Authors:
Thierry Perret-Ellena
;
Aleksandar Subic
;
Toh Yen Pang
and
Helmy Mustafa
Affiliation:
RMIT University, Australia
Keyword(s):
3D Anthropometry, Reverse Engineering, Gap Analysis, Bicycle Helmet Fit, 3D Scanner.
Related
Ontology
Subjects/Areas/Topics:
Computer Systems in Sports
;
Simulation and Mathematical Modeling
;
Sport Science Research and Technology
Abstract:
While a bicycle helmet protects the wearer’s head in the event of a crash, not every user benefits to the same extent when wearing the headgear. A proper fit with the cyclist’s head is found to be one of the most important attributes to improve protection during impact. A correct fit is defined as a small and uniform distance between the helmet liner and the wearer’s head shape, with a broad coverage of the head area. The scientific community has recognised the need for improved fitting, but in-depth methods to analyse and compare the fit performance of distinct helmets models are still absent from the literature. We present a method based on 3D anthropometry, reverse engineering techniques and computational analysis to redress this shortcoming. As a result of this study, we introduce the Helmet Fit Index (HFI) as a tool for fit analysis between a helmet model and a human head. It is envisaged that the HFI can provide detailed understanding of helmet efficiency regarding fit and shou
ld be used during helmet development phases and testing.
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