Automatic parametric digital design of custom-fit bicycle helmets based on 3D anthropometry and novel clustering algorithm

Bicycle helmets can provide valuable protective effects to the wearer’s head in the event of a crash. However, the level of protection that helmets offer varies greatly between the users for similar impacts. Although these discrepancies can be due to many causes, several researchers highlighted the poor fit of helmets experienced by some users as a possible explanation. Poor helmet fit may be attributed to two main causes. First, the helmet could be worn incorrectly, with the helmet either worn back to front, or tilted forward or backward. The chin strap could also be unfastened. Second, helmet sizes and shapes available to the public might not be suitable for the full range of head morphologies observed in the population. Indeed, for some users, there could either be a large gap and/or pressure points between the inner surfaces of the helmet and the head, or a low coverage of the skull area with significant unprotected regions of the head. While the poorly informed usage of bicycle helmets is partly rectifiable through education programs, the mismatch between the head and the helmet’s inside surfaces primarily relates to the conventional design method and manufacturing techniques used in the industry today. In addition to the safety concerns described above, poorly fitted helmets can cause significant discomfort and may lead people to cycle infrequently or even not cycle altogether. Such a reaction could be somewhat detrimental to the user since the health benefits of regular cycling are significant. Some organisations and institutions even believe that the risks involved in cycling without a helmet (in not-extreme practices such as mountain biking) might be outweighed by the health benefits of consistent physical workout that the activity procures. However, this is impractical in countries such as Australia where mandatory helmet laws (MHL) are in place. Improper helmet fit coupled with MHL might be the reason why Australians cycle less than formerly, despite many initiatives undertaken by the government to grow the activity. In summary, current commercially available bicycle helmets suffer from the lack of fit accuracy, are uncomfortable, and consequently can discourage riding activities in the community, especially in populations like Australia where MHL exist. Therefore, the main purpose of this research has been to develop an innovative method to produce bicycle helmet models that provide a highly accurate fit to the wearer’s head. To achieve this goal, a mass customisation (MC) framework was initiated. MC systems enable the association of the small unit costs of mass production with the compliance of individual customisation. Although MC is defined as the use of both computer-aided design and manufacturing systems to produce custom output, it was decided to focus exclusively, in this study, on the design part of the MC framework of bicycle helmets. More specifically, I tried to answer the following central research question: How can one automatically create commercially ready, custom-fit digital 3D models of bicycle helmets based on 3D anthropometric data? One objective was to create certified design models, since helmets must comply with relevant safety regulations to be sold in a country. Safety standards generally determine the amount of energy a helmet must absorb during a crash, which mostly affects the thickness of its foam liner. Since customisation plays a major role in the helmet liner’s thickness, special considerations on how the automatic process should affect the helmet’s shape were provided. Contrary to conventional helmet production techniques, this method was based on state of the art technologies and techniques, such as three-dimensional (3D) anthropometry, supervised and unsupervised machine-learning methods, and fully parametric design models. Indeed, until today, traditional 1D anthropometric data (e.g., head circumference, head length, and head breath) have been the primary sources of information used by ergonomists for the design of user-centred products such as helmets. Although these data are simple to use and understand, they only provide univariate measures of key dimensions, and these tend to only partially represent the actual shape characteristics of the head. However, 3D anthropometric data can capture the full shape of a scanned surface, thereby providing meaningful information for the design of properly fitted headgear. However, the interpretation of these data can be complicated due to the abundance of information they contain (i.e., a 3D head scan can contain up to several million