Estimation of the Non-Linear Material Properties for a Finite Elements Model of the Human Body Parts Involved in Sitting

Abstract

An optimization procedure was developed to search for the ergonomically optimum shape of consumer products. The entity to be optimized is a Finite Elements Model of the human body. The modification variable is the pressure values in the contact area. The Finite Elements Model and the optimization procedures were developed for a sitting support without backrest or arm rests. The model consists of a simplified assembly of the upper leg and the buttock area. Three components are included: skin, bony parts and in between a matrix of soft tissue. This paper presents the construction of the Finite Elements Model, in particular the assessment of the material properties according to the James-Green-Simpson elasticity model, and the first results of the Finite Elements Analysis. The first experiments are to validate the model for material properties. To that end the coefficients of the elasticity model are needed that cause good agreement of the maximum pressure values in the contact area with the predicted values obtained by earlier published regression. A hypothetical dependency of the maximum interface pressure on the stiffness is introduced. The results confirmed a part of the hypothesis. The current model needs further elaboration to test the hypothesis completely and to obtain a valid assessment of the material properties.

Multi-dimensional digital human models for ergonomic analysis based on natural data representations

“…The predicted shapes were used to create solid finite element models (FEMs). The solid FEMS were used to validate the constitutive equations by comparing computed pressure distribution knowledge (Moes and Horváth, 2002b) with measured pressure distribution knowledge (Moes, 2006) for individual humans, or groups of individuals, when sitting in chairs. Therefore, the multi-dimensional digital human model was used to analyse the relationships between the stresses and strains inside the bodies of individual humans, or groups of individual humans, and the shapes of chairs, based on actual measured knowledge, and the results were used to create virtual models of the optimised chairs (Moes, 2004).…”