@inproceedings {2209,
	title = {Evaluation of a Morphable Anthropomorphic Articulated Total Body Model},
	booktitle = {Design Tools and Methods in Industrial Engineering II - Proceedings of the 2nd International Conference on Design Tools and Methods in Industrial Engineering, ADM 2021},
	year = {2022},
	pages = {761{\textendash}772},
	publisher = {Springer},
	organization = {Springer},
	abstract = {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.},
	keywords = {3D parametric human model, Articulated total body, Forensic biomechanics, Multibody analysis, principal component analysis (PCA)},
	isbn = {978-3-030-91233-8},
	doi = {10.1007/978-3-030-91234-5_77},
	author = {Giulia Pascoletti and Toon Huysmans and Paolo Conti and Zanetti, Elisabetta M.},
	editor = {Caterina Rizzi and Francesca Campana and Michele Bici and Francesco Gherardini and Tommaso Ingrassia and Paolo Cicconi}
}
