PolyU research boosts garment fit and performance for sports and medical apparel with groundbreaking anthropometric method to pr
Archived: 2026-04-23 17:09
PolyU research boosts garment fit and performance for sports and medical apparel with groundbreaking anthropometric method to precisely measure tissue deformation | The Hong Kong Polytechnic University
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Prof. Joanne Yip, Associate Dean and Professor of PolyU School of Fashion and Textiles, and her research team developed a novel anthropometric method using image recognition algorithms to systematically access tissue deformation while minimising motion-related errors.
Sports leggings with different material mechanical properties, pattern designs and circumferential dimensions were used as experimental samples.
Sports leggings with different material mechanical properties, pattern designs and circumferential dimensions were used as experimental samples.
Sports leggings with different material mechanical properties, pattern designs and circumferential dimensions were used as experimental samples.
By leveraging image recognition algorithms, this innovation quantifies tissue deformation during movement, addressing a longstanding challenge in the sportswear and wearable tech design.
Soft tissue deformation during body movement has long posed a challenge to achieving optimal garment fit and comfort, particularly in sportswear and functional medical wear. Researchers at The Hong Kong Polytechnic University (PolyU) have developed a novel anthropometric method that delivers highly accurate measurements to enhance the performance and design of compression-based apparel.
Prof. Joanne YIP, Associate Dean and Professor of
the
School of Fashion and Textiles at PolyU
, and her research team pioneered this anthropometric method using image recognition algorithms to systematically access tissue deformation while minimising motion-related errors. The team also
develop
ed an analytical model to predict tissue deformation using the Boussinesq solution, based on elastic theory and stress function methodology.
By leveraging
image recognition algorithms, this innovation quantif
ies
tissue deformation during movement,
addressing
a longstanding challenge in sportswear and wearable
tech
design.
Inaccurate deformation measurements, especially during motion, often lead to ill-fitting designs that undermine functionality. This innovative approach tackles the issue by minimising motion artifacts and providing a systematic framework to correlate garment pressure with tissue response, which is vital for optimising wearables’ the biochemical efficacy.
Soft tissue deformation is a critical factor directly influencing appearance, comfort, performance, and physiological effects such as blood circulation and muscle support. With the integration of mechanical property testing, the method accurately predicts tissue deformation. Validation against body scanning measurements showed deviations within 1.15 mm under static condition and 2.36 mm in dynamic condition. The remarkable precision of this method equips designers with reliable data that accurately reflects soft tissue deformation.
Prof. Joanne Yip
said, “Our technology is highly adaptable to compression-based garments, including sportswear such as leggings and functional medical wear like compression stockings and post-surgical garments. The analytical model can be tailored to different garment types by adjusting parameters like material mechanical properties and circumferential dimensions.”
Sports leggings with different material mechanical properties, pattern designs and circumferential dimensions were used as experimental samples. Research findings offer actionable insights that link material properties to garment fit and performance. This framework not only advances biomechanical simulation techniques for wearable applications but also provides a practical tool for optimising sportswear ergonomics, enabling data-driven design of compression garments that enhances athletic performance while preventing the risk of musculoskeletal injuries.
This innovative technology holds promising transformative potential for the industry, offering feasible and cost-effective applications. It can be integrated into existing CAD/CAM system to streamline prototyping and reduce reliance on trial-and-error filling. By quantifying individual tissue response, this technique supports personalised garment design, particularly beneficial for medical compression wear tailored to specific patient needs. Additionally, the image-based tools reduce dependence on expensive motion-capture systems, making the approach accessible for small and medium-sized enterprises.
The research has been published in
a paper
titled “
A novel anthropometric method to accurately evaluate tissue deformation
”
in
the academic journal
Frontiers in Bioengineering and Biotechnology
.
This technology breakthrough underscores PolyU excellence in interdisciplinary translational research, integrating
its
strengths in fashion, biomechanics, materials science, computing, and engineering to solve real-world compression sportswear design and wearable design challenges.
***END***
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繁體
简体
Education
Education
Teaching and Learning
Broad-based Curriculum for Holistic Academic Development
Work-Integrated Education
Service-Learning
Student Exchange
Leadership Programme
Faculties, Schools and College
Graduate School
College of Undergraduate Studies
Admissions
Admissions
Why PolyU
Study@PolyU
University Ranking
Student Stories
Programmes, Tuition Fees and Scholarships
Tuition Fees and Scholarships
Research
Research
PolyU Academy for Interdisciplinary Research (PAIR)
Mainland Translational Research Institutes
State Key Laboratories and Chinese National Engineering Research Centres (HK Branches)
State Key Laboratory of Climate Resilience for Coastal Cities
State Key Laboratory of Ultra-precision Machining Technology
Hong Kong Branch of National Engineering Research Centre for Steel Construction
Hong Kong Branch of National Rail Transit Electrification and Automation Engineering Technology Research Centre
University-level Research Centres and Facilities
Faculty/School/Department-level Research Centres
University Research Facilities
Centralised Animal Facilities
University Research Facility in 3D Printing
University Research Facility in Behavioral and Systems Neuroscience
University Research Facility in Big Data Analytics
University Research Facility in Chemical and Environmental Analysis
University Research Facility in Life Sciences
University Research Facility in Materials Characterization and Device Fabrication
InnoHK
Centre for Eye and Vision Research (CEVR)
Laboratory for Artificial Intelligence in Design (AiDLab)
Research Centre for Intelligent GRID and Energy Technologies (I-GET)
Graduate School
Research and Innovation Office
PolyU Scholars
Academicians and Distinguished Scholars
PolyU Scholars Hub
Knowledge Transfer
Knowledge Transfer
Innovation and Technology Development
Technology Transfer and Commercialisation
Entrepreneurship
Success Stories
Global
Global
International Community
Global Perspectives in Academic Programmes
International Collaborations and Partnerships
Eyes on China
Campus Life
Campus Life
Athletics and Recreation
Art and Culture
Living on Campus
Counselling and Wellness
Clinics and Centres
Housing
Dining
About PolyU
About PolyU
PolyU at a Glance
Motto, Vision and Mission
Key Facts
University Identity
History
University Committee Structure
Leadership
Governance
Organisations
Campus Map
Photo Gallery
Video Channel
Publications
Alumni
Current Students
Staff
Start main content
Prof. Joanne Yip, Associate Dean and Professor of PolyU School of Fashion and Textiles, and her research team developed a novel anthropometric method using image recognition algorithms to systematically access tissue deformation while minimising motion-related errors.
