Self-Experiencing “The Healthiest Weight”

Abstract

The Ideal Weight has been an interesting topic for years. The Healthiest Weight should be accurate and unique for everyone. Current methods use the BMI (Body Mass Index) as an indicator of a person's optimal weight. However, BMI has some issues, leading to inefficient weight management programs. Successful programs should consider the optimal timing for the brain control of weight-presetting, the fundamental of the Lipostat theory, not yet reported in humans. In this study, the bases for successful Weight Management Programs are proposed by BMI sub-categorization, current state-of-the-art mobile technology and self-experimentation. This is the first reported longterm human self-experiment involving successful weight loss, metabolic adaptation and weight-presetting, consistent with the Lipostat theory. New concepts and ideas are raised, setting up the bases for further experimental investigations.

Reinventing the Body Mass Index: A Machine Learning Approach

“…For example, in epidemiological studies, the BMI based on self-reported height and weight (self-reported BMI) is subjected to measurement error [17]. Other studies have suggested adjusting the Normal BMI values to avoid false positive/ negative assignments [18]. It is expected that medical professionals would take the BMI result and consider patients as unique individuals.…”