Agnizing Sarcopenia and Coherent Variable Optimization of Body Fat Percentage using Genetic Algorithms and Regression

Abstract

Obesity is a malady which poses wide threats across the world with its augmented inflation. A domineering determinant to most pandemic diseases in the human body is the agglomeration of body fat. Therefore, an apposite anatomization of body fat estimation for every individual is incumbent. The previous work aberrates and pioneered the implementation of attributes from the lipid profile and Bio-Electric Impedance Analysis (BIA) method of a person, from the conventional use of attributes such as BMI, age and gender to obtain the value of body fat percentage. But the proposed analysis meliorates the accuracy of body fat percentage and resuscitated the gamut of health gremlins it vanguards to. This paper also delineates the variable optimization using regression and genetic algorithm for the attributes incorporated to procure the body fat percentage. Thereby corroborating and revamping the veracity of the novel body fat percentage derived using lipids and the BIA method. The study has further helped in diagnosing a disease known as sarcopenia. The samples from the blood tests and Bio-Electric Impedance method have been procured from the Institute of Bio-Chemistry, after obtaining the consent from the Institutional Ethics Committee, Madras Medical College, Chennai. The simulations are carried out in MATLAB GUI and the results have been successfully obtained.