Sports leggings with different material mechanical properties, pattern designs and circumferential dimensions were used as experimental samples.
Sports leggings with different material mechanical properties, pattern designs and circumferential dimensions were used as experimental samples.
Sports leggings with different material mechanical properties, pattern designs and circumferential dimensions were used as experimental samples.
By leveraging image recognition algorithms, this innovation quantifies tissue deformation during movement, addressing a longstanding challenge in the sportswear and wearable tech design.
Soft tissue deformation during body movement has long posed a challenge to achieving optimal garment fit and comfort, particularly in sportswear and functional medical wear. Researchers at The Hong Kong Polytechnic University (PolyU) have developed a novel anthropometric method that delivers highly accurate measurements to enhance the performance and design of compression-based apparel.
Prof. Joanne YIP, Associate Dean and Professor of
the
School of Fashion and Textiles at PolyU
, and her research team pioneered this anthropometric method using image recognition algorithms to systematically access tissue deformation while minimising motion-related errors. The team also
develop
ed an analytical model to predict tissue deformation using the Boussinesq solution, based on elastic theory and stress function methodology.
By leveraging
image recognition algorithms, this innovation quantif
ies
tissue deformation during movement,
addressing
a longstanding challenge in sportswear and wearable
tech
design.
Inaccurate deformation measurements, especially during motion, often lead to ill-fitting designs that undermine functionality. This innovative approach tackles the issue by minimising motion artifacts and providing a systematic framework to correlate garment pressure with tissue response, which is vital for optimising wearables’ the biochemical efficacy.
Soft tissue deformation is a critical factor directly influencing appearance, comfort, performance, and physiological effects such as blood circulation and muscle support. With the integration of mechanical property testing, the method accurately predicts tissue deformation. Validation against body scanning measurements showed deviations within 1.15 mm under static condition and 2.36 mm in dynamic condition. The remarkable precision of this method equips designers with reliable data that accurately reflects soft tissue deformation.
Prof. Joanne Yip
said, “Our technology is highly adaptable to compression-based garments, including sportswear such as leggings and functional medical wear like compression stockings and post-surgical garments. The analytical model can be tailored to different garment types by adjusting parameters like material mechanical properties and circumferential dimensions.”
Sports leggings with different material mechanical properties, pattern designs and circumferential dimensions were used as experimental samples. Research findings offer actionable insights that link material properties to garment fit and performance. This framework not only advances biomechanical simulation techniques for wearable applications but also provides a practical tool for optimising sportswear ergonomics, enabling data-driven design of compression garments that enhances athletic performance while preventing the risk of musculoskeletal injuries.
This innovative technology holds promising transformative potential for the industry, offering feasible and cost-effective applications. It can be integrated into existing CAD/CAM system to streamline prototyping and reduce reliance on trial-and-error filling. By quantifying individual tissue response, this technique supports personalised garment design, particularly beneficial for medical compression wear tailored to specific patient needs. Additionally, the image-based tools reduce dependence on expensive motion-capture systems, making the approach accessible for small and medium-sized enterprises.
The research has been published in
a paper
titled “
A novel anthropometric method to accurately evaluate tissue deformation
”
in
the academic journal
Frontiers in Bioengineering and Biotechnology
.
This technology breakthrough underscores PolyU excellence in interdisciplinary translational research, integrating
its
strengths in fashion, biomechanics, materials science, computing, and engineering to solve real-world compression sportswear design and wearable design challenges.
***END***
We use Cookies to give you a better experience on our website. By continuing to browse the site without changing your privacy settings, you are consenting to our use of Cookies. For more information, please see our
Privacy Policy Statement
.
Your browser is not the latest version. If you continue to browse our website, Some pages may not function properly.
You are recommended to upgrade to a newer version or switch to a different browser. A list of the web browsers that we support can be found
here
What are you looking for?
Internal Document Search
Popular Search
Undergraduate Admission
Postgraduate Admission
Scholarships
Financial Assistance
Service-Learning
Rankings
Internship
Entrepreneurship
Greater Bay Area
MOOCs
Clinics
Campus Map
Finance Office
Human Resources Office
Library