Skip to main content

Estimating Anthropometric Measurements of Algerian Students with Microsoft Kinect

  • Conference paper
  • First Online:
Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) (IEA 2018)

Abstract

Ergonomics aims at fitting the job to the man. Anthropometry supports ergonomics to achieve this aim. The design or redesign of workplaces, machines, and tools can be done successfully through anthropometry. Therefore, the measurement of anthropometric dimensions is highly necessary for ergonomic practices.

Currently, the main concern of ergonomists is the search for tools that enable taking measurements reliably, efficiently and inexpensively. The use of traditional anthropometry has been criticized for being time consuming, expensive, and requires skilled personnel. Ergonomists have found their place in 3D scanners. Despite the fact that with 3D scanners, anthropometric surveys are done faster with quicker results, greater accuracy and minimum errors, they are costly and many institutions in developing countries cannot afford to buy them. In addition, their maintenance is another burden on these institutions to obtain them. It may be wise to seek a compromise between the two types of anthropometry. Motion capture interactive entertainment tools like Kinect show some promise in anthropometry. In comparison to other devices, it is affordable as it can be purchased for about 200$. Further, it is light, easy to use, and can be interfaced with computer Microsoft Windows Operating Systems.

The results obtained in this study using Kinect showed that they did not differ in accuracy from those obtained using conventional anthropometry. Therefore, researchers have been urged to use this device in research and to keep in mind continuously developing it.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Simmons KP (2001) Body measurement techniques: a comparison of three-dimensional body scanning and physical anthropometric methods. Ph.D. thesis Submitted to the TTM Graduate Faculty College of Textiles, North Carolina State University, North Carolina, USA

    Google Scholar 

  2. Meunier P, Yin S (2000) Performance of a 2D image-based anthropometric measurement and clothing sizing system. Appl Ergon 31(5):445–451

    Article  Google Scholar 

  3. Rogers MS, Barr AB, Kasemsontitum B, Rempel DM (2008) A three-dimensional anthropometric solid model of the hand based on landmark measurements. Ergonomics 51(4):511–526

    Article  Google Scholar 

  4. De Miguel-Etayo P, Mesana MI, Cardon G, De Bourdeaudhuij I, Góźdź M, Socha P, Lateva M, Iotova V, Koletzko BV, Duvinage K, Androutsos O (2014) Reliability of anthropometric measurements in European preschool children: the ToyBox-study. Obes Rev 15:67–73

    Article  Google Scholar 

  5. Akbarnejad F, Osqueizadeh R, Mokhtarinia HR, Jafarpisheh AS (2017) A novel technique for rapid-accurate 2D hand anthropometry. Iran J Public Health 46(6):865–866

    Google Scholar 

  6. Brooke-Wavell K, Jones PR, West GM (1994) Reliability and repeatability of 3-D body scanner (LASS) measurements compared to anthropometry. Ann Hum Biol 21:571–577

    Article  Google Scholar 

  7. Daniell N, Olds T, Tomkinson G (2010) The importance of site location for girth measurements. J Sports Sci 28:751–757

    Article  Google Scholar 

  8. Microsoft Kinect. http://www.xbox.com/kinect. Accessed 22 Aug 2018

  9. Fernandez-Baena A, Susin A, Xavier Lligadas X (2012) Biomechanical validation of upper-body and lower-body joint movements of Kinect motion capture data for rehabilitation treatments. In: Proceedings of 4th international conference on intelligent networking and collaborative systems (INCoS), Bucharest, Romania, 19–21 September 2012, pp 656–661

    Google Scholar 

  10. Weiss A, Hirshberg D, Black MJ (2011) Home 3D body scans from noisy image and range data. In: Proceedings of IEEE international conference on computer vision (ICCV), Barcelona, Spain, 6–13 November 2011, pp 1951–1958

    Google Scholar 

  11. Braganca S, Carvalho M, Xu B, Arezes P, Ashdown S (2014) A validation study of a Kinect based body imaging (KBI) device system based on ISO 20685:2010. In: 5th international conference on 3D body scanning technologies, Lugano, Switzerland, 21–22 October 2014, pp 372–377

