Detailed GH.p-Modulus Values at 15-Minute Time Intervals for a Synthesized Sensor PPG Waveform of 159 Liquid Egg Meals, and 126 Solid Egg Meals Using Linear Elastic Glucose Theory of GH-Method: Math-Physical Medicine, Part 13 (No. 365)

Abstract

This article is Part 13 of the author’s linear elastic glucose behavior study. It focuses on a deeper investigation of GH.p-modulus at 15-minute time intervals for a synthesized PPG waveform based on the comparison of the results from his neuroscience study on two types of egg meals during the period from 5/5/2018 to 11/17/2020. Here is the step by step explanation for the predicted postprandial plasma glucose (PPG) equation using linear elastic glucose theory as described in References 9 through 20: (1) Baseline PPG equals to 97% of fasting plasma glucose (FPG) value, or 97% * (weight * GH.f-Modulus). (2) Baseline PPG plus increased amount of PPG due to food, i.e. plus (carbs/sugar intake amount * GH.p-Modulus). (3) Baseline PPG plus increased PPG due to food, and then subtracts reduction amount of PPG due to exercise, i.e. minus (post-meal walking k-steps * 5). (4) The Predicted PPG equals to Baseline PPG plus the food influences, and then subtracts the exercise influences. The linear elastic glucose equation is: Predicted PPG = (0.97 * GH.f-modulus * Weight) +(GH.p-modulus * Carbs&sugar) - (post-meal walking k-steps * 5) Where (1) Incremental PPG = Predicted PPG - Baseline PPG + Exercise impact (2) GH.f-modulus = FPG / Weight (3) GH.p-modulus = Incremental PPG / Carbs intake This study analyzes the glucose coefficient of GH.p-modulus at 15-minute intervals for two synthesized PPG waveforms associated with liquid eggs and solid eggs. The variation range of GH.p-modulus are between 15 and 22 with an average of 18.9 for solid eggs and between 10 and 14 with an average of 11.6 for liquid eggs. The average GH.p-modulus values of 18.9 for solid eggs and 11.6 for liquid eggs using every 15-minute intervals of the PPG values are comparable with the average GH.p-modulus values of 20.7 for solid eggs and 12.7 for liquid eggs using the average glucose values of 285 egg meals (Reference 19 of paper no. 363). However, a vast difference can be observed by comparing the 285 egg meals, where the GH.p-modulus are in double digits, against his 2,843 total meals (see Reference 19). His GH.p-modulus values of 2,483 total meals are 2.1 using finger PPG and 3.4 using sensor PPG, where the GH.p-modulus are in a single digit. The differences are caused by the neural communication model between the brain and internal organs. This neuroscience contribution factor has caused the higher solid egg meals PPG magnitudes in comparison with the lower liquid egg meals PPG values. Actually, the different peak PPG values of the two different physical states of egg meals, resulting from varying cooking methods, have the same carbs/sugar intake amount of ~2 grams and comparable exercise amount of ~4,500 steps. Although this paper does not focus on the neuroscience studies of egg meals, it is investigating the possible variance of GH.p-modulus. The study utilizes a step by step illustration of moving from (1) the difference between PPG and FPG, going through (2) Incremental PPG, then finally arriving at (3) Predicted PPG. By moving along with this calculation process, we can observe three waveform variances between liquid egg meals versus solid egg meals. As a result, the author has gained a great deal of inside knowledge and a clear picture of the characteristics and behaviors of the most difficult glucose coefficient, GH.p-modulus, as presented in his research work on linear elastic glucose behaviors for Part 13.