An Re-Examination of PPG Curve and its 5 Component Curves Using Signal Processing Techniques and Viscoplastic Energy Model of Gh-Method: Math-Physical Medicine (No. 1016, Viscoelastic Medicine Theory #414)

Abstract

Gerald C. Hsu

The author's first article, number 013 published on 3/17/2019, applied signal processing techniques to predict his postprandial plasma glucose (PPG) levels using data collected over four years (from 5/1/18 to 3/19/19). Subsequently, in his article number 1016, the author re-examined his PPG curve using five component waveforms of the composite PPG waveform. These five components are derived from the insulin resistance state indicated by 70% of his fasting glucose levels in the early morning (Base), sugar and carbohydrate intake (food), post-meal walking exercise (Steps), ambient temperature (Temp), and a combined curve from about 20 other minor influential factors (Others). The generation of these five component waveforms utilized signal processing techniques detailed in the Introduction section of this article. This study used a total of nine years of collected data, with approximately five additional years of data collected from the author's own body (between 3/20/19 and 12/31/23).

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