Journal of Real-Time Image Processing

, Volume 4, Issue 2, pp 181–190 | Cite as

Real-time scratching behavior quantification system for laboratory mice using high-speed vision

  • Yuman Nie
  • Idaku Ishii
  • Kenkichi Yamamoto
  • Kensuke Orito
  • Hiroshi Matsuda
Original Research Paper

Abstract

Scratching is a specific behavior induced by itching; it is also a common symptom of many types of dermatitis. For the itching evaluation in animal models, automatic quantification system is needed for objective and accurate observation. In this study, a dedicated real-time motion analysis system is developed for detecting the scratching behavior of laboratory mice in long-time experiments, which enables automated behavior quantification for the development of new drugs for diseases such as atopic dermatitis. This system can detect laboratory mice scratching in a non-