Abstract

Recently, the author applied theories of elasticity, plasticity, 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 certain output biomarkers, such as glucose (symptoms or behaviors) resulting from a selected input biomarker, such as the carbs/sugar amount, exercise level, or others (causes or stressors). In this article, he chose his synthesized postprandial plasma glucose (PPG) data and waveform over the past 3.8 years as the strain (ε or output, symptom). Since 5/8/2018, he has been utilizing a continuously monitoring glucose sensor (CGM) device to collect 96 glucose data each day and 13 glucose data each meal at 15-minute time intervals. In order to investigate and learn the behaviors of the strain (ε) or PPG, and its stress (σ) or input/ cause as defined to be the estimated average glucose (eAG) change rate multiplied by a selected viscosity factor (η), which is the carbs/sugar intake amount. In this study, he selected “elastic” PPG case with average “Fingerpiercing PPG <120 mg/dL along with four “plastic” PPG cases, >120 mg/dL, >140 mg/dL, >180 mg/dL, and >200 mg/dL. The procedure of the analysis contains four steps. Step 1, he draws the 5 PPG (1 elastic and 4 plastic) waveforms in a time-domain (TD) with 15-minutes time interval within a 3-hour time span. Step 2, he calculates the stress values to draw the corresponding stress-strain diagram in a spatial-domain (SD). Step 3, he calculates 4 predicted plastic PPG values using the viscoelastic perturbation model. Step 4, he calculates the corresponding cardiovascular disease (CVD) risk probabilities induced by the 5 cases. There are three main purposes of this research article. First, to verify plastic postprandial plasma glucose (PPG) characteristics via stress-strain diagrams and their comparison against pseudo-linear elastic characteristics. Second, to examine the suitability of visco-perturbation model generated predicted PPG values via both prediction accuracy and correlation coefficient between the predicted PPG and measured PPG. Third, to verify the connectivity between the plastic hyperglycemic situations and heart disease such as CVD risk probabilities. The following two defined equations from the viscoelasticity glucose theory (VGT) are utilized to study the stressstrain relationship for this case study. At first, he selects his PPG as the strain, which is his target research item: strain = ε = individual output biomarker value (PPG) at present time

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