Self-Directed Weight Management by Feedback from a Self-Adaptive Metabolic Health Monitoring System

摘要

The primary objective is to manage weight and body composition through a mobile phone app utilizing a personalized self-adapting metabolic health monitoring system and a web based interactive technology with practitioner coaching for lifestyle changes. A mathematical model of the energy metabolism has been developed based on the principle of the conservation of energy to estimate the daily utilized macronutrient calorie intake, macronutrient oxidation rate, and body composition change through biweekly serial measurements of body composition, resting metabolic rate, daily measurement of physical energy expenditure and biweekly input of macronutrient intake. The model is self adaptive and uses the Kalman filer. The model provides a daily dynamic indirect individualized measurement method for the otherwise difficult to measure metabolic variables. The results of a simulation study using the data of the Minnesota starvation and overfeeding experiment demonstrated that the model and app display to the user the daily carbohydrate and fat balance accurately with resolution to the gram range. The model app also shows the individual's fuel selection in terms of carbohydrate versus fat burning rate while precisely following the principles of indirect calorimetry. This close feedback of information realizes an adaptive control system. The indirect measurement of components of the metabolism assists a self-directed weight management process and helps in setting realistic goals and reaching those goals by correctly chosen behavior changes.