Abstract

Recently, the author applied theories of viscoelasticity and viscoplasticity from engineering and physics along with wave theory and energy theory from physics to conduct his biomedical research on output biomarkers of postprandial plasma glucose (PPG), which is one of the key indicators for diabetes, resulting from the input biomarker of carbs/sugar intake amounts, which is a major cause for hyperglycemia. In this article, he extracted three sub-groups of PPG waveforms and datasets during a long period of ~4 years from 5/8/2018 to 3/16/2022. All of the PPG data are collected via a continuous glucose monitoring (CGM) sensor device at 15-minute time intervals (96 data each day) over 1,408 days and 4,310 meals that contain 56,030 PPG data. These three PPG sub-groups are listed below: Low PPG - 2,885 meals with 6.6 carbs/sugar grams and 122 mg/dL average PPG; Medium PPG - 1,298 meals with 23.9 carbs/sugar grams and 132 mg/dL average PPG; High PPG - 127 meals with 73.7 carbs/sugar grams and 153 mg/dL average PPG. There are three specific calculation steps for the numerical operation.

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