Viscoelastic and Viscoplastic Glucose Theory (VGT #17): Selecting 12 Cases and Applying Theories of Viscoelasticity and Viscoplasticity from Engineering and Perturbation Theory from Quantum Mechanics to Predict the Behavior of an Output Biomarker as the Strain (ε or Behavior, Symptom) by Using the Strain Rate (dε/dt) Multiplying with a Correlated Input Biomarker of Stress Value (σ or Stressor, Cause) as

Abstract

The author has collected ~3 million data regarding his health condition and lifestyle details over the past 12 years. He spent the entire year of 2014 to develop a metabolism index (MI) model using topology concept, nonlinear algebra, algebraic geometry, and finite element method. This MI model contains various measured biomarkers and recorded lifestyle details along with their induced new biomedical variables for an additional ~1.5 million data. Body weight, glucose, blood pressure, heart rate, lipids, body temperature, and blood oxygen level, along with important lifestyle details, including diet, exercise, sleep, stress, water intake, and daily life routines are included in his MI database. His developed MI model has a total of 10 categories covering approximately 500 detailed elements that constitute his defined “metabolism model” which are the building blocks or root causes for diabetes and other chronic disease complications, including but not limited to cardiovascular disease (CVD), chronic heart disease (CHD), chronic kidney disease (CKD), retinopathy, neuropathy, foot ulcer, and hypothyroidism. The end result of the MI development work is a combined MI value within any selected time period with 73.5% as its dividing line between a healthy and unhealthy state. The MI serves as the foundation to many of his follow-up medical research work. During the period from 2015 to 2017, he focused his research on type 2 diabetes (T2D), especially glucoses, including fasting plasma glucose (FPG), postprandial plasma glucose (PPG), estimated average glucose (eAG), and hemoglobin A1C (HbA1C). During the following period from 2018 to 2022, he concentrated on researching medical complications resulting from diabetes, chronic diseases, and metabolic disorders which include heart problems, stroke, kidney problems, retinopathy, neuropathy, foot ulcer, diabetic skin fungal infection, hypothyroidism, and diabetic constipation, cancer, and dementia. He also developed a few mathematical risk models to calculate the probability percentages of developing various diabetic complications. Recently, he has applied theories of elasticity, plasticity, viscoelasticity, and viscoplasticity from engineering along with the theories of wave and energy from physics to conduct his research on output biomarkers (symptoms or behaviors) resulting from a suspected or identified input biomarkers (causes or stressors). As a result, he has written 16 different articles in this research area. In this article, he utilizes the perturbation theory of quantum mechanics in modern physics to develop a set of predicted output biomarkers using the identified input biomarkers from his previous research work. Next, he compares his predicted biomarkers against his measured biomarkers using their calculated correlation coefficients and prediction accuracies.