Curvature generation based on weight-updated boosting using shoe last point-cloud measurements

© 2024 The Authors. Published by Elsevier Ltd..

Lasts are foot-shaped forms made of plastic, wood, aluminum, or 3D-printed plastic. The last of a shoe determines not only its shape and style but also how well it fits and protects the foot. A weight-updated boosting-based ensemble learning (WUBEL) algorithm is presented in this paper to extract critical features (points) from plantar pressure imaging to optimize the shoe's last surface to satisfy a comfortable shoe's last surface optimization design. An enhanced last design is constructed from the foot measurement data of the bottom surface of the base last, the critical control lines (points) of the shoe's last body, and the running-in degree of the pressure-sensitive area lattice data. Using a Likert scale (LS) and relevant evaluation indicators, we conducted an experimental evaluation and comparative study of our enhanced last design. With a point-cloud dataset, the proposed method performs highly effectively in constructing shoes, which will help diabetes patients find comfortable and customized shoes.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:10

Enthalten in:

Heliyon - 10(2024), 4 vom: 29. Feb., Seite e26498

Sprache:

Englisch

Beteiligte Personen:

Wang, Dan [VerfasserIn]
Li, Zairan [VerfasserIn]
Dey, Nilanjan [VerfasserIn]
Misra, Bitan [VerfasserIn]
Sherratt, R Simon [VerfasserIn]
Shi, Fuqian [VerfasserIn]

Links:

Volltext

Themen:

Comfort shoes
Ensemble learning
Journal Article
Point-cloud dataset
Shoe last customizing

Anmerkungen:

Date Revised 05.03.2024

published: Electronic-eCollection

Citation Status PubMed-not-MEDLINE

doi:

10.1016/j.heliyon.2024.e26498

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM369238966