• Korean Journal of Computational Design and Engineering
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• v.16 no.6
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• pp.424-436
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• 2011

In this paper, we propose a methodology of generating a parametric segment model for human body using the Korean anthropometric data. The model is defined as an articulated body model consisted with 19 ellipsoid primitives. The primitives are joined at locations representing the physical joints of human body. A lot of previous researches have suggested methodologies of generating body models using the European or American anthropometric data, so that these models were inappropriate for engineering analyses and simulations in case of the Koreans. We defined a set of 35 body dimensions representing our segment model based on the anthropometric data of Koreans. Also we defined four key parameters of age, height, weight and waist circumference, and then we applied regression equations to associate the parameters to the aforementioned dimensions. As the results, we obtained the parametric human body segment models according to the various body types and the subject-specific models for a specific individual. The models in the various industries can be used as the base models for static and dynamic analysis considering the Koreans.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.73-78
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• 2021

As interest in beauty has increased, various studies have been conducted, and related companies have considered the anthropometric data handled between humans and interfaces as an important factor. However, owing to the nature of 3D human body scanners used to extract anthropometric data, it is difficult to accurately analyze a user's body shape until a service is provided because the user only scans and extracts data. To solve this problem, the body shape of several users was analyzed, and the collected anthropometric data were obtained using a 3D human body scanner. After processing the extracted data and the anthropometric data, a custom deep learning model was designed, the designed model was learned, and the user's body shape information was predicted to provide a service suitable for the body shape. Through this approach, it is expected that the user's body shape information can be predicted using a 3D human body scanner, based upon which a beauty service can be provide.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.213-220
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• 2002

Anthropometric survey is important as a basis for human engineering fields. According to our experiences, there are difficulties in obtaining the measurements of some body parts because respondents are reluctant to expose. In order to overcome these difficulties, we propose a method for estimating such hard-to-measure measurements by using easy-to-measure measurements those are closely related to them. Multiple Regression Model, Feedforward Neural Network(FNN) Model and Projection Pursuit Regression(PPR) Model will be used as analytical tools for this purpose. The method we propose will be illustrated with real data from the 1992 Korea national anthropometric survey.

• Journal of the Ergonomics Society of Korea
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• v.22 no.4
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• pp.59-78
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• 2003

Most regression models of anthropometric variables use stature and/or weight as regressors; however, these 'flat' regression models result in large errors for anthropometric variables having low correlations with the regressors. To develop more accurate regression models for anthropometric variables, this study proposed a method to estimate anthropometric variables in a hierarchical manner based on the relationships among the variables and a process to develop and improve corresponding regression models. By applying the proposed approach, a hierarchical estimation structure was constructed for 59 anthropometric variables selected for the occupant package design of a passenger car and corresponding regression models were developed with the 1988 US Army anthropometric survey data. The hierarchical regression models were compared with the corresponding flat regression models in terms of accuracy. As results, the standard errors of the hierarchical regression models decreased by 28% (4.3mm) on average compared with those of the flat models.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.1-7
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• 2015

As a measure of health, the percentage of body fat has been utilized for many ergonomist, physician, athletic trainers, and work physiologists. Underwater weighing procedure for measuring the percentage of body fat is popular and accurate. However, it is relatively expensive, difficult to perform and requires large space. Anthropometric techniques can be utilized to predict the percentage of body fat in the field setting because they are easy to implement and require little space. In this concern, the purpose of this study was to find a regression model to easily predict the percentage of body fat using the anthropometric circumference measurements as predictor variables. In this study, the data for 10 anthropometric circumference measurements for 252 men were analyzed. A full model with ten predictor variables was constructed based on subjective knowledge and literature. The linear regression modeling consists of variable selection and various assumptions regarding the anticipated model. All possible regression models and the assumptions are evaluated using various statistical methods. Based on the evaluation, a reduced model was selected with five predictor variables to predict the percentage of body fat. The model is : % Body Fat = 2.704-0.601 (Neck Circumference) + 0.974 (Abdominal Circumference) -0.332 (Hip Circumference) + 0.409 (Arm Circumference) - 1.618 (Wrist Circumference) + $\epsilon$. This model can be used to estimate the percentage of body fat using only a tape measure.

