Assessing ergonomic risks of software: Development of the SEAT

Peres, S. Camille; Mehta, Ranjana K.; Ritchey, Paul

doi:10.1016/j.apergo.2016.09.014

Cited by 11 publications

(3 citation statements)

References 30 publications

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“…Third, at the data analysis level, after validation of the acquired data by using the Kaiser-Meyer-Olkin (KMO) test and the Bartlett test, 43 we applied principal factor extraction to reduce the dimensionality of the measured anthropometric data by projecting them onto a low-dimensional subspace, where each axis (factor) is a linear combination of the initial variables (items). [44][45][46][47] To provide a convenient measurement for users, we only found one representative item from each principal factor, and then used these items for body classification. Finally, the K-means clustering method 48,49 was used to classify each body part, in which the number of classes or clusters was determined using analysis of variance (ANOVA).…”

Section: Overview Of the Proposed Modeling Proceduresmentioning

confidence: 99%

A new parametric 3D human body modeling approach by using key position labeling and body parts segmentation

Cheng

Zeng

Bruniaux

et al. 2022

Textile Research Journal

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The current three-dimensional human models used in the apparel industry are mostly rigid and lack semantic information on body positions and body parts. Therefore, it is difficult for designers to make accurate, fast and effective designs from these models. This paper proposes a new parametric three-dimensional human body model based on key position labeling and optimized body parts segmentation. First, by using experts’ professional knowledge, we manually realize accurate human body data measurements as well as their interpretation and classification, and extract relevant human body features. After deep analysis, measured data irrelevant to body shape have been excluded by designers. Furthermore, the relation between body shapes and body features have been modeled. Second, based on this relational model, we label key positions on the corresponding three-dimensional body model obtained by scanning and segmenting the whole three-dimensional human body into semantically interpretable body parts. In this way, two databases have been created, enabling us to identify features of all segmented body parts, whose combination corresponds to the whole body shape. Third, for a specific consumer, his/her personalized three-dimensional human model can be obtained by taking a very few number of body measurements on himself/herself, making an appropriate combination of the identified body parts, and adjusting parameters of all involved body parts. By comparing the proposed labeled and segmented three-dimensional human model and the existing human models through a number of experiments, the proposed model leads to more relevant results with high accuracy and high visual quality related to real human body shapes.

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Section: Overview Of the Proposed Modeling Proceduresmentioning

confidence: 99%

A new parametric 3D human body modeling approach by using key position labeling and body parts segmentation

Cheng

Zeng

Bruniaux

et al. 2022

Textile Research Journal

View full text Add to dashboard Cite

show abstract

“…Understanding of anthropometric characteristics for the complex and diverse shapes of the external ears of different user populations is needed for optimizing ergonomic design. Further, the categorization of measurements is considered as an effective method to determine the factors associated with human body shapes and ergonomic risks for design, and to simplify the process of data matching for different types of products (Ball, 2011;Lacko et al, 2017;Peres et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Anthropometric Characteristics of Chinese Auricles for Ergonomic Design

Wang

Fan

Harris

et al. 2019

Proceedings of the Human Factors and Ergonomics Society Annual

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With the increased demand of auricular measurements for application in ergonomics, clinical diagnosis and identity recognition, the need for comprehensive and new auricular measurements is rising. Similarly, the design forms of ear-related wearable products vary with new functions. Ergonomic design refers to designing for humans; accordingly, designing ear-related wearable products requires anthropometric characteristics of human ears. However, despite the large need, anthropometric characteristics of the Chinese population is lacking. Thus, most ear-related product manufacturers in China make their products following different standards, which can lead to poor fit, discomfort and poor performance of ear-related products. Therefore, the purpose of this study was to provide summarized anthropometric characteristics about Chinese auricles and determine distinct factors which were associated with the variation of auricular shape.

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“…of measurements is an effective method to associate body shapes with different types of products [12][13][14] , including principal component analysis 15 , clustering analysis [16][17][18][19] , and so on. These methods were used for generating the sizing system of products [15][16][17][18][19][20][21][22] .…”

mentioning

confidence: 99%

An earphone fit deviation analysis algorithm

Yan

Liu

Wang

2023

Sci Rep

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This study provides an accurate method for evaluating the fit of earphones, which could be used for establishing a linkage between interference/gap values with human perception. Seven commercial CAD software tools stood out and were explored for the analysis of the deviation between earphone and ear. However, the current deviation analysis method remains to be improved for earphone fit evaluation due to excessive points in the calculation (Geomagic Wrap and Siemens NX), lack of value on interference (Geomagic Control X), computation boundary required (Rapidform XOR/Redesign), repetitive computation with same points and inclined calculation line segment or even invalid calculation (Solidworks, Creo). Therefore, an accurate deviation analysis algorithm was promoted, which calculated the deviation between earphone and ear exactly and classified the interference set and gap set precisely. There are five main procedures of this algorithm, which are point cloud model pre-processing, the generation of distance vectors, the discrimination of interference set and gap set, the discrimination of validity, and statistical analysis and visualization. Furthermore, the usability and validity of the deviation analysis algorithm were verified through statistical analysis and comparing visual effects based on the earphone-wearing experiment. It is certified that the deviation analysis algorithm is appropriate for earphone fit evaluation and the eight indexes of this algorithm were proved to be related to subjective comfort scores. It is meaningful for ear-worn product fit analysis, design, and development phases.

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Assessing ergonomic risks of software: Development of the SEAT

Cited by 11 publications

References 30 publications

A new parametric 3D human body modeling approach by using key position labeling and body parts segmentation

A new parametric 3D human body modeling approach by using key position labeling and body parts segmentation

Anthropometric Characteristics of Chinese Auricles for Ergonomic Design

An earphone fit deviation analysis algorithm

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