Ergonomic Design of Footwear

AiDLab
Overview

This project aims to design a framework and learning algorithms that integrates foot biomechanics, dynamic 3D scanning, foot anthropometry and material properties to design orthotic footwear insoles with accurate control of interface pressure distribution in different loading conditions to yielding new insights and high-tech solutions in footwear design and engineering for improving health and wellbeing.

  • Ergonomic Design of Footwear 0
  • Ergonomic Design of Footwear 1
Commercialisation opportunities
non-exclusive licensing; insole evaluation services
Problem addressed

With impairment of protective sensation and high plantar pressure during locomotion, foot ulcerations are commonly found in diabetic patients. Custom-fabricated orthotic insoles are usually prescribed for reducing high plantar pressure and foot ulcers in the hospitals and/or clinics. However, traditional insole foam materials trap heat and moisture inside footwear, which may lead to discomfort. Its fabrication process is also highly complex, time-consuming and error-prone.

Innovation
  • An AI-based framework that utilised multilayer perceptron (MLP) neural network model with embedding technique has been proposed to advance the insole prescription and diagnostic processes by using a 2D footprint images obtained from a traditional podography to predict the changes in dynamic plantar pressures under various insole materials.
  • A novel textile-fabricated insole with 3D structure has also been developed to enhance support, thermal comfort and footwear microclimate of diabetic patients.
  • By using 4D foot scanning system and 3D printing technology, personalised 3D heel pad and arch support with a unique auxetic structure in conforming foot shape is also affixed to enhance the shock absorption and protect the foot from repeated impact forces during gait.
Key impact
  • The AI-based framework simplifies the diagnostic and insole prescription procedures of the orthotists and provide accurate diagnosis for clinicians to advance the design and fit of insoles and reduce the plantar pressure of diabetic patients.
  • The AI-based framework provides a simple and low-cost method for the diabetic patients to assess and monitor their plantar pressure at home.
  • The newly-developed insole can be used as the replacement of traditional insole foam materials and 3D moulding process.
  • The new insole also provides new approach for the footwear manufacturer to enable custom foot protection and offloading as well as improve the in-shoe micro-environment of the insole design.
Application
  • A simple and low-cost AI-based framework for the diabetic patients to assess and monitor their plantar pressure at home.
  • A novel textile-fabricated insole with 3D structure to replace traditional insole foam materials for diabetic patients.
  • AI-based framework simplifies the diagnostic and insole prescription procedures of the orthotists
  • The new insole provides new approach for the footwear manufacturer to enable custom foot protection and offloading as well as improve the in-shoe micro-environment of the insole design.

Patent

  • Plantar Pressure detection method and device, storage medium and electronic equipment (Patent App. No.: CN 202211391068.8)

AiDLab is the first research platform that focuses on the integration of Artificial Intelligence (AI) with design. It was jointly established by The Hong Kong Polytechnic University (PolyU) and the Royal College of Art (RCA) in the UK, and is funded by the HKSAR Government under the InnoHK Research Clusters. Located at the Hong Kong Science Park, AiDLab has established a new creative cluster of AI in design and is in a leading position internationally to conduct interdisciplinary research in three thematic programmes: Ergonomic and Inclusive Design, Innovation in Product and Service Design, and Intelligent Fashion Design and Quality Control, that drives innovation and sustainability, and makes a positive impact on both industry and society.

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