Bicycle helmet size, adjustment, and stability

A parametric design framework for the mass customization of bicycle helmet

Cluster analysis of 3D head shapes plays a crucial role in the mass customization design of products related to the head. Head shapes exhibit variations across different races, and designing helmets exclusively for Chinese individuals cannot solely rely on or reference foreign head models. Currently, research on cluster analysis of Chinese head shapes is limited, especially concerning shape variances. To address this, we developed an improved k-medoids algorithm and integrated Cluster Validity Index as an assessment metric. This enabled us to cluster 339 Chinese young males aged 18 to 30 into 7 groups based on their head shapes. By comparing our improved algorithm to the traditional k-medoids method, we affirmed its superiority in achieving higher sample participation rates and reducing inter-cluster sample disparities. To simplify the helmet design and editing process, and to improve the efficiency of mass customization, we have developed a parametric modeling program for bicycle helmets based on the head shape clustering results. Results from the Helmet Fit Index and stress simulation analysis demonstrate that our approach significantly enhances helmet fit and wearer comfort.

Approximating subject-specific brain injury models via scaling based on head-brain morphological relationships

Most human head/brain models represent a generic adult male head/brain. They may suffer in accuracy when investigating traumatic brain injury (TBI) on a subject-specific basis. Subject-specific models can be developed from neuroimages; however, neuroimages are not typically available in practice. In this study, we establish simple and elegant regression models between brain outer surface morphology and head dimensions measured from neuroimages along with age and sex information (N = 191; 141 males and 50 females with age ranging 14-25 years). The regression models are then used to approximate subject-specific brain models by scaling a generic counterpart, without using neuroimages. Model geometrical accuracy is assessed using adjusted [Formula: see text] and absolute percentage error (e.g., 0.720 and 3.09 ± 2.38%, respectively, for brain volume when incorporating tragion-to-top). For a subset of 11 subjects (from smallest to largest in brain volume), impact-induced brain strains are compared with those from "morphed models" derived from neuroimage-based mesh warping. We find that regional peak strains from the scaled subject-specific models are comparable to those of the morphed counterparts but could be considerably different from those of the generic model (e.g., linear regression slope of 1.01-1.03 for gray and white matter regions versus 1.16-1.19, or up to ~ 20% overestimation for the smallest brain studied). These results highlight the importance of incorporating brain morphological variations in impact simulation and demonstrate the feasibility of approximating subject-specific brain models without neuroimages using age, sex, and easily measurable head dimensions. The scaled models may improve subject specificity for future TBI investigations.

Sex-based differences in helmet performance in bicycle trauma

OBJECTIVES

To determine the existence of sex-based differences in the protective effects of helmets against common injuries in bicycle trauma.

METHODS

In a retrospective cohort study, we identified patients 18 years or older in the 2017 National Trauma Database presenting after bicycle crash. Sex-disaggregated and sex-combined multivariable logistic regression models were calculated for short-term outcomes that included age, involvement with motor vehicle collision, anticoagulant use, bleeding disorder and helmet use. The sex-combined model included an interaction term for sex and helmet use. The resulting exponentiated model parameter yields an adjusted OR ratio of the effects of helmet use for females compared with males.

RESULTS

In total, 18 604 patients of average age 48.1 were identified, and 18% were female. Helmet use was greater in females than males (48.0% vs 34.2%, p<0.001). Compared with helmeted males, helmeted females had greater rates of serious head injury (37.7% vs 29.9%, p<0.001) despite less injury overall. In sex-disaggregated models, helmet use reduced odds of intracranial haemorrhage and death in males (p<0.001) but not females. In sex-combined models, helmets conferred to females significantly less odds reduction for severe head injury (p=0.002), intracranial bleeding (p<0.001), skull fractures (p=0.001), cranial surgery (p=0.006) and death (p=0.017). There was no difference for cervical spine fracture.

CONCLUSIONS

Bicycle helmets may offer less protection to females compared with males. The cause of this sex or gender-based difference is uncertain, but there may be intrinsic incompatibility between available helmets and female anatomy and/or sex disparity in helmet testing standards.

Fit, stability and comfort assessment of custom-fitted bicycle helmet inner liner designs, based on 3D anthropometric data

Research has demonstrated that a better-fitted bicycle helmet offers improved protection to the rider during an impact. Nowadays, bicycle helmets in the market that range in size from small/medium to medium/large might not fit the diverse range of human head shapes and dimensions. 3D scanning was used to create 3D head shape databases of 20 participants who volunteered for the study. We developed new custom-fitted helmet inner liners, based on the 3D head shape of two sub-groups of participants, to map their head sizes and contours closely to the conventional Medium (M) and Large (L) sizes as described in from AS/NZS 2512.1: 2009. The new custom-fitted helmet was compared with the helmet available in the market place in a dynamics stability test and from participants' subjective feedback. A significant reduction in the angle of helmet rotation on the headform in the lateral direction was recorded for the custom-fitted helmet. A Wilcoxon signed-rank test was conducted to evaluate participants' feedback on the helmets according to different area definitions. The overall fit and comfort and the top region of the new helmet were significantly improved. However, no difference was found at the significant level of 0.05 for the front and rear region of the new helmet.

