Relevant bibliographies by topics / Anthropometric data

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Anthropometric data'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "Anthropometric data"

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Tiit, Ene-Margit. "Creation and revitalization of the Estonian National Register of anthropometric data." Papers on Anthropology 25, no. 2 (December 21, 2016): 70. http://dx.doi.org/10.12697/poa.2016.25.2.07.

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Anthropmetric data have always been of interest for scientists. They have also great practical value for different groups of people: tailors, designers and also health care specialists. Anthropological data are different in different geographical areas and also change in time. That is why it is important to save also results of older anthropometrical measurements. In Estonia the anthropometrical measurements have been made by different researchers since the 18th century. The Group of Physical Anthropology at the University of Tartu (initiated by prof Helje Kaarma) was especially active in gathering anthropometric data. The data were saved in the Anthropometic Register. Unfortunately, the register had no financial support and so its activities stopped. In summer 2016 the group of people interested in saving the historical anthropometric data started revitalising the Register of Anthropological Data. Hopefully, it will be possible to use the Estonian Social Science Data Archive for this purpose.
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Dāboliņa, Inga, Ausma Viļumsone, and Eva Lapkovska. "ANTHROPOMETRIC PARAMETRIZATION OF UNIFORMS FOR ARMED FORCES." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 3 (June 15, 2017): 41. http://dx.doi.org/10.17770/etr2017vol3.2519.

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Planning manufacture of uniforms decisions must be taken as to how many and in what size a particular model series should be manufactured, how they should be labeled and to what body-dimensions garment sizes should correspond. The purpose of anthropometric parametrization is to introduce garment size classification for mass production clothing, so as to representatively depict wearers’ body figure diversity. It is in the interests of manufacturers (design time and costs, logistics etc.) and buyers/procurement service alike to confine themselves with a minimum garment sizes and to use a possibly less complicated garment size classification. The aim of this research is to gather different impact factors for anthropometric parametrization for Uniforms of Armed Forces. Research is formed from anthropometric data and end user survey exploring data set of 150 soldiers. Anthropometrics are performed by non-contact anthropometric methods (3D anthropometrical scanner Vitus Smart XXL® is used in the study), data processing automation systems, pattern making CAD/CAM systems, etc. National Armed Forces (NAF) technical specification provides for manufacture of a wide range of garment sizes (by height indifference interval of 6 cm). Manufacturers labeling system and charts of finished products are subjected to comparative analysis and evaluation of corresponding standard recommendations is included. The study indicates the need to optimize the currently used anthropometry method in the Latvian Army, anthropometric data registration and application, thus improving the performance of military personnel and the procurement process and the use of resources, thus promoting resource planning and environmental protection. Also improvements are needed in uniform labeling and instructing of the military personnel on selection of uniform and equipment components. Proper anthropometric parametrization and labeling of Uniforms for Armed Forces would minimize expenses of Uniforms as well as the negative waste impact to the environment.
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Kinghorn, Rhonda A., and Alvah C. Bittner. "Truck Driver Anthropometric Data: Estimating the Current Population." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 37, no. 9 (October 1993): 580–84. http://dx.doi.org/10.1177/154193129303700914.

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This report shows that a challenge facing designers of commercial trucks and other vehicles is a lack of current operator anthropometric data on which to base design decisions. Specifically, it was points out that current data suffer from a number of limitations including secular size changes, ethnic and gender composition shifts, and excessive standard errors (S.E.) of percentiles estimates. These and other limitations point out the need for estimates of contemporary, professional driver anthropometry. This report presents tabulations of comprehensive male and female driver population anthropometry estimates, and outlines a method for applying these anthropometric data to the design of trucks and other vehicles.
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Erkan, Ilker. "A system proposal for rapid detecting of anthropometric data and affecting design strategies." Journal of Engineering, Design and Technology 18, no. 6 (March 27, 2020): 1793–822. http://dx.doi.org/10.1108/jedt-11-2019-0302.

