In this work a new approach for the creation of Articulated Total Body (ATB) models for person-specific multi-body simulations is presented, with the main aim of overcoming limitations related to classical multi-ellipsoids ATB models, based on regression equations having only the weight and the height of the subject as input. The new methodology is based on a Statistical Shape Model (SSM), morphable according to up to 24 input parameters: the SSM was obtained from Principal Component Analysis (PCA), applied on a wide database of 3D human scans (CAESAR). The so obtained geometry can be segmented automatically to generate body segments with the respective inertial properties (mass, principal moments of inertia, and centres of mass location). The routine has been tested on a random set of 20 male subjects and the classical multi-ellipsoids models were compared to these in terms of inertial properties and 3D external geometry: the highest differences were registered at the abdomen and the thighs for what concerns the mass (60%), principal moments (75%) and centres of mass (50 mm) properties; the trunk, the shoulder and the calves are the most critical areas for the external geometry (average distance between the anthropomorphic and ellipsoids models equal to 50 mm). A contribution has been made to build person-specific multibody models. This is a valuable method since approximations made by multi-ellipsoidal models have resulted to be relevant at specific body areas, and personalised models can be a support to design and to forensic analyses.@en

Human computer models represent a useful tool for investigating the human body response to external static/dynamic loads or for human-centred design. Articulated Total Body (ATB) models are the simplest human multibody models, where body segments are represented by ellipsoids joined at skeletal articulations. Over the years, regression models on both living subjects’ and cadavers’ data have been developed to predict body segments properties. These models are affected by two main limitations: the only inputs are the subject’s weight and height, not considering that for the same combination different morphologies can exist; secondly, regression analyses were performed over a specific population not including peculiar morphologies (under-weight or obese). A novel methodology for developing anthropomorphic ATB models is here presented: a statistical shape model able to predict the external geometry of the human body from a limited set of anthropometric measurements was implemented and body segments were obtained by segmentation; the respective inertial properties were computed from volumes, assuming a constant density value. The properties of this new anthropomorphic ATB model were compared to those calculated by GEBOD (Generator of Body Data), a well-known programme for ATB data calculation. A virtual population of twenty subjects was analysed: with reference to the inertial properties the most relevant differences occurred at the abdomen and the thighs segments (60% relative error), while the trunk, the shoulder and the calves represent the most critical areas for the geometry reconstruction (50 mm average error). The significance of these outcomes was investigated performing multibody simulations with various scenarios.@en