data points). In recent years, the use of 3D measurements for product design has become more appealing thanks to the advances in mesh parameterization, multivariate analyses, and clustering algorithms. Such analyses and algorithms have been adopted in this project. To the author’s knowledge, this is the first time that these methods have been applied to the design of helmets within a mass customisation framework. As a result, a novel method has been developed to automatically create a complete, certified custom-fit 3D model of a bicycle helmet based on the 3D head scan of a specific individual. Even though the manufacturing of the generated customised helmets is not discussed in detail in this research, it is envisaged that the models could be fabricated using either advanced subtractive and additive manufacturing technologies (e.g., numerical control machining and 3D printing.), standard moulding techniques, or a combination of both. The proposed design framework was demonstrated using a case study where customised helmet models were created for Australian cyclists. The computed models were evaluated and validated using objective (digital models) fit assessments. Thus, a significant improvement in terms of fit accuracy was observed compared to commercially available helmet models. More specifically, a set of new techniques and algorithms were developed, which successively: (i) clean, repair, and transform a digitized head scan to a registered state; (ii) compare it to the population of interest and categorize it into a predefined group; and (iii) modify the group’s generic helmet 3D model to precisely follow the head shape considered. To successfully implement the described steps, a 3D anthropometric database comprising 222 Australian cyclists was first established using a cutting edge handheld white light 3D scanner. Subsequently, a clustering algorithm, called 3D-HEAD-CLUSTERING, was introduced to categorize individuals with similar head shapes into groups. The algorithm successfully classified 95% of the sample into four groups. A new supervised learning method was then developed to classify new customers into one of the four computed groups. It was named the 3D-HEAD-CLASSIFIER. Generic 3D helmet models were then generated for each of the computed groups using the minimum, maximum, and mean shapes of all the participants classified inside a group. The generic models were designed specifically to comply with the relevant safety standard when accounting for all the possible head shape variations within a group. Furthermore, a novel quantitative method that investigates the fit accuracy of helmets was presented. The creation of the new method was deemed necessary, since the scarce computational methods available in the literature for fit assessment of user-centred products were inadequate for the complex shapes of today’s modern bicycle helmets. The HELMET-FIT-INDEX (HFI) was thus introduced, providing a fit score ranging on a scale from 0 (excessively poor fit) to 100 (perfect fit) for a specific helmet and a specific individual. In-depth analysis of three commercially available helmets and 125 participants demonstrated a consistent correlation between subjective assessment of helmet fit and the index. The HFI provided a detailed understanding of helmet efficiency regarding fit. For example, it was shown that females and Asians experience lower helmet fit accuracy than males and Caucasians, respectively. The index was used during the MC design process to validate the high fit accuracy of the generated customised helmet models. As far as the author is aware, HFI is the first method to successfully demonstrate an ability to evaluate users’ feelings regarding fit using computational analysis. The user-centred framework presented in this work for the customisation of bicycle helmet models is proved to be a valuable alternative to the current standard design processes. With the new approach presented in this research study, the fit accuracy of bicycle helmets is optimised, improving both the comfort and the safety characteristics of the headgear. Notwithstanding the fact that the method is easily adjustable to other helmet types (e.g., motorcycle, rock climbing, football, military, and construction), the author believes that the development of similar MC frameworks for user-centred products such as shoes, glasses and gloves could be adapted effortlessly. Future work should first emphasise the fabrication side of the proposed MC system and describe how customised helmet models can be accommodated in a global supply chain model. Other research projects could focus on adjusting the proposed customisation framework to other user-centred products

NIOSH Healthcare and Social Assistance Program: Evidence Package 2006-2016

This document contains materials to demonstrate the relevance and impact of the Healthcare and Social Assistance Program\u2019s work in the areas of safe and healthy workplaces, musculoskeletal disorders, hazardous drugs and other chemicals, and infectious disease transmission

Soft- and hard-tissue facial anthropometry in three dimensions: what’s new

In the last few years, technology has provided new instruments for the three-dimensional analysis of human facial morphology. Currently, quantitative assessments of dimensions, spatial positions and relative proportions of distinctive facial features can be obtained for both soft- and hard- (skeletal and dental) tissues. New mathematical tools allow to fuse digital data obtained from various image analyzers, thus providing quantitative information for anatomical and anthropometric descriptions, medical evaluations (clinical genetics, orthodontics, maxillo-facial and plastic surgery), and forensic medicine

Análise biomecânica de impactos com capacetes: novos materiais e geometrias

Doutoramento em Engenharia MecânicaA cortiça é um material celular natural capaz de suster quantidades consideráveis de energia. Estas características tornam este material ideal para determinadas aplicações como a proteção de impactos. Considerando equipamentos de segurança passiva pessoal, os materiais sintéticos são hoje em dia os mais utilizados, em particular o poliestireno expandido. Este também é capaz de absorver razoáveis quantidades de energia via deformação permanentemente. Por outro lado, a cortiça além de ser um material natural, é capaz de recuperar grande parte da sua forma após deformada, uma característica desejada em aplicações com multi-impacto. Neste trabalho é efetuada uma avaliação da aplicabilidade da cortiça em equipamentos de segurança pessoal, especificamente capacetes. Vários tipos de cortiça aglomerada foram caracterizados experimentalmente. Impactos foram simulados numericamente para avaliar a validade dos modelos constitutivos e as propriedades utilizadas para simular o comportamento da cortiça. Capacetes foram selecionados como caso de estudo, dado as energias de impacto e repetibilidade de impactos a que estes podem ser sujeitos. Para avaliar os capacetes de um ponto de vista biomecânico, um modelo de cabeça humana em elementos finitos foi desenvolvido. Este foi validado de acordo com testes em cadáveres existentes na literatura. Dois modelos de capacete foram modelados. Um modelo de um capacete rodoviário feito de materiais sintéticos, o qual se encontra disponível no mercado e aprovado pelas principais normas de segurança de capacetes, que serve de referência. Este foi validado de acordo com os impactos da norma. Após validado, este foi avaliado com o modelo de cabeça humana em elementos finitos e uma análise ao risco de existência de lesões foi efetuado. Com este mesmo capacete, foi concluído que para incorporar cortiça aglomerada, a espessura teria de ser reduzida. Então um novo modelo de capacete foi desenvolvido, sendo este uma espécie de modelo genérico com espessuras constantes. Um estudo paramétrico foi realizado, variando a espessura do capacete e submetendo o mesmo a duplos impactos. Os resultados destes impactos e da análise com o modelo de cabeça indicaram uma espessura ótima de 40 mm de cortiça aglomerada, com a qual o capacete tem uma melhor resposta a vários impactos do que se feito de poliestireno expandido.Cork is a natural cellular material capable of withstanding considerable amounts of energy. These features make it an ideal material for some applications, such as impact protection. Regarding personal safety gear, synthetic materials, particularly expanded polystyrene, are typically used. These are also able to absorb reasonable amounts of energy by deforming permanently. On the other hand, in addition to cork being a natural material, it recovers almost entirely after deformation, which is a desired characteristic in multi-impact applications. In this work, the applicability of agglomerated cork in personal safety gear, specifically helmets, is analysed. Different types of agglomerated cork were experimentally characterized. These experiments were simulated in order to assess the validity of the constitutive models used to replicate cork's mechanical behaviour. In order to assess the helmets from a biomechanical point of view, a finite element human head model was developed. This head model was validated by simulating the experiments performed on cadavers available in the literature. Two helmet models were developed. One of a motorcycle helmet made of synthetic materials, which is available on the market and certified by the main motorcycle helmets safety standards, being used as reference. This helmet model was validated against the impacts performed by the European standard. After validated, this helmet model was analysed with the human head model, by assessing its head injury risk. With this helmet, it was concluded that a thinner helmet made of agglomerated cork might perform better. Thus, a new helmet model with a generic geometry and a constant thickness was developed. Several versions of it were created by varying the thickness and subjecting them to double impacts. The results from these impacts and the analyses carried out with the finite element head model indicated an optimal thickness of 40 mm, with which the agglomerated cork helmet performed better than the one made of expanded polystyrene

Review—Lab-in-a-Mouth and Advanced Point-of-Care Sensing Systems: Detecting Bioinformation from the Oral Cavity and Saliva

Cavitas sensors and point-of-need sensors capable of providing physical and biochemical information from the oral cavity and saliva have attracted great attention because they offer remarkable advantages for noninvasive sensing systems. Herein, we introduce the basic anatomy and physiology of important body cavities to understand their characteristics as it is a pivotal foundation for the successful development of in-mouth devices. Next, the advanced development in lab-in-a-mouth sensors and point-of-need sensors for analyzing saliva are explained. In addition, we discuss the integrations of artificial intelligence and electronic technologies in smart sensing networks for healthcare systems. This review ends with a discussion of the challenges, future research trends, and opportunities in relevant disciplines. Mouthguard-based sensors and conventional salivary sensing devices will continue to be significant for the progress in the next-generation sensing technologies and smart healthcare systems.ope

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 385)

This bibliography lists 536 reports, articles and other documents introduced into the NASA Scientific and Technical Information System Database. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

NIOSH bibliography of communication and research products 2010: a listing of NIOSH publications for calendar year 2010

"This publication is a compendium of NIOSH publications and reports produced during calendar year 2009 [i.e., 2010]. Citations are listed by category including: I. Journal Articles; II. Book Chapters; III. NIOSH Numbered Publications; IV. Abstracts/Proceedings; V. Control Technology Reports; VI. Fatality Assessment and Control Evaluation Reports; VII. Fire Fighter Fatality Investigation and Prevention Reports; and, VIII. Health Hazard Evaluation Reports. Author, keyword and National Occupational Research Agenda (NORA) priority area indexes are also included." - NIOSHTIC-2I. Journal articles -- II. Books and book chapters -- III. NIOSH numbered publications -- IV. Abstracts/Proceedings -- V. Control technology reports -- VI. Fatality assessment and control evaluation reports -- VII. Fire fighter fatality investigation and prevention reports -- VIII. Health hazard evaluation reports -- IX. Author index-- X. Keyword index -- XI. National Occupational Research Agenda (NORA) index"April 2011."Also available via the World Wide Web as an Acrobat .pdf file (1.64 MB, 143 p.)