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Purpose The purpose of this study on architecture, design, ergonomics and anthropometry was to ensure compliance with the human-machine-work environment, minimize human error and obtain anthropometric measurements accurately, safely and rapidly. Design/methodology/approach The developed system efficiently extracted anthropometric data for 15,243 individuals with an accuracy rate of 98.8 per cent, focusing on the values for “shoulder breath” and “body depth.” In this study, a new anthropometric measurement system was developed and subsequently applied to obtain anthropometric measurements easily and quickly. The effect of the newly collected anthropometric data on the design discipline was evaluated. Findings The findings highlighted the need to update the anthropometric data used in other design studies. In addition to contributing to designing discipline, the updated anthropometric data are considered suitable for use in many different fields. Research limitations/implications The design discipline and related disciplines are expected to take advantage of these measurements. Updating the aforementioned data will also be easier and faster because of the simplicity and affordability of the system. Originality/value This is the first and only such study in Turkey with regard to the up-to-date anthropometric measurements obtained and the size of the database created.
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Shu, Chang, Stefanie Wuhrer, and Pengcheng Xi. "3D anthropometric data processing." International Journal of Human Factors Modelling and Simulation 3, no. 2 (2012): 133. http://dx.doi.org/10.1504/ijhfms.2012.051093.

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Hearps, Stephen J. C. "Self-reported anthropometric data." Canadian Journal of Public Health 101, no. 4 (July 2010): 345. http://dx.doi.org/10.1007/bf03405301.

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Zetli, Sri, Nofriani Fajrah, and Melanda Paramita. "PERBANDINGAN DATA ANTROPOMETRI BERDASARKAN SUKU DI INDONESIA." JURNAL REKAYASA SISTEM INDUSTRI 5, no. 1 (November 15, 2019): 23. http://dx.doi.org/10.33884/jrsi.v5i1.1390.

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Anthropometry is defined as the science of measurement and art in applying human physicalproperties, which is one of the most important factors to consider in designing a product. Productsthat meet ergonomic rules are products that are designed according to the dimensions of the user'sbody. Various factors affect anthropometric data, one of which is ethnicity. Ethnicity is defined as agroup of people identified through ancestral heritage, certain languages and certain cultures.Indonesia has more than 300 different ethnic groups, so it is important to represent anthropometricdata based on ethnicity. Batam City has a heterogeneous community consisting of various tribes andgroups. The dominant tribes include Batak, Javanese, Malay, Minang and Chinese. With the variationin anthropometric size, it is not possible for a design system to adjust to all types of sizes, thereforethere is a need for a database of anthropometric sizes in Indonesia. From the comparative testconducted by Anova testing, all 36 anthropometric with Sig. <α (0.05) which means that there aredifferences in Anthropometric between the five terms. Whereas for differences in AnthropometricBatak and Javanese are 19 same and 17 different, Batak and Malay are 14 same and 22 different,Batak and Minang are 12 same and 24 different, Batak and Chinese are 14 same and 22 different,Java and Malay are 12 same and 24 different, Java and Minang are 12 same and 24 different, Javaand Chinese are 12 same and 24 different, Malay and Minang are 9 same and 27 different, Malay andChinese are 14 same and 22 different, Minang and Chinese are 14 same and 22 different. The resultsof anthropometry obtained based on this research are expected to be a recommendation in thedevelopment of more ergonomic tools for users, especially the people of Indonesia.
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Paquette, Steven, J. David Brantley, Brian D. Corner, Peng Li, and Thomas Oliver. "Automated Extraction of Anthropometric Data from 3D Images." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 38 (July 2000): 727–30. http://dx.doi.org/10.1177/154193120004403811.

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The use of 3D scanning systems for the capture and measurement of human body dimensions is becoming commonplace. While the ability of available scanning systems to record the surface anatomy of the human body is generally regarded as acceptable for most applications, effective use of the images to obtain anthropometric data requires specially developed data extraction software. However, for large data sets, extraction of useful information can be quite time consuming. A major benefit therefore is to possess an automated software program that quickly facilitates the extraction of reliable anthropometric data from 3D scanned images. In this paper the accuracy and variability of two fully automated data extraction systems (Cyberware WB-4 scanner with Natick-Scan software and Hamamatsu BL Scanner with accompanying software) are examined and compared with measurements obtained from traditional anthropometry. In order to remove many confounding variables that living humans introduce during the scanning process, a set of clothing dressforms was chosen as the focus of study. An analysis of the measurement data generally indicates that automated data extraction compares favorably with standard anthropometry for some measurements but requires additional refinement for others.
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Albin, Thomas J. "Combining Very Limited Anthropometric Data." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 57, no. 1 (September 2013): 943–47. http://dx.doi.org/10.1177/1541931213571209.