• Journal of the Ergonomics Society of Korea
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• v.12 no.2
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• pp.63-83
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• 1993

The primary objective of the research is to develop a mathematical method to incorporate the variability of anthropometric body dimensions and joint strengths of individuals in a biomechanical analysis. A multivariate normal simulation model estimated anthropometric body dimensions and joint strengths of the random link-person, based on the assumptions that the vari- ables of body dimensions and joint strengths are correlated and follow normal distributions. Statistical comparative analysis demonstrated that the random link-person represented a more realistic human-like form in an anthropometric sense than the proportional link-person whose body dimensions were estimated proportionally. Estimated joint strengths for the random link-person, however, did not match the measured joint strengths as closely as the estimated body dimensions. The random link-person will allow biomechanical analysis of manual materials handling tasks to be individualized with respect to the anthropometry and a static strength.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1278-1282
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• 2005

Air mattress is now used widely to prevent the pressure ulcer by reducing the localized pressure peaks. In this paper an air-cell mattress and its pressure control method based on an approximate anthropometric model are presented. The air-cell mattress has eighteen cylindrical air cells made of porous material allowing air leakage to contribute in reducing the development of pressure ulcer by lowering the pressure peak, temperature and humidity. To determine an optimal air-cell pressure appropriate for each user, we divide the parts of the body into four sections such as head, trunk, hip, and leg. Then, the pressure of each section is independently calculated from the weight of each part based on the individual body height and weight and the approximate anthropometric model. Air supply system for the air-cell mattress is implemented by using four electronic solenoid valves and an air compressor, and it is driven by a real-time micro-controller. The experimental results with seven subjects shows that the proposed air-cell mattress is effective for the prevention of the pressure ulcer.

• Journal of Physiology & Pathology in Korean Medicine
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• v.20 no.1
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• pp.268-272
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• 2006

In this study, when physician make a diagnosis of Sasang constitution of patients, anthropometric data are applied to seek the classification function into Sasang constitution. Data used in the analysis are the anthropometric data of 550 patients who had been treated in nine oriental medical hospital, and our data have no missing value in 12 anthropometric variables. In order to improve the accuracy of classification function into Sasang constitution, we consider one method of variable transformation of anthropometric data based on oriental medicine.

• Journal of the Ergonomics Society of Korea
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• v.28 no.2
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• pp.17-26
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• 2009

In this study, anthropometric analysis and usability evaluation for four-wheeled walker were carried out and then ergonomics design guidelines were proposed. In anthropometric analysis, design factors of four-wheeled walker were firstly identified and anthropometric design guidelines were made using Korean human scales. Design suitability for two typical four-wheeled walkers was analyzed in based on anthropometric design guidelines. Usability evaluation for two typical walkers was also performed through observation method and expert evaluation. Several usability problems were identified and design solutions were proposed for the design improvement of four-wheeled walker. Finally a design model of four wheeled walker considering analysis results was proposed.

• Journal of the Ergonomics Society of Korea
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• v.26 no.1
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• pp.103-109
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• 2007

Representative human models (RHMs), a group of digital human models which represent the people of the target population within a designated percentage (e.g., 95%), are used for ergonomic design and evaluation in virtual environments. The present study evaluated the grid approach, a RHM generation method, in terms of accommodation percentage. RHMs generated from the grid approach dramatically decreased the accommodation percentage of the target population as the number of anthropometric dimensions under consideration increased. For example, the accommodation percentages by RHMs generated by the grid approach were 95% for 3 key dimensions (selected among 10 anthropometric dimensions), 45% for 5 dimensions, and 10% for 10 dimensions. A standardized multiple regression analysis found that this decreasing accommodation percentage was caused by low correlations between key dimensions and other dimensions. The accommodation evaluation process used in the present study is applicable to evaluation of other RHM generation methods.