Abstract
Functional compression textiles have been widely applied in fields of medical, healthcare, rehabilitation, sports and personal protection. The global compression wear market is expected to grow at a CAGR (Compound Average Growth Rate) of 5.1% during 2017–2022. The rising of chronic venous disorders (CVD) (e.g. varicose veins, deep vein thrombosis, lymphedema) and the steady rise of fitness and sports industry are the major drivers to push up the potentiality of compression textiles globally. However, user-oriented ergonomic fit and personalized pressure designs for precise individualized treatment have not matured. The aim of this study is to establish a new compression textiles design-development-assessment system including modular structured sections of 3D body scanning, 3D digital seamless knitting and 3D biomechanical visualization, based on medical magnetic resonance scanning images, leg anthropometry and finite element model, to enhance design efficiency, treatment precision, user fit and compliance of compression textiles in practice. The visualized pressure profiles along lower limbs lengthwise and crosswise as well as internal stress and tissue deformations can be quantitatively detected via new system to guide technical design and functional assessment of multi-class compression textiles. The pressure dosages calculated by FE model presented a favorable agreement with the experimental data, demonstrating its practicability. This new biodigital-based compression design approach raised functional performance of ergonomic design of compression textiles and enhanced our understanding on effects of varying textile design parameters on pressure dosages delivery for CVD treatment.
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Acknowledgment
This work was supported by General Research Grant (RGC) PolyU 252153/18E and Central Research Grants of the Hong Kong Polytechnic University through Research Projects PolyU 252064/17E and 1-ZVLQ.
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Liu, R., Xu, B., Ye, C. (2020). Biodigital Design and Functional Visualization of Multi-Class Personalized Compression Textiles for Ergonomic Fit. In: Di Bucchianico, G. (eds) Advances in Design for Inclusion. AHFE 2019. Advances in Intelligent Systems and Computing, vol 954. Springer, Cham. https://doi.org/10.1007/978-3-030-20444-0_51
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DOI: https://doi.org/10.1007/978-3-030-20444-0_51
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