Viscoelastic or Viscoplastic Glucose Theory (VGT 37): Applying the VEGT or VPGT to Study Body Weight Versus Sleep Score and Food Quantity to Predict Body Weight using Viscoelastic Perturbation Model over 13 Semi-Annual Periods from Y15H2 to Y21H2 based on the GH-Method: Math-Physical Medicine (No. 618)

Abstract

Gerald C Hsu

Since 2012, the author has collected his body weight and finger-piercing glucose values each day. Next, he accumulated medical conditions data including blood pressure, heart rate, and blood lipids along with lifestyle details of diet, exercise, sleep, stress, water intake and daily routine details. Based on the collected big data, he organized them into two main groups. The first group is the medical conditions (MC) with 4 categories: weight, glucose, BP, and lipids. The second guru is the lifestyle details (LD) with 6 categories: food, exercise, water intake, sleep, stress, and daily routines. He collects his daily data and then calculates a unique score for each of these 10 categories, including weight (m1), sleep score (m7), and food quantity score (m9a). In this article, the author applies the viscoelasticity and viscoplasticity theories to conduct his research to discover some hidden behavior or relationship between m1 (as an output or strain) versus either m7 or m9a (as inputs or stresses). The hidden behaviors and relationships between the output biomarker for body weight m1 and the two input biomarkers, sleep score m7 and food quantity score m9a, are time-dependent which change from time to time.

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