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Lee, Young Suk, and Sung Heon Shin. "Anthropometric Data Application in Product Design." Japanese journal of ergonomics 40 (2004): 126–27. http://dx.doi.org/10.5100/jje.40.supplement_126.

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Dissertations / Theses on the topic "Anthropometric data"

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Pena, Isis. "Utility-based data mining: An anthropometric case study." Thesis, University of Ottawa (Canada), 2008. http://hdl.handle.net/10393/27723.

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One of the most important challenges for the apparel industry is to produce garments that fit the population properly. In order to achieve this objective, it is crucial to understand the typical profile of consumer's bodies. In this work, we aim to identify the typical consumer from the virtual tailor's perspective. To this end, we perform clustering analysis on anthropometric and 3-D data to group the population into clothing sizes. Next, we perform multi-view relational classification to analyze the interplay of different body measurements within each size. In this study, we analyze three different populations as contained in the CAESAR(TM) database, namely, the American, the Italian and the Dutch populations. Throughout this study, we follow a utility-based data mining approach. The goal of utility-base data mining is to consider all utility aspects of the mining process and to thus maximize the utility of the entire process. In order to address this issue, we engage in dimension reduction techniques to find a smaller set of body measurement that reduces the cost and improves the performance of the mining process. We also apply objective interestingness measures in our analysis of demographic data, to improve the quality of the results and reduce the time and search space of the mining process. The analysis of demographic data allows us to better understand the demographic nature of potential customers, in order to target subgroups of potential customers better.
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Rogers, Nick. "The development of an anthropometric data tool for use in the conceptual design of domestic products." Thesis, Open University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323617.

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Sadetskaya, Katie. "Measuring wellbeing in New Zealand during the 19th - early 20th centuries : a spatial perspective." Thesis, University of Canterbury. Economics, 2014. http://hdl.handle.net/10092/9221.

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The overall objective of this thesis is to compare and contrast alternative measures of wellbeing in New Zealand during the 19th -early 20th centuries from a spatial perspective by collecting, collating and analyzing new economic, social and anthropometric data. Provincial data was collected from the Statistics New Zealand Annual Reports and New Zealand Census. Anthropometric data was derived from the personnel records of New Zealanders serving in WWI, which only became available to the public in 2005. Time-series tests for convergence and causality have been applied to analyze New Zealand’s economic history, where appropriate. The last quarter of the 19th century in New Zealand was a period of rapid change both in terms of economic and demographic indicators. Prior to the universal convergence of the existing monetary-based measures of wellbeing across Provinces, there were some apparent disparities in the commodity price and real wage series, as well as urban-rural differences in occupation-specific real wages and infant mortality trends. There was also no single pattern of stature decline across provinces during 1871-1898, or between urban and rural areas, where disparities were particularly apparent. The traditional view of the healthy and wealthy New Zealand could only be established at an aggregate level, during a certain time period and for a certain ethnic group (New Zealand European only). Using Provincial data for the period 1874-1919 I have been able to show that improvements in real wages and a decrease in education inequality (between females and males) corresponded to lower infant deaths and thus better health outcomes, while increased dwelling density created unfavorable conditions for infants’ chances of survival. Anthropometric data was used in conjunction with socio-economic provincial data to establish the relationship between stature, urbanization, real wages and infant mortality. The results showed that dwelling density (overcrowding) and general economic conditions were both important in determining stature outcomes during 1870-1900, while the effect of infant mortality on stature was negligible. Most importantly, it has been demonstrated that in New Zealand stature represents a much more robust measure of living standards than real wages or health indicators on their own, at least during the 1870-1900 period.
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Dangour, Alan David. "Growth of body proportion in two Amerindian tribes in Guyana." Thesis, University College London (University of London), 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288025.

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Manuel, Melissa Barnes Ulrich Pamela V. Connell Lenda Jo. "Using 3D body scan measurement data and body shape assessment to build anthropometric profiles of tween girls." Auburn, Ala, 2009. http://hdl.handle.net/10415/1585.

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Du, Plessis Daniel Jacobus. "Comparative characteristics of elite New Zealand and South African u/16 rugby-players with reference to game-specific skills, physical abilities and anthropometric data." Diss., Pretoria : [s.n.], 2007. http://upetd.up.ac.za/thesis/available/etd-04302008-085932.

