Numerical modeling of bra wear during running

International audienceNumerical modelling of bras and their influence on breasts during sport could be a valuable tool for bra designers as it could avoid the development of prototypes and help improving the performances of bras. Such a model requires a model for the breasts and for the bra. Models of breasts are available in the literature but they are based on MRI data that are expensive and heavy to segment and mesh. One of the main issues to develop a breast numerical model is to define a reference state for the breast without gravity, to avoid errors in the evaluation of stresses during sport. Rajagopal et al. used water to cancel the effect of gravity on a part of the breast and define the reference state; this idea is followed in the present work. The present work is focused on modelling female breasts, simulating brawear and investigating the influence of the bra on stresses and strains in the breast. A particular objective of this work is to provide a model that can run fast enough on a regular computer, so that it is convenient to use for industrial and commercial purposes

Numerical simulation of breast deformation under static conditions

International audienc

Numerical simulation of breast deformation under static conditions

International audienc

Improvement of energy expenditure prediction from heart rate during running

We aimed to develop new equations that predict exercise-induced energy expenditure (EE) more accurately than previous ones during running by including new parameters as fitness level, body composition and/or running intensity in addition to heart rate (HR). Original equations predicting EE were created from data obtained during three running intensities (25%, 50% and 70% of HR reserve) performed by 50 subjects. Five equations were conserved according to their accuracy assessed from error rates, interchangeability and correlations analyses: one containing only basic parameters, two containing VO2max or speed at VO2max and two including running speed with or without HR. Equations accuracy was further tested in an independent sample during a 40 min validation test at 50% of HR reserve. It appeared that: (1) the new basic equation was more accurate than pre-existing equations (R2 0.809 versus. 0,737 respectively); (2) the prediction of EE was more accurate with the addition of VO2max (R2 = 0.879); and (3) the equations containing running speed were the most accurate and were considered to have good agreement with indirect calorimetry. In conclusion, EE estimation during running might be significantly improved by including running speed in the predictive models, a parameter readily available with treadmill or GPS