has the following new PPG prediction equation: (3) Predicted PPG= (0.97 * GH.f-modulus * Weight) +(GH.p-modulus * Carbs&sugar) - (post-meal walking k-steps * 5) The three equations from above were inspired by his prior knowledge in the theory of elasticity in strengths of engineering materials which has the following engineering equation developed in 1807 by a British scientist, Thomas Young: Stress = Young’s modulus * Strain Young’s modulus and the two biomedical coefficients (GH.f-modulus and GH.p-modulus) are reciprocal to each other. The main objective of this study is to offer numerical proof for the PPG prediction accuracy using the above-mentioned equation (3) and based on his own health data collected from 7/1/2015 to 10/31/2020. Listed below are the annual values of the GH.f-modulus, GH.p-modulus, PPG prediction % for the author’s case which reflect his severity levels of both obesity and diabetes, and PPG prediction accuracy %: Y2015: (0.71, 1.6,97%) Y2016: (0.68, 1.8,99%) Y2017: (0.69, 1.6, 100%)Y2018: (0.66, 1.9, 100%) Y2019: (0.66, 1.8,99%) Y2020: (0.59, 2.4, 103%) Average: (0.67, 1.9, 100%)