A novel anthropometric method to accurately evaluate tissue deformation
IntroductionBiomechanical imaging through body scanning can provide a more comprehensive understanding of the soft tissue deformation exerted by compression sportswear, which is crucial in sports science research and functional sportswear design. However, displacement from movement affects alignment...
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Bioengineering and Biotechnology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fbioe.2025.1632806/full |
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| Summary: | IntroductionBiomechanical imaging through body scanning can provide a more comprehensive understanding of the soft tissue deformation exerted by compression sportswear, which is crucial in sports science research and functional sportswear design. However, displacement from movement affects alignment so accurately measuring tissue deformation with different wear conditions becomes challenging.MethodsTo address this issue, an analytical model is constructed to predict tissue deformation by using the Boussinesq solution, which is based on the elastic theory and stress function method. Moreover, a novel anthropometric method based on image recognition algorithms that systematically measures and evaluates tissue deformation while minimizing the impact of the effects of motion is proposed. The mechanical properties of five leggings samples are tested by using the Instron 4,411 and KES-FB1 systems to determine the uniaxial tension and pure shear.ResultsThe predicted results are then compared with the experimental results, which shows that they are in good agreement, with deviations within 1.15 mm for the static condition and 2.36 mm for the dynamic condition, thus validating the proposed novel method.DiscussionThis anthropometric approach is an invaluable tool for evaluating tissue deformation patterns, thus providing key insights for sportswear designers to optimize garment performance and design. |
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| ISSN: | 2296-4185 |