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Three-Dimensional (3-D) Photonic Scanning: A New Approach to Anthropometry

Chapter

Abstract

Anthropometric measurements, such as body mass index (BMI) and body girths have long been used to assess nutritional status in all age groups. Although most such measurements are merely one-dimensional (1-D), they are often used to index body shape. Examples include BMI, waist–hip ratio or waist–height ratio, each of which acts as a proxy for whole-body or regional-body shape. Recently, whole-body photonic scanners developed by the clothing industry have appeared, and offer a new approach to body shape assessment. Although a variety of technologies have been developed, all photonic scanners project light onto the surface of the body, and record the surface topography. Initial data capture provides a ‘point-cloud’, which is then processed using computer algorithms to extract the skin surface topography. Automatic landmark identification then allows an ‘e-tape measure’ to be applied, extracting multiple girths, distances, diameters and two-dimensional (2-D) cross-sectional areas. Current software allows around 200 such measurements to be extracted, making the technique ideal for large anthropometric surveys. However, the major potential of the technique lies in its ability to go beyond 1-D measurements and extract more complex topographical and shape outcomes. The technology offers numerous benefits over traditional approaches, with the digital data facilitating rapid processing and archiving, the application of diverse analytical software programmes, and repeat scans allowing change in shape to be quantified. 3-D scanning has recently been applied in several large National Sizing Surveys, allowing exploration of the associations of age, gender and nutritional status with body dimensions. Validation studies against manual measurements indicate high consistency in ranking individuals compared with manual measurements, but systematic differences in average values, due to differences in the way that the data is obtained. 3-D photonic scanning is easy, quick and cheap to apply, as well as being non-invasive and well-accepted by the majority of adults. The technology offers a novel approach to anthropometry and is likely to be adopted increasingly in large surveys of size, growth, nutritional status and health.

Keywords

Body Mass Index Body Shape Photonic Technology Clothing Industry Waist Girth 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The author is grateful to his long-standing collaborator Professor Philip Treleaven of UCL Department of Computer Science, with whom this research has been carried out.

References

  1. Fernandez JR, Redden DT, Pietrobelli A, Allison DB.J Pediatr. 2004;145:439–44.PubMedCrossRefGoogle Scholar
  2. Ferro-Luzzi A, James WP.Br J Nutr. 1996;75:3–10.PubMedCrossRefGoogle Scholar
  3. Garrow JS, Webster J.Int J Obes. 1985;9:147–53.PubMedGoogle Scholar
  4. Haroun D, Taylor SJC, Viner RM, Hayward RS, Darch TS, Eaton S, Cole TJ, Wells JC.Obesity. 2010;18:1252–59.Google Scholar
  5. Heymsfield SB, Martin-Nguyen A, Fong TM, Gallagher D, Pietrobelli A.Nutr Metab. 2008;5:24.CrossRefGoogle Scholar
  6. Huxley R, Mendis S, Zheleznyakov E, Reddy S, Chan J.Eur J Clin Nutr. 2010;64:16–22.Google Scholar
  7. James WP, Ferro-Luzzi A, Waterlow JC.Eur J Clin Nutr. 1988;42:969–81.PubMedGoogle Scholar
  8. Lee CM, Huxley RR, Wildman RP, Woodward M.J Clin Epidemiol. 2008;61:646–53.PubMedCrossRefGoogle Scholar
  9. Lin JD, Chiou WK, Weng HF, Tsai YH, Liu TH.J Clin Epidemiol. 2002;55:757–66.PubMedCrossRefGoogle Scholar
  10. Mensah GA, Mokdad AH, Ford ES, Greenlund KJ, Croft JB.Circulation. 2005;111:1233–41.PubMedCrossRefGoogle Scholar
  11. Misra A, Vikram NK, Gupta R, Pandey RM, Wasir JS, Gupta VP.Int J Obes. 2006;30:106–11.CrossRefGoogle Scholar
  12. Park YW, Zhu S, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB.Arch Intern Med. 2003;163:427–36.PubMedCrossRefGoogle Scholar
  13. Pierson WR. Ann N Y Acad Sci 1963;110:109–12.PubMedCrossRefGoogle Scholar
  14. Sierra-Johnson J, Johnson BD, Bailey KR, Turner ST.Obes Res. 2004;12:2070–7.PubMedCrossRefGoogle Scholar
  15. Scherzer R, Shen W, Bacchetti P, Kotler D, Lewis CE, Shlipak MG, Heymsfield SB, Grunfeld C.Am J Clin Nutr. 2008;87:1809–17.PubMedGoogle Scholar
  16. Snijder MB, Dekker JM, Visser M, Bouter LM, Stehouwer CD, Kostense PJ, Yudkin JS, Heine RJ, Nijpels G, Seidell JC. Am J Clin Nutr. 2003;77:1192–7.PubMedGoogle Scholar
  17. Snijder MB, Zimmet PZ, Visser M, Dekker JM, Seidell JC, Shaw JE.Obes Res. 2004;12:1370–4.PubMedCrossRefGoogle Scholar
  18. Treleaven P, Wells JC.Computer. 2007;40:28–34.CrossRefGoogle Scholar
  19. Wang J, Gallagher D, Thornton JC, Yu W, Horlick M, Pi-Sunyer FX.Am J Clin Nutr. 2006;83:809–16.PubMedGoogle Scholar
  20. Wang J, Gallagher D, Thornton JC, Yu W, Weil R, Kovac B, Pi-Sunyer FX.Obesity. 2007;15:2688–98.PubMedCrossRefGoogle Scholar
  21. Wells JC. Int J Obes. 2000;24:325–9.CrossRefGoogle Scholar
  22. Wells JC, Fewtrell MS, Williams JE, Haroun D, Lawson MS, Cole TJ.Int J Obes. 2006;30:1506–13.CrossRefGoogle Scholar
  23. Wells JC, Treleaven P, Cole TJ.Am J Clin Nutr. 2007;85:419–25.PubMedGoogle Scholar
  24. Wells JC, Ruto A, Treleaven P.Int J Obes. 2008a;32:232–8.CrossRefGoogle Scholar
  25. Wells JC, Cole TJ, Bruner D, Treleaven P.Int J Obes. 2008b;32:152–9.CrossRefGoogle Scholar
  26. Wells JC, Cole TJ, Treleaven P.Obesity. 2008c;16:435–41.CrossRefGoogle Scholar
  27. Wells JC, Griffin L, Treleaven P.Am J Hum Biol. 2010;22:456–62.Google Scholar
  28. Yusuf S, Hawken S, Ounpuu S, Bautista L, Franzosi MG, Commerford P, Lang CC, Rumboldt Z, Onen CL, Lisheng L, Tanomsup S, Wangai P Jr, Razak F, Sharma AM, Anand SS, Interheart Study Investigators Lancet. 2005;366:1640–9.PubMedCrossRefGoogle Scholar
  29. Zhu S, Heymsfield SB, Toyoshima H, Wang Z, Pietrobelli A, Heshka S.Am J Clin Nutr. 2005;81:409–15.PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Childhood Nutrition Research CentreUCL Institute of Child HealthLondonUK

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