Backpropagation Neural Network for Sex Determination from Patella in Forensic Anthropology

  • Iis Afrianty
  • Dewi Nasien
  • Mohammed R. A. Kadir
  • Habibollah Haron
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 279)


Forensic anthropology is a discipline that concerned on postmortem identification from skeletal remains in sex determination. In sex determination, besides empirical techniques such as Discriminant Function Analysis (DFA), Artificial Intelligence techniques such as Artificial Neural Network (ANN) should be considered to get more accurate result. This paper proposes back propagation ANN model for sex determination. By using data and DFA result from previous work, this paper compares the result with the result of ANN model obtained from the experiment. A total sample data of 113 patellae has been generated based on statistics values of previous study. The data is divided into three groups of ages (young, middle, and old) and is measured using three parameters (width, height, and thickness). The ANN model produces average accuracy until 96.1% compared to 92.9% result from DFA technique. This concludes that ANN produces more accurate result in sex determination compared to DFA.


Backpropagation neural network Forensic anthropology Patella Sex determination 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Blau, S., Briggs, C.A.: The role of forensic anthropology in Disaster Victim Identification (DVI). Forensic Sci. Int. 205, 29–35 (2011)CrossRefGoogle Scholar
  2. 2.
    Adebisi, S.S.: Forensic Anthropology In Perspective: The Current Trend. Forensic Sci. Int. 4, 2–2 (2009)Google Scholar
  3. 3.
    Iscan, M.Y., Olivera, H.E.S.: Forensic anthropology in Latin America. Forensic Sci. Int. 109, 15–30 (2000)CrossRefGoogle Scholar
  4. 4.
    Schmitt, E.C.A.J.P.A.: Forensic Anthropology and Medicine: Complementary Sciences From Recovery To Cause of Death. International Journal of Osteoarchaeology, Int. J. Osteoarchaeol. 17, 434–436 (2007)CrossRefGoogle Scholar
  5. 5.
    Vaz, M., Benfica, F.S.: The experience of the Forensic Anthropology Service of the Medical Examiner’s Office in Porto Alegre, Brazil. Forensic Sci. Int. 179, e45–e49 (2008)Google Scholar
  6. 6.
    Mahfouz, M., Badawi, A., Merkl, B., Fatah, E.E., Pritchard, E., Kesler, K., Moore, M., Jantz, R., Jantz, L.: Patella sex determination by 3D statistical shape models and nonlinear classifiers. Forensic Sci. Int. 173, 161–170 (2007)CrossRefGoogle Scholar
  7. 7.
    Gomez-Valdes, J.A., Quinto-Sanchez, M., Menendez Garmendia, A., Veleminska, J., Sanchez-Mejorada, G., Bruzek, J.: Comparison of methods to determine sex by evaluating the greater sciatic notch: Visual, angular and geometric morphometrics. Forensic Sci. Int. 221, 156 (2012)CrossRefGoogle Scholar
  8. 8.
    Koçak, A., Özgür Aktas, E., Ertürk, S., Aktas, S., Yemisçigil, A.: Sex determination from the sternal end of the rib by osteometric analysis. Legal Medicine 5, 100–104 (2003)CrossRefGoogle Scholar
  9. 9.
    Mostafa, E.M., El-Elemi, A.H., El-Beblawy, M.A., Dawood, A.E.-W.A.: Adult sex identification using digital radiographs of the proximal epiphysis of the femur at Suez Canal University Hospital in Ismailia, Egypt. Egyptian Journal of Forensic Sciences 2, 81–88 (2012)CrossRefGoogle Scholar
  10. 10.
    Akhlaghi, M., Sheikhazadi, A., Ebrahimnia, A., Hedayati, M., Nazparvar, B., Saberi Anary, S.H.: The value of radius bone in prediction of sex and height in the Iranian population. J. Forensic Leg. Med. 19, 219–222 (2012)CrossRefGoogle Scholar
  11. 11.
    Cattaneo, C.: Forensic anthropology: developments of a classical discipline in the new millennium. Forensic Sci. Int. 165, 185–193 (2007)CrossRefGoogle Scholar
  12. 12.
    Ogawa, Y., Imaizumi, K., Miyasaka, S., Yoshino, M.: Discriminant functions for sex estimation of modern Japanese skulls. J.Forensic Leg. Med. 20, 234–238 (2012)CrossRefGoogle Scholar
  13. 13.
    Cattaneo, C., Porta, D., De Angelis, D., Gibelli, D., Poppa, P., Grandi, M.: Unidentified bodies and human remains: An Italian glimpse through a European problem. Forensic Sci. Int. 195, 167.e1–167.e6 (2010)Google Scholar
  14. 14.
    Akhlaghi, M., Hajibeygi, M., Zamani, N., Moradi, B.: Estimation of stature from upper limb anthropometry in Iranian population. J. Forensic Leg. Med. 19, 280–284 (2012)CrossRefGoogle Scholar
  15. 15.
    Akhlaghi, M., Sheikhazadi, A., Naghsh, A., Dorvashi, G.: Identification of sex in Iranian population using patella dimensions. J. Forensic Leg. Med. 17, 150–155 (2010)CrossRefGoogle Scholar
  16. 16.
    Akhlaghi, M., Moradi, B., Hajibeygi, M.: Sex determination using anthropometric dimensions of the clavicle in Iranian population. J. Forensic Leg. Med. 19, 381–385 (2012)CrossRefGoogle Scholar
  17. 17.
    Dixit, S.G., Kakar, S., Agarwal, S., Choudhry, R.: Sexing of human hip bones of Indian origin by discriminant function analysis. J. Forensic Leg. Med. 14, 429–435 (2007)CrossRefGoogle Scholar
  18. 18.
    Guyomarc’h, P., Bruzek, J.: Accuracy and reliability in sex determination from skulls: a comparison of Fordisc(R) 3.0 and the discriminant function analysis. Forensic Sci. Int. 208, 180 e1–186 e1 (2011)Google Scholar
  19. 19.
    Hu, K.S., Koh, K.S., Han, S.H., Shin, K.J., Kim, H.J.: Sex determination using nonmetric characteristics of the mandible in Koreans. J. Forensic. Sci. 51, 1376–1382 (2006)CrossRefGoogle Scholar
  20. 20.
    Saini, V., Srivastava, R., Shamal, S.N., Singh, T.B., Pandey, A.K., Tripathi, S.K.: Sex determination using mandibular ramus flexure: a preliminary study on Indian population. J. Forensic Leg. Med. 18, 208–212 (2011)CrossRefGoogle Scholar
  21. 21.
    Papaioannou, V.A., Kranioti, E.F., Joveneaux, P., Nathena, D., Michalodimitrakis, M.: Sexual dimorphism of the scapula and the clavicle in a contemporary Greek population: applications in forensic identification. Forensic Sci. Int. 217, 231 e1–237 e1 (2012)Google Scholar
  22. 22.
    du Jardin, P., Ponsaille, J., Alunni-Perret, V., Quatrehomme, G.: A comparison between neural network and other metric methods to determine sex from the upper femur in a modern French population. Forensic Sci. Int. 192, 127 e1–136 e1 (2009)Google Scholar
  23. 23.
    Harma, A., Karakas, H.M.: Determination of sex from the femur in Anatolian Caucasians: a digital radiological study. J. Forensic Leg. Med. 14, 190–194 (2007)CrossRefGoogle Scholar
  24. 24.
    Purkait, R.: Triangle identified at the proximal end of femur: a new sex determinant. Forensic Sci. Int. 147, 135–139 (2005)CrossRefGoogle Scholar
  25. 25.
    Rissech, C., Schaefer, M., Malgosa, A.: Development of the femur–implications for age and sex determination. Forensic Sci. Int. 180, 1–9 (2008)CrossRefGoogle Scholar
  26. 26.
    Mellit, A., Kalogirou, S.A.: Artificial intelligence techniques for photovoltaic applications: A review. Progress in Energy and Combustion Science 34, 574–632 (2008)CrossRefGoogle Scholar
  27. 27.
    Liang, L., Wu, D.: An application of pattern recognition on scoring Chinese corporations financial conditions based on backpropagation neural network. J. Computers & Operation Research 32, 1115–1129 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Iis Afrianty
    • 1
  • Dewi Nasien
    • 1
  • Mohammed R. A. Kadir
    • 2
  • Habibollah Haron
    • 1
  1. 1.Faculty of ComputingUniversiti Teknologi MalaysiaSkudaiMalaysia
  2. 2.Faculty of BioScience and Medical EngineeringUniversiti Teknologi MalaysiaSkudaiMalaysia

Personalised recommendations