Towards Parametric Modelling of Skin Cancer Risk: Estimation of Body Surface Area Covered by Protective Clothing Using Base Mesh Modelling

  • Leyde Briceno
  • Simone Harrison
  • Gunther Paul
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 822)


The accumulated exposure to ultra-violet radiation creates an occupational and public health risk, and is carcinogenic to humans. The body surface area coverage by clothing (BSAC) contributes to skin cancer risk, and is a requirement in international standards on sun protective clothing, such as AS/NZS 4399:2017. BSAC is usually calculated utilising human subjects or physical mannequins using coating methods, indirect methods or direct measurements estimating the fraction of body covered. These methods are laborious and inflexible, and do not support computer based apparel design. To obtain a simpler, process integrated method, we determine the proportion of exposed body surface area using variable digital human models as virtual subjects, and image processing tools. Parametric, neutral posture human bodies of varying body stature, weight and age, including females and males, were generated in MakeHuman v1.1.1, and a protective clothing mesh, covering the minimum BSA specified in AS/NZS 4399:2017 was added. The MakeHuman definition of a human is based on fuzzy logic, with the main parameters normalised, and linked in a non-linear relation. The Whole Body Surface Area (WBSA) and the BSAC were obtained employing MeshLab, integrating elements on the respective surfaces, which were processed to improve precision. A procedure was developed to control geometric inconsistencies between the body base mesh and the clothing mesh. Thus different representative, generalized groups of subjects were analysed to explore BSAC. The method assists in the evaluation of exposed body areas in a wider spectrum of different occupations with their respective typical protective clothing conditions.


Digital human modelling (DHM) Body surface area coverage by clothing (BSAC) Skin cancer MakeHuman 


  1. 1.
    International Agency for Research on Cancer, World Health Organization (1992) IARC monograph on the evaluation of carcinogenic risks to human: Solar and ultraviolet Radiation, Lyon, vol 55Google Scholar
  2. 2.
    Lucas R, McMichael A, Smith W, Armstrong BK (2006) Solar ultraviolet radiation: global burden of disease from solar ultraviolet radiation. In: Prüss-Üstün A, Zeeb H, Mathers C, Repacholi M (eds) Environmental burden of disease series no. 13. World Health Organization, GenevaGoogle Scholar
  3. 3.
    Doran CM, Ling R, Byrnes J, Crane M, Searles A, Perez D, Shakeshaft A (2015) Estimating the economic costs of skin cancer in New South Wales, Australia. BMC Public Health 1(15):952CrossRefGoogle Scholar
  4. 4.
    Armstrong BK, Kricker A (1993) How much melanoma is caused by sun exposure? Melanoma Res 3:395–401CrossRefGoogle Scholar
  5. 5.
    Holman CDJ, Armstrong BK (1984) Cutaneous malignant melanoma and indicators of total accumulated exposure to the sun: an analysis separating histogenic types. J Natl Cancer Inst 73:75–82Google Scholar
  6. 6.
    Harrison SL, MacLennan R, Speare R, Wronski I (1994) Sun exposure and melanocytic naevi in young Australian children. Lancet 344:1529–1532CrossRefGoogle Scholar
  7. 7.
    Harrison SL, Downs N (2015) Development of a reproducible rating system for sun protective clothing that incorporates body surface coverage. World J Eng Technol 3:208–214CrossRefGoogle Scholar
  8. 8.
    Harrison SL, Buettner PG, MacLennan R (2005) The North Queensland sun-safe clothing study: design and baseline results of a randomized trial to determine the effectiveness of sun-protective clothing in preventing melanocytic nevi. Am J Epidemiol 161:536–545CrossRefGoogle Scholar
  9. 9.
    Harrison SL, Buettner PG, MacLennan R, Woosnam J, Hutton L, Nowak M (2010) Sun-safe clothing helps to prevent the development of pigmented moles—results of a randomised control trial in young Australian children. Ann ACTM 11:49–50Google Scholar
  10. 10.
    Gies HP, Roy CR, Elliott G, Zongli W (1994) Ultraviolet radiation protection factors for clothing. Health Phys 67:131–139CrossRefGoogle Scholar
  11. 11.
    Standards Australia/Standards New Zealand (1996) AS/NZS 4399:1996 sun protective clothing—evaluation and classification. Standards Australia, Sydney and Standards New Zealand, WellingtonGoogle Scholar
  12. 12.
    The British Standards Institution: BS 7949:1999 Children’s clothing. Requirements for protection against erythemally weighted solar ultraviolet radiation (1999). Accessed April 2018
  13. 13.
    European Committee for Standardization CSN EN 13758-2 + A1 Textiles—solar UV protective properties—Part 2: classification and marking of apparel (2003). Accessed April 2018
  14. 14.
    American Association of Textile Chemists and Colorists: AATCC TM183-2014 Transmittance or Blocking of Erythemally Weighted Ultraviolet Radiation through Fabrics (2014). Accessed April 2018
  15. 15.
    American Society for Testing and Materials: ASTM D6603-12 standard specification for labeling of UV-protective textiles (2012). Accessed April 2018
  16. 16.
    Standards Australia: AS/NZS 4399:2017 sun protective clothing—evaluation and classification (2017). Accessed April 2018
  17. 17.
    Downs NJ, Harrison SL (2018) A comprehensive approach to evaluating and classifying sun-protective clothing. Br J Dermatol 178:958–964CrossRefGoogle Scholar
  18. 18.
    Bastioni M, Re S, Misra S (2008) Ideas and methods for modeling 3D human figures: The principal algorithms used by MakeHuman and their implementation in a new approach to parametric modeling. In: Proceedings of the 1st Bangalore annual compute conference. COMPUTE’08. ACM, New York, pp 10:1–10:6. Accessed April 2018
  19. 19.
    Fryar CD, Gu Q, Ogden CL, Flegal KM (2016) Anthropometric reference data for children and adults: United States, 2011–2014. National Center for Health Statistics. Vital Health Stat 3(39). Accessed April 2018
  20. 20.
    Cignoni P, Callieri M, Corsini M, Dellepiane M, Ganovelli F, Ranzuglia G (2008) MeshLab: an open-source mesh processing tool. In: Sixth eurographics Italian chapter conference, pp 129–136. Accessed April 2018
  21. 21.
    Venables WN, Smith DM (2018) R Core Team: an introduction to R. notes on R: a programming environment for data analysis and graphics. Version 3.4.4. R Foundation. Accessed April 2018
  22. 22.
    Lee J, Choi J (2009) Estimation of regional body surface area covered by clothing. J Hum Environ Syst 12(1):35–45CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Leyde Briceno
    • 1
    • 2
  • Simone Harrison
    • 3
    • 4
  • Gunther Paul
    • 1
    • 2
  1. 1.AITHMJames Cook UniversityTownsvilleAustralia
  2. 2.Mackay Institute of Research and InnovationMackayAustralia
  3. 3.Skin Cancer Research Unit, College of Public Health, Medical and Veterinary SciencesJames Cook UniversityTownsvilleAustralia
  4. 4.UV Radiation Group, School of Agricultural, Computational and Environmental SciencesUniversity of Southern QueenslandToowoombaAustralia

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