Abstract

The author developed his GH-Method: math-physical medicine (MPM) by applying mathematics, physics, engineering modeling, and computer science (big data analytics and AI). He believes in “prediction” and has developed five models, including metabolism index, weight, fasting plasma glucose (FPG), postprandial plasma glucose (PPG), and hemoglobin A1C. All prediction models have reached to 95% to 99% accuracy. His focus is on preventive medicine, especially on diabetes control via lifestyle management. In this paper, he interprets the brain stimulator and its associated simulation model of predicted breakfast PPG via a food nutrition segmentation analysis and Sensor PPG waveform characteristics study by utilizing the PPG data of meals from McDonald’s breakfasts and 240 eggs, including McDonald’s breakfasts, to conduct his research.