Viscoelastic and Viscoplastic Glucose Theory (VGT #25): Applying the Concepts of Viscoelasticity, Viscoplasticity and Perturbation Theories to Predict PPG Dataset and Waveforms for the Pre-Virus and Virus Periods Using the Total PPG Values as a Baseline Along with the Estimated PPG Relative Energy Levels in Both Time-Domain and Frequency-Domain Based on the GH-Method: MathPhysical Medicine (No. 605)

Abstract

Recently, the author applied theories of viscoelasticity and viscoplasticity from engineering and perturbation theory from quantum mechanics along with the wave theory and energy theory from physics to conduct his biomedical research on the output biomarkers of postprandial plasma glucose (PPG), a symptom of diabetes, resulting from the input biomarker of carbs/sugar amount (a cause of high glucose). In this article, he calculated two additional PPG datasets and curves, which are the predicted PPG for the pre-virus period from 5/1/2018 to 1/18/2020 and the virus period from 1/19/2020 to 2/12/2022. He used the total period from 5/1/2018 to 2/12/2022 PPG values as the dataset baseline. All PPG data from the three periods are collected via a continuous glucose monitoring (CGM) sensor device at 15-minute time-interval over a period of 1,379 days. For this article, there are two primary objectives to check the different PPG behaviors between two time periods with different lifestyles due to the COVID-19 virus quarantine. First, he applies the visco-perturbation model to predict these two different PPG behaviors and verify their associated correlation coefficients along with the prediction accuracy percentages. Second, he estimates and compares the three relative energies associated with PPG in both time-domain (TD) and frequency-domain (FD) for these three periods, including the total period of both pre-virus and virus periods.