    Google Scholar 

  12. Osbourne B (2013) The efficacy of traditional and digitally-derived anthropometry among black women. MA thesis presented to the College of Fine Arts. The University of Florida, Florida, USA

    Google Scholar 

  13. Domingues A, Barbosa F, Pereira EM, Borgonovo Santos M, Seixas A, Vilas-Boas J, Gabriel J, Vardasca R (2016) Towards a detailed anthropometric body characterization using the Microsoft Kinect. Technol Health Care 24:251–265

    Article  Google Scholar 

  14. Braganca S, Arezes P, Carvalho M, Ashdown SP, Castellucci I, Leao C (2018) A comparison of manual anthropometric measurements with Kinect-based scanned measurements in terms of precision and reliability. Work 59:325–339

    Article  Google Scholar 

  15. Groves R, Fowler F, Couper M, Lepkowski J, Singer E, Tourangeau R (2004) Survey methodology. Wiley, Hoboken

    MATH  Google Scholar 

  16. Ministere de l’Enseignement Supérieur et de la Recherche Scientifique (MESRS). https://www.mesrs.dz/. Accessed 22 Apr 2018

  17. Pheasant S (1996) Bodyspace, 2nd edn. Taylor & Francis, London

    Google Scholar 

  18. Hertzberg HTE (1968) The conference on standardization of anthropometric techniques and terminology. Am J Phys Anthropol 28(1):1–16

    Article  Google Scholar 

  19. Wright U, Govindaraju M, Mital A (1997) Reach profiles of men and women 65 to 89 years of age. Exp Aging Res 23:369–395

    Article  Google Scholar 

  20. Roebuck J (1995) Anthropometric methods: designing to fit the human body. Human Factors and Ergonomics Society, Santa Monica

    Google Scholar 

  21. Smith S, Norris B, Peebles L (2000) Older adult data: the handbook of measurements and capabilities of the older adult. Institute for Occupational Ergonomics, Nottingham

    Google Scholar 

  22. Mony PK, Swaminathan S, Gajendran JK, Vaz M (2016) Quality assurance for accuracy of anthropometric measurements in clinical and epidemiological studies: [Errare humanum est = to err is human]. Indian J Community Med 41(2):98–102

    Article  Google Scholar 

  23. Espitia-Contreras A, Sánchez-Caiman P, Uribe-Quevedo A (2014) Development of a Kinect-based anthropometric measurement application. In: Coquillart S, Kiyokawa K, Swan JE, Bowman D (eds) International conference on virtual reality (VR). IEEE, New York, USA, pp 71–72

    Google Scholar 

  24. Chiu CY, Fawkner S, Coleman S, Sanders R (2016) Automatic calculation of personal body segment parameters with a Microsoft Kinect device. In: Michiyoshi A, Yasushi E, Norihisa F, Hideki T (eds) Proceedings of the 34th international conference of biomechanics in sport, Tsukuba, Japan, 18–22 July 2016, pp 35–38

    Google Scholar 

  25. Robinson M, Parkinson MB (2013) Estimating anthropometry with Microsoft Kinect. In: 2nd international digital human modeling symposium, 11–13 June 2013. The University of Michigan, Ann Arbor, pp 1–7

    Google Scholar 

  26. Qutubuddin SM, Hebbal SS, Kumar ACS (2012) Significance of anthropometric data for the manufacturing organizations. Int J Eng Res Ind Appl (IJERIA) 5(I):111–126

    Google Scholar 

  27. Mobini A, Behzadipour S, Foumani MS (2014) Accuracy of Kinect’s skeleton tracking for upper body rehabilitation applications. Disabil Rehabil Assistive Technol 9(4):344–352

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the researchers (A. Borji, F. Z. Douar and Z. Nemiche) from the Laboratory of Ergonomics and Risks’ Prevention, University of Oran 2, who actively participated in the anthropometric data collection.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohamed Mokdad .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Mokdad, M., Mokdad, I., Bouhafs, M., Lahcene, B. (2019). Estimating Anthropometric Measurements of Algerian Students with Microsoft Kinect. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 826. Springer, Cham. https://doi.org/10.1007/978-3-319-96065-4_54

Download citation

Publish with us

Policies and ethics