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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 should be used during helmet development phases and testing.

The Helmet Fit Index - A Method for the Computational Analysis of Fit between Human Head Shapes and Bicycle Helmets