Neural networks based approach to estimate body fat (%BF)

Abstract: The amount of fat in human body composition relative to total body weight (%BF) is considered a determinant factor to a healthier and longer life. In this paper a neural network approach, that overcomes some of the current limitations of assessing %BF through skinfold thickness measurement...

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Bibliographic Details
Main Author: Manuel R. Barbosa (author)
Other Authors: Teresa Amaral (author), Maria de Fátima Chousal (author), Maria Teresa Restivo (author)
Format: book
Language:eng
Published: 2010
Subjects:
Online Access:https://hdl.handle.net/10216/79708
Country:Portugal
Oai:oai:repositorio-aberto.up.pt:10216/79708
Description
Summary:Abstract: The amount of fat in human body composition relative to total body weight (%BF) is considered a determinant factor to a healthier and longer life. In this paper a neural network approach, that overcomes some of the current limitations of assessing %BF through skinfold thickness measurement with calliper devices, is presented. Neural networks recognised capabilities in modelling nonlinear problems can provide a valuable tool to deal with the inherent nonlinear behaviour of body tissues. The approach was tested on a sample of elder individuals, men and women, showing better performance when compared with two available alternative methodologies.