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Williams, Gavin L. "Improving fit through the integration of anthropometric data into a computer aided design and manufacture based design process." Thesis, Loughborough University, 2007. https://dspace.lboro.ac.uk/2134/4328.

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For all types of clothing and body worn technologies it is important to consider how they integrate and interact with the complex shapes that form the unique profile of the human body. This interaction determines the fit of these products and it is often difficult to generate a fit that can simultaneously accommodate these complex shapes. Achieving the correct fit is determined by a number of different factors that must be combined appropriately to create the fit associated with a particular product. This is particularly applicable to Personal Protective Equipment (PPE) to ensure it provides protection while maintaining comfort, mobility and good interaction with the surrounding environment. Integrating suitable anthropometric data into the design and manufacture of this type of clothing plays a critical role in achieving a good fit. By using various processes of Computer Aided Design (CAD) and Computer Aided Manufacture (CAM), the detail contained within these data can be quickly and accurately transferred into physical tools. The aim of this study was to demonstrate and validate a method of enhancing the fit of PPE handwear. This has been achieved through an action research strategy using descriptive and practical research methods. The research tools primarily used are case studies, used to demonstrate how manually collected 2D anthropometric data can be used to generate computer models that represent these data in a 3D form. The products of the case studies are tools that have been introduced into the design and manufacture processes of commercial handwear manufacturing environments. The tools have successfully been used to produce gloves using two different manufacturing methods and been assessed to analyse their fit. An improvement in fit for the gloves has been quantified through user trials to determine the level of increased performance afforded to the wearer. The conclusions drawn from the case studies demonstrate that the integration of anthropometric data and CAD/CAM can greatly influence the fit of handwear and improve the iterative processes of its design. However, the data alone does not achieve this as the added integration of tacit knowledge related to glove design is needed to ensure the correct properties are included to the meet the needs of the target population. The methods developed in the case studies have the potential to be applied to other products where fit and interaction with the human body are important design considerations.
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Bosman, Lise. "A secondary analysis of anthropometric data from the 1999 National Food Consumption Survey, using different growth reference standards." Thesis, Link to the online version, 2008. http://hdl.handle.net/10019/1495.

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Ray, Snehaa. "Assessment of a Nutrition Education Intervention on the Nutrition Knowledge, Attitudes, Beliefs, Habits and Anthropometric Data in Adolescent Academy Male Soccer Players." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1586343005089916.

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Sims, Ruth. "'Design for all' : methods and data to support designers." Thesis, Loughborough University, 2003. https://dspace.lboro.ac.uk/2134/6914.

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If designers are to meet the needs of the growing population of older and disabled people then data on size, shape, posture and capabilities will be increasingly important. This thesis details a methodology for the collection of anthropometry, joint constraints, reach range, postural capability and task specific information, to create a unique database of `individuals'. These data were then used in the development of a computer-based design tool (HADRIAN), to allow design professionals to estimate the percentage of people who could be accommodated by a design. Having complete data sets for individuals is vital to enable multivariate analysis, as opposed to traditional univariate percentile data. Following a review of the literature two interview surveys were conducted with 32 design professionals and 50 older and disabled people. The majority of designers were aware of the philosophy of `design for all', but rarely considered the approach due to perceived time and financial costs. With respect to older and disabled people it was found that nearly all experienced problems completing basic activities of daily life, and that improvements to existing designs could improve quality of life. Activities such as being able to cook a meal, and use the bath were reported as being particularly important. Firstly, a pilot study was conducted with 8 participants to assess the different data collection options. Data were then collected on 100 people, with the majority being older and/or disabled, and encompassing a wide range of capabilities. From these data it was possible to see that the anthropometric data showed a range beyond 15` and 99`h percentile for each dimension when compared to existing anthropometry data, and a breadth of variation in task specific behaviours. Validation trials were then conducted to compare the actual task performance of 10 of the 100 `individuals' with that predicted by HADRIAN, with postures and task capabilities being correctly predicted for open-access reach-and-lift tasks. This gives some confidence that it is possible to predict postures and capabilities from the data collected.
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Books on the topic "Anthropometric data"

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HFES 300 Committee. Guidelines for using anthropometric data in product design. Santa Monica, Calif: Human Factors and Ergonomics Society, 2004.

