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Development of body shape data based digital human models for ergonomics simulations
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (User Centred Product Design)ORCID iD: 0000-0002-0125-0832
Fraunhofer-Chalmers Centre, Geometry and Motion Planning, Gothenburg, Sweden.
Fraunhofer-Chalmers Centre, Geometry and Motion Planning, Gothenburg, Sweden.
Fraunhofer-Chalmers Centre, Geometry and Motion Planning, Gothenburg, Sweden.
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2022 (English)In: Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022), August 29–30, 2022, Iowa City, Iowa, USA, University of Iowa Press, 2022, Vol. 7, p. 1-9, article id 13Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents the development of body-shape-data-based digital human models, i.e. manikins, for ergonomics simulations. In digital human modeling (DHM) tools, it is important that the generated manikin models are accurate and representative for different body sizes and shapes as well as being able to scale and move during motion simulations. The developed DHM models described in this paper are based on body scan data from the CAESAR anthropometric survey. The described development process consists of six steps and includes alignment of body scans, fitting of template mesh through homologous body modeling, statistical prediction of body shape, joint centre prediction, adjustment of posture to T-pose, and, finally, generation of a relation between predicted mesh and manikin mesh. The implemented method can be used to create any type of manikin size that can be directly used in a simulation. To evaluate the results, a comparison was done of original body scans and statistically predicted meshes generated in an intermediary step, as well as the resulting DHM manikins. The accuracy of the statistically predicted meshes are relatively good, even though differences can be seen, mostly related to postural differences and differences around smaller areas with distinct shapes. The biggest differences between the final manikin models and the original scans can be found in the shoulder and abdominal areas, in addition to the significantly different initial posture that the manikin models have. To further improve and evaluate the generated manikin models, additional body scan data sets that include more diverse postures would be useful. DHM tool functionality could also be improved to enable evaluation of the accuracy of the generated manikin models, possibly resulting in DHM tools that are more compliant with standard documents. At the same time, standard documents might need to be updated in some aspects to include more three-dimensional accuracy analysis.

Place, publisher, year, edition, pages
University of Iowa Press, 2022. Vol. 7, p. 1-9, article id 13
Keywords [en]
Anthropometry, 3D body scanning, body shape, statistical body model, joint centre
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; VF-KDO
Identifiers
URN: urn:nbn:se:his:diva-21829DOI: 10.17077/dhm.31759ISBN: 978-0-9840378-4-1 (print)OAI: oai:DiVA.org:his-21829DiVA, id: diva2:1697443
Conference
7th International Digital Human Modeling Symposium (DHM 2022), August 29–30, 2022, Iowa City, Iowa, USA. The conference was followed by the Iowa Virtual Human Summit 2022.
Part of project
Virtual factories with knowledge-driven optimization (VF-KDO), Knowledge Foundation
Note

Copyright © 2022 the author(s) 

Available from: 2022-09-20 Created: 2022-09-20 Last updated: 2024-10-23Bibliographically approved

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Brolin, ErikHanson, LarsHögberg, Dan

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