Head injury mechanisms in FIS World Cup alpine and freestyle skiers and snowboarders

Introduction

Head injuries represent a concern in skiing and snowboarding, with traumatic brain injuries being the most common cause of death.

Aim

To describe the mechanisms of head and face injuries among World Cup alpine and freestyle skiers and snowboarders.

Methods

We performed a qualitative analysis of videos obtained of head and face injuries reported through the International Ski Federation Injury Surveillance System during 10 World Cup seasons (2006–2016). We analysed 57 head impact injury videos (alpine n=29, snowboard n=13, freestyle n=15), first independently and subsequently in a consensus meeting.

Results

During the crash sequence, most athletes (84%) impacted the snow with the skis or board first, followed by the upper or lower extremities, buttocks/pelvis, back and, finally, the head. Alpine skiers had sideways (45%) and backwards pitching falls (35%), with impacts to the rear (38%) and side (35%) of the helmet. Freestyle skiers and snowboarders had backwards pitching falls (snowboard 77%, freestyle 53%), mainly with impacts to the rear of the helmet (snowboard 69%, freestyle 40%). There were three helmet ejections among alpine skiers (10% of cases), and 41% of alpine skiing injuries occurred due to inappropriate gate contact prior to falling. Athletes had one (47%) or two (28%) head impacts, and the first impact was the most severe (71%). Head impacts were mainly on snow (83%) on a downward slope (63%).

Conclusion

This study has identified several characteristics of the mechanisms of head injuries, which may be addressed to reduce risk.

The effect of motorcycle helmet fit on estimating head impact kinematics from residual liner crush

Proper helmet fit is important for optimizing head protection during an impact, yet many motorcyclists wear helmets that do not properly fit their heads. The goals of this study are i) to quantify how a mismatch in headform size and motorcycle helmet size affects headform peak acceleration and head injury criteria (HIC), and ii) to determine if peak acceleration, HIC, and impact speed can be estimated from the foam liner's maximum residual crush depth or residual crush volume. Shorty-style helmets (4 sizes of a single model) were tested on instrumented headforms (4 sizes) during linear impacts between 2.0 and 10.5m/s to the forehead region. Helmets were CT scanned to quantify residual crush depth and volume. Separate linear regression models were used to quantify how the response variables (peak acceleration (g), HIC, and impact speed (m/s)) were related to the predictor variables (maximum crush depth (mm), crush volume (cm³), and the difference in circumference between the helmet and headform (cm)). Overall, we found that increasingly oversized helmets reduced peak headform acceleration and HIC for a given impact speed for maximum residual crush depths less than 7.9mm and residual crush volume less than 40cm³. Below these levels of residual crush, we found that peak headform acceleration, HIC, and impact speed can be estimated from a helmet's residual crush. Above these crush thresholds, large variations in headform kinematics are present, possibly related to densification of the foam liner during the impact.

The Helmet Fit Index--An intelligent tool for fit assessment and design customisation

Helmet safety benefits are reduced if the headgear is poorly fitted on the wearer's head. At present, there are no industry standards available to assess objectively how a specific protective helmet fits a particular person. A proper fit is typically 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. This paper presents a novel method to investigate and compare fitting accuracy of helmets based on 3D anthropometry, reverse engineering techniques and computational analysis. The Helmet Fit Index (HFI) that provides a fit score on a scale from 0 (excessively poor fit) to 100 (perfect fit) was compared with subjective fit assessments of surveyed cyclists. Results in this study showed that quantitative (HFI) and qualitative (participants' feelings) data were related when comparing three commercially available bicycle helmets. Findings also demonstrated that females and Asian people have lower fit scores than males and Caucasians, respectively. The HFI could provide detailed understanding of helmet efficiency regarding fit and could be used during helmet design and development phases.

A shape-based helmet fitting system for concussion protection

Helmets are widely used as protection against sports-related concussions. The degree of concussion protection offered by a helmet may be related to the fit between the helmet and head. This paper presents the design of a prototype helmet fitting recommendation system using shape-based helmet fitting. The shape-based helmet fitting system uses a Kinect sensor to scan a client's head and then compares the head shape to helmet shapes from a database of off-the-shelf helmets. A slice extraction method is used to compare a standard reference slice extracted from the head to a corresponding slice from the helmet. The degree to which the helmet fits the client's head is calculated and displayed to the user. The prototype system could potentially help a concussion expert make recommendations about helmet fit to clients, if more research about the effects of helmet fitting on concussion protection becomes available.