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Computational finite element (FE) human body models (HBM) are used to estimate internal loads and soft tissue deformation, which cannot be easily measured experimentally, for seating discomfort investigation. However, most existing models only represent a limited number of body sizes and postures and cannot be easily personalized and repositioned, which limits their applicability. In recent years, an open source software package has been developed within the European project PIPER (available at www.PIPER-project.org) to help personalize and to position an HBM used for crash injury simulation. In addition to the personalizing and positioning tools, a child model has also been developed and is also now available. The present study aims to derive an adult male HBM to study seating discomfort from the PIPER Child model using the PIPER personalizing tools and information with external body shape and partial internal skeleton of an adult as targets.

The Abdominal Pressure Twin Sensors (APTS) for Q3 and Q6 dummies are composed of soft polyurethane bladders filled with fluid and equipped with pressure sensors. Implanted within the abdominal insert of child dummies, they can be used to detect abdominal loading due to the belt during frontal collisions. In the present study - which is part of the EC funded CASPER project - two versions of APTS (V1 and V2) were evaluated in abdominal belt compression tests, torso flexion test (V1 only) and two series of sled tests with degraded restraint conditions. The results suggest that the two versions have similar responses, and that the pressure sensitivity to torso flexion is limited. The APTS ability to detect abdominal loading in sled tests was also confirmed, with peak pressures typically below 1 bar when the belt loaded only the pelvis and the thorax (appropriate restraint) and values above that level when the abdomen was loaded directly (inappropriate restraint).

Finite Element Human Body Models (HBM) have become powerful tools to study the response to impact. However, they are typically only developed for a limited number of sizes and ages. Various approaches driven by control points have been reported in the literature for the non-linear scaling of these HBM into models with different geometrical characteristics. The purpose of this study is to compare the performances of commonly used control points based interpolation methods in different usage scenarios. Performance metrics include the respect of target, the mesh quality and the runability. For this study, the Kriging and Moving Least square interpolation approaches were compared in three test cases. The first two cases correspond to changes of anthropometric dimensions of (1) a child model (from 6 to 1.5 years old) and (2) the GHBMC M50 model (Global Human Body Models Consortium, from 50th to 5th percentile female).