A Simple and Straightforward Linear Approximation Model of Predicting the Glucose and HbA1C Values to Manage Type 2 Diabetes Based on GH-Method: Math-Physical Medicine (No. 472)

Abstract

Gerald C Hsu

Based on research work over 6.5 years, the author summarized his work results into a set of simple and straightforward linear model to predict approximate, but accurate enough, sensor glucose and HbA1C values. It utilizes both of the linear elastic glucose theory (LEGT) from strength of engineering materials and the first-order interpolation perturbation theory (perturbation) from quantum mechanics to construct various PPG waveforms. To start, he measures his weight in early morning, next he estimates his fasting plasma glucose (FPG) at his wakeup moment, then approximates his breakfast post-prandial plasma glucose (PPG) at 0-minute time instant, and finally applies either LEGT model or perturbation model to construct his daily PPG waveform over a three-hours timeframe. Based on the estimated FPG value and three PPG values, he can then assess his daily average sensor glucose (eAG) and HbA1C (A1C) value on that particular day.

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