Comput Methods Programs Biomed - Predicting body fat percentage based on gender, age and BMI by using artificial neural networks.

Tópicos

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Resumo

In the human body, the relation between fat and fat-free mass (muscles, bones etc.) is necessary for the diagnosis of obesity and prediction of its comorbidities. Numerous formulas, such as Deurenberg et al., Gallagher et al., Jackson and Pollock, Jackson et al. etc., are available to predict body fat percentage (BF%) from gender (GEN), age (AGE) and body mass index (BMI). These formulas are all fairly similar and widely applicable, since they provide an easy, low-cost and non-invasive prediction of BF%. This paper presents a program solution for predicting BF% based on artificial neural network (ANN). ANN training, validation and testing are done by randomly divided dataset that includes 2755 subjects: 1332 women (GEN = 0) and 1423 men (GEN = 1), with AGE from 18 to 88 y and BMI from 16.60 to 64.60 kg/m(2). BF% was estimated by using Tanita bioelectrical impedance measurements (Tanita Corporation, Tokyo, Japan). ANN inputs are: GEN, AGE and BMI, and output is BF%. The predictive accuracy of our solution is 80.43%. The main goal of this paper is to promote a new approach to predicting BF% that has same complexity and costs but higher predictive accuracy than above-mentioned formulas.

Resumo Limpo

human bodi relat fat fatfre mass muscl bone etc necessari diagnosi obes predict comorbid numer formula deurenberg et al gallagh et al jackson pollock jackson et al etc avail predict bodi fat percentag bf gender gen age age bodi mass index bmi formula fair similar wide applic sinc provid easi lowcost noninvas predict bf paper present program solut predict bf base artifici neural network ann ann train valid test done random divid dataset includ subject women gen men gen age y bmi kgm bf estim use tanita bioelectr imped measur tanita corpor tokyo japan ann input gen age bmi output bf predict accuraci solut main goal paper promot new approach predict bf complex cost higher predict accuraci abovement formula

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