Footwear is intended to offer the first line of protectionto the feet. Inappropriate footwear not only causes discomfort, but also results in foot pain, tissue injury and ulceration due to high plantar pressure. The problems are exacerbaed when people have deformed feet and/or diabetic foot ulcers.

In custom designed diabetic footwear, feet are usually measured or scanned in static standing or non-weight-bearing sitting conditions. Hence, specific information on the geometric characteristics of the foot plantar is particularly scarce. Inherent ambiguity also exists in the foot dimension and the 3D foot shape geometry changes during locomotion due to changes in body weight and balance.

This project incorporates precise 3D foot shape and plantar geometries, human locomotion and realistic models of footwear material behavior to enchance the ergonomic design of footwear for diabetic patients. A novel knitted insole material structure has been developed to enhance in-shoe comfort, air and moisture permeabilities. With the assistance of artificial intelligence and image deep learning, ergonomic footwear providing explicit control of plantar pressure and wear comfort can be designed and developed.
Project Leaflet

Publication:
Tang, K. P. M., Yick, K. L., Li, P. L., Yip, J., Or, K. H., & Chau, K. H. (2020). Effect of Contacting Surface on the Performance of Thin-Film Force and Pressure Sensors. Sensors, 20(23), 6863. https://doi.org/10.3390/s20236863

Yu, A., Yick, K. L., & Wong, S. T. (2021). Analysis of length of finger segments with different hand postures to enhance glove design. Applied Ergonomics, 94, 103409. https://doi.org/10.1016/j.apergo.2021.103409

Principal Investigator
Dr Kit Lun YICK

Commercialisation Opportunity:
The above technology from AiDLab project RP1-2 is ready for commercialisation. Please feel free to contact us for discussion if you are interested to explore the collaboration opportunities.