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J, Kuczmarski Robert, and National Center for Health Statistics (U.S.), eds. Anthropometric data and prevalence of overweight for Hispanics, 1982-84. Hyattsville, Md: U.S. Dept. of Health and Human Services, Public Health Service, Centers for Disease Control, National Center for Health Statistics, 1989.

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Najjar, Matthew F. Anthropometric reference data and prevalence of overweight, United States, 1976-80. Hyattsville, Md: U.S. Dept. of Health and Human Services, Public Health Service, National Center for Health Statistics, 1987.

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D, Fryar Cheryl, Ogden Cynthia L, National Center for Health Statistics (U.S.), and National Health and Nutrition Examination Survey (U.S.), eds. Anthropometric reference data for children and adults: United States, 1988-1994. Hyattsville, Md: U.S. Dept. of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, 2009.

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Kostermans, Kees. Assessing the quality of anthropometric data: Background and illustrated guidelines for survey managers. Washington, D.C: World Bank, 1994.

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Peebles, Laura. Adultdata: The handbook of adult anthropometric and strength measurements : data for design safety. London: Department of Trade and Industry, 1998.

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), National Center for Health Statistics (U S. Anthropometric reference data for children and adults: United States, 2007-2010 : data from the nathional health and nutrition survey. Hyattsville, Md: U.S. Dept. of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, 2012.

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Brainerd, Elizabeth. Reassessing the standard of living in the Soviet Union: An analysis using archival and anthropometric data. Bonn, Germany: IZA, 2006.

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Tassenaar, Vincent. Regional differences in standard of living in the Netherlands, 1800-1875: A study based on anthropometric data. Groningen, Netherlands: Groningen Growth and Development Centre (University of Groningen), 1995.

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Jürgens, Hans W. International data on anthropometry. Geneva: International Labour Office, 1990.

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Book chapters on the topic "Anthropometric data"

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Tosi, Francesca. "The Anthropometric Reference Data." In Springer Series in Design and Innovation, 217–31. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33562-5_11.

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Lee, Kyung-Sun, Myung-Chul Jung, Seung-Min Mo, and Seung Nam Min. "Anthropometric Data for Biomechanical Hand Model." In Advances in Intelligent Systems and Computing, 398–404. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96065-4_45.

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Castellucci, H. I., C. A. Viviani, J. F. M. Molenbroek, P. M. Arezes, M. Martínez, V. Aparici, and S. Bragança. "Anthropometric Data of Chilean Male Workers." In Advances in Intelligent Systems and Computing, 841–49. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96071-5_87.

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Zhang, Fan, Jing Zhao, Chao Zhao, Gang Wu, Wenxing Ding, and Haitao Wang. "Foot Anthropometric Data for Young Chinese Population." In Advances in Ergonomics in Design, 183–89. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94706-8_21.

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Barata, António, Lucília Carvalho, and Francisco M. Couto. "Anthropometric Data Analytics: A Portuguese Case Study." In Advances in Intelligent Systems and Computing, 92–100. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60816-7_12.

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Niu, Jianwei, and Zhizhong Li. "Using Three-Dimensional (3D) Anthropometric Data in Design." In Handbook of Anthropometry, 3001–13. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-1788-1_185.

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Müller-Wille, Staffan. "Data, Meta Data and Pattern Data: How Franz Boas Mobilized Anthropometric Data, 1890 and Beyond." In Data Journeys in the Sciences, 265–83. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37177-7_14.

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Shin, Su-Jeong Hwang, and Mona Maher. "Reliability of Anthropometric Reference Data for Children’s Product Design." In Advances in Intelligent Systems and Computing, 350–57. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20444-0_34.

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Capelassi, Carla, Miguel Carvalho, Raquel Campos, Cristina Kattel, and Bugao Xu. "Segmentation of Anthropometric Data of the Brazilian’ Female Population." In Advances in Ergonomics in Design, 1029–36. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60582-1_104.

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Hernández-Arellano, Juan Luis, Julián Israel Aguilar-Duque, and Karla Gabriela Gómez-Bull. "Methodology to Determine Product Dimensions Based on User Anthropometric Data." In Management and Industrial Engineering, 373–85. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56871-3_18.

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Conference papers on the topic "Anthropometric data"

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Abdali, Osama, Herna Viktor, Eric Paquet, and Marc Rioux. "Exploring Anthropometric Data through Cluster Analysis." In Digital Human Modeling for Design and Engineering Symposium. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2004. http://dx.doi.org/10.4271/2004-01-2187.

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Rothbucher, M., T. Habigt, J. Habigt, T. Riedmaier, and K. Diepold. "Measuring Anthropometric Data for HRTF Personalization." In Internet-Based Systems (SITIS 2010). IEEE, 2010. http://dx.doi.org/10.1109/sitis.2010.27.

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Shaw, Brian E., and Mark S. Sanders. "U.S. Truck Driver Anthropometric and Truck Work Space Data Survey: Demographics and Static Anthropometrics." In 3rd International Pacific Conference on Automotive Engineering (1985). 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1985. http://dx.doi.org/10.4271/852316.

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"Classification of Anthropometric Data using Neural Networks." In 14th International Conference on Enterprise Information Systems. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0004002301160119.

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Pawar, Archana A., D. K. Kamat, and P. M. Patil. "Body composition analysis using various anthropometric equations." In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS). IEEE, 2017. http://dx.doi.org/10.1109/icecds.2017.8390040.

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Xu, Haocan, Jituo Li, Jiaman Li, and Guodong Lu. "Prediction of Anthropometric Data Based on Ladder Network." In 2019 Chinese Automation Congress (CAC). IEEE, 2019. http://dx.doi.org/10.1109/cac48633.2019.8997368.

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GRIFFIN, Linsey, Susan SOKOLOWSKI, and Emily SEIFERT. "Process Considerations in 3D Hand Anthropometric Data Collection." In 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018. Ascona, Switzerland: Hometrica Consulting - Dr. Nicola D'Apuzzo, 2018. http://dx.doi.org/10.15221/18.121.

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GRIFFIN, Linsey, Susan SOKOLOWSKI, and Emily SEIFERT. "Process Considerations in 3D Hand Anthropometric Data Collection." In 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018. Ascona, Switzerland: Hometrica Consulting - Dr. Nicola D'Apuzzo, 2018. http://dx.doi.org/10.15221/18.123.

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SOKOLOWSKI, Susan L., Linsey GRIFFIN, and Sandeep CHANDRASEKHAR. "Current Technology Landscape for Collecting Hand Anthropometric Data." In 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018. Ascona, Switzerland: Hometrica Consulting - Dr. Nicola D'Apuzzo, 2018. http://dx.doi.org/10.15221/18.142.

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Böcker, Martin, Werner Blohm, and Lothar Mühlbach. "Anthropometric data on horizontal head movements in videocommunications." In Conference companion. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/257089.257175.

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Reports on the topic "Anthropometric data"

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Fenlon, Riley. Facial respirator shape analysis using 3D anthropometric data. Gaithersburg, MD: National Institute of Standards and Technology, 2007. http://dx.doi.org/10.6028/nist.ir.7460.

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Juhnke, Bethany, Brad Holschuh, Colleen G. Pokorny, Elisheva Savvateev, Emily Seifert, and Linsey A. Gordon. Validation of the Artec Eva for Hand Anthropometric Data Collection. Ames (Iowa): Iowa State University. Library, January 2019. http://dx.doi.org/10.31274/itaa.8376.

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Clauser, Charles E., John T. McConville, Claire C. Gordon, and Ilse O. Tebbetts. Selection of Dimensions for an Anthropometric Data Base. Volume 2. Dimension Evaluation Sheets. Fort Belvoir, VA: Defense Technical Information Center, May 1986. http://dx.doi.org/10.21236/ada179472.

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Harris, Bernard. Anthropometric history and the measurement of wellbeing. Verlag der Österreichischen Akademie der Wissenschaften, June 2021. http://dx.doi.org/10.1553/populationyearbook2021.rev02.

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Abstract:
It has often been recognised that the average height of a population is influencedby the economic, social and environmental conditions in which it finds itself, andthis insight has inspired a generation of historians to use anthropometric data toinvestigate the health and wellbeing of past populations. This paper reviews someof the main developments in the field, and assesses the extent to which heightremains a viable measure of historical wellbeing. It explores a number of differentissues, including the nature of human growth; the impact of variations in diet andexposure to disease; the role of ethnicity; the relationships between height, mortalityand labour productivity; and the “social value” of human stature. It concludes that,despite certain caveats, height has retained its capacity to act as a “mirror” of theconditions of past societies, and of the wellbeing of their members.
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