Helmet accommodation analysis using 3D laser scanning

Meunier, Pierre; Tack, David W.; Ricci, A; Bossi, Linda; Angel, Harry

doi:10.1016/s0003-6870(00)00006-5

Cited by 47 publications

(20 citation statements)

References 3 publications

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“…Research on statistical shape models of the human body has made major progress, with over the last decades the seminal work of Allen to establish correspondences (33), construction of the Caesar database (10, 11) and a realm of 3D databases becoming available (13). Applications comprise animations (34,35), apparel (6,36,37), orthopedics (8) and industrial design (7,16,17,38,39). Where in traditional anthropometry, shape is described by a set of 1D measurements using several univariate statistical distributions, SSMs directly describe the whole 3D shape using a single multivariate, high-dimensional distribution.…”

Section: Enriched Statistical Shape Models: From 1d To 3d Anthropometrymentioning

confidence: 99%

A new data structure and workflow for using 3D anthropometry in the design of wearable products

Verwulgen

Lacko

Vleugels

et al. 2018

International Journal of Industrial Ergonomics

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Abstract.The human body is a complex biomechanical system that exhibits many variations. Wearable products should be both functional and comfortable. They require a close and accurate fit to the body of the end-user. Current approaches to design body near products rely on 1D anthropometry and unrealistic manikins, e.g. constructed from simple surfaces such as spheres and cylinders connected by splines. With the uprising of 3D scanning, a myriad of accurate 3D body models becomes available. In this paper we present a framework to use this 3D shape information in the development of wearable products. The key concept that we introduce to achieve this extension, is an enriched shape model: a statistical shape model of the human body that also contains all 1D anthropometric data in it. With enriched shape models, a 3D shape can be parameterized with a given set of anthropometric features. Thus the dense geometric information of an individual's shape can be obtained simply by tuning that individual's anthropometric values. By designing on the generated 3D surface, a product can be obtained that closely fits the individual's shape. We thus extend the method of linking 1D anthropometric data with the dimensions of a product. This results in three design strategies that link both body shape with product geometry: design for collective fit, design for fit within clusters and design for individual fit. Each strategy is explained and studied with the design of wearable EEG headsets that fits the human head. KeywordsMass-customization, EEG headsets, CAD, parameterized design, 3D anthropometry, statistical shape models Relevance to Design PracticeWe present a workflow to use accurate 3D shape models of the human body in the design of products that should closely fit the end-user. To that end, we introduce enriched shape models: a new data structure that contains all dense geometric shape information together with classical anthropometric data. We illustrate how enriched shape models can be used to achieve products with personalized fit, as an extension to the use of univariate anthropometric data. The use of enriched shape models for personalized design could become an important driver for mass customization. To that end, tools and techniques should be developed to incorporate the presented workflow in CAD/CAM.

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Section: Enriched Statistical Shape Models: From 1d To 3d Anthropometrymentioning

confidence: 99%

A new data structure and workflow for using 3D anthropometry in the design of wearable products

Verwulgen

Lacko

Vleugels

et al. 2018

International Journal of Industrial Ergonomics

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“…It forms the basis for the SAE International recommended practices (SAE International 2009), which are used for vehicle design. Other examples include Eksioglu (2004), which uses a sample of 12 users to determine the optimum 'grip span' range for hand-held artefacts, such as portable power tools, and Meunier et al (2000), which measures the standoff distance of 30 sample users to determine appropriate dimensions for various sizes of ballistic helmets. Since the use of a population model technique does not require assumptions about user anthropometry or behaviour, variability in the selections of a population that is not attributable to anthropometry may be captured.…”

Section: Population Model Approachesmentioning

confidence: 99%

A comparison of methodologies for designing for human variability

Garneau

Parkinson

2011

Journal of Engineering Design

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In the design of artefacts that interact with people, the spatial dimensions of the user population are often used to size and engineer the artefact. The variability in anthropometry indicates the fixed allocation of space, adjustability requirements, or how many sizes are needed to accommodate the intended user population. Various tools are used to achieve this goal, including boundary manikins, digital human models, prototypes and population models, and hybrid methods that combine the approaches. The present work explores each of these and their relative strengths and weaknesses. This is done in the context of a univariate case study involving the adjustability requirements of a stationary bicycle.

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“…3D anthropometry surveys, such as the CAESAR project [7], can provide tremendous amount of shape information. Researchers have utilized 3D anthropometric data in the design of helmet [8], human-harness [9] and hand tools [10], etc. However, few studies have been reported regarding the effects of the selection of alignment methods on 3D anthropometric shape comparison.…”

Section: Introductionmentioning

confidence: 99%

Alignment Influence on 3D Anthropometric Data Clustering

Niu¹,

Li²,

Salvendy³

2008

TOERGJ

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Shape analysis and comparison is important to sizing system for the design of many products which require close fitting contact with the human body. However, the choice of the alignment reference can profoundly influence the shape analytical results. The objective of this case study is to demonstrate that the statistical results of the threedimensional (3D) upper heads could be different if different alignment approaches are used for the data analysis. Taking a data set of 432 upper heads as an example, this paper addressed the influence on data analysis of two alignment approaches, i.e., aligned at the centroid and aligned at the head top. K-means clustering was applied on block-based distance vectors of the upper head samples to classify the population into categories based on their shapes. Cluster membership variation of different alignment methods was examined. Results indicated that the reference can greatly influence k-means clustering results of 3D anthropometric data. Thus, alignment reference should be carefully chosen according to the specific requirements of an application.

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Helmet accommodation analysis using 3D laser scanning

Cited by 47 publications

References 3 publications

A new data structure and workflow for using 3D anthropometry in the design of wearable products

A new data structure and workflow for using 3D anthropometry in the design of wearable products

A comparison of methodologies for designing for human variability

Alignment Influence on 3D Anthropometric Data Clustering

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