A Novel Non-contact Infection Screening System Based on Self-Organizing Map with K-means Clustering

  • Guanghao Sun
  • Shigeto Abe
  • Osamu Takei
  • Yukiya Hakozaki
  • Takemi Matsui
Part of the Communications in Computer and Information Science book series (CCIS, volume 258)


This paper aims to evaluate the efficacy of our non-contact infection screening system which uses Kohonen’s self-organizing map (SOM) with Kmeans clustering algorithm. In this study, the linear discriminant analysis (LDA) used in our previous system was replaced by SOM with K-means clustering algorithm to increase accuracy. The system simultaneously measures heart rate, respiratory rate, and facial skin temperature. The evaluation was done using the same data which we used in our previous study. The data was based on the test on 57 influenza patients and 35 normal control subjects at Japan Self-defense Forces Central Hospital. The system showed higher sensitivity of 98% and negative predictive value (NPV) of 96% compared to our previous system (sensitivity of 89%, NPV of 83%). The system can be used as a public health measure at points of entry where high sensitivity is most required in order to prevent the spread of the pandemic.


Screening infection self-organizing map K-means thermography heart rate respiratory rate microwave radar 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    World Health Organization: Communicable Disease Surveillance and Response: Severe Acute Respiratory Syndrome (SARS): Status of the outbreak and lessons for the immediate future, Geneva (2003)Google Scholar
  2. 2.
    St John, R.K., King, A., de Jong, D., Bodie-Collins, M., Squires, S.G., Tam, T.W.: Border screening for SARS. Emerg. Infect. Dis. 11, 6–10 (2005)CrossRefGoogle Scholar
  3. 3.
    Chan, L.S., Cheung, G.T., Lauder, I.J., Kumana, C.R., Lauder, I.J.: Screening for fever by remote-sensing infrared thermographic camera. J. Travel Med. 11, 273–279 (2004)CrossRefGoogle Scholar
  4. 4.
    Liu, C.C., Chang, R.E., Chang, W.C.: Limitations of forehead infrared body temperature detection for fever screening for severe acute respiratory syndrome. Infect. Control Hosp. Epidemiol. 25, 1109–1111 (2004)CrossRefGoogle Scholar
  5. 5.
    Nishiura, H., Kamiya, K.: Fever screening during the influenza (H1N1-2009) pandemic at Narita International Airport, Japan. BMC Infectious Diseases 11, 111 (2011), doi:10.1186/1471-2334-11-111CrossRefGoogle Scholar
  6. 6.
    Matsui, T., Suzuki, S., Ujikawa, K., Usui, T., Gotoh, S., Sugamata, M.: The development of a non-contact screening system for rapid medical inspection at a quarantine depot using a laser Doppler blood-flow meter, microwave radar and infrared thermography. J. Med. Eng. Technol. 33(6), 481–487 (2009)CrossRefGoogle Scholar
  7. 7.
    Matsui, T., Hakozaki, Y., Suzuki, S., Usui, T., Kato, T., Hasegawa, K., Sugiyama, Y., Sugamata, M., Abe, S.: A novel screening method for influenza patients using a newly developed non-contact screening system. J. Infect. 60, 271–277 (2010)CrossRefGoogle Scholar
  8. 8.
    Fukunaga, K.: Introduction to statistical pattern recognition. Academic Press, Tokyo (1990)zbMATHGoogle Scholar
  9. 9.
    Sugiyama, M.: Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis. The Journal of Machine Learning Research 8, 1027–1061 (2007)zbMATHGoogle Scholar
  10. 10.
    Kohonen, T.: The self-organizing map. Proceedings of the IEEE 78, 1464–1480 (1990)CrossRefGoogle Scholar
  11. 11.
    Vesanto, J., Himberg, J., Alhoniemi, E., Parhankangas, J.: Self-organizing map in Matlab: the SOM Toolbox. In: Proceedings of the Matlab DSP Conference, pp. 16–17 (1999)Google Scholar
  12. 12.
    MacQueen, J.: Some methods for classification and analysis of multivariate observations. In: Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, pp. 281–297 (1967)Google Scholar
  13. 13.
    Bitar, D., Goubar, A., Desenclos, J.C.: International travels and fever screening during epidemics: a literature review on the effectiveness and potential use of non-contact infrared thermometers. Eurosurveillance 12, 1–5 (2009)Google Scholar
  14. 14.
    Lalkhen, A.G., McCluskey, A.: Clinical tests: sensitivity and specificity. Continuing Education in Anaesthesia, Critical Care & Pain 2008 8, 221–223 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Guanghao Sun
    • 1
  • Shigeto Abe
    • 2
  • Osamu Takei
    • 3
  • Yukiya Hakozaki
    • 4
  • Takemi Matsui
    • 1
  1. 1.Department of Management Systems EngineeringTokyo Metropolitan UniversityHinoJapan
  2. 2.Takasaka ClinicIwakiJapan
  3. 3.Lifetech Co., LtdIrumaJapan
  4. 4.Department of Internal MedicineJapan Self-Defense Forces Central HospitalSetagayaJapan

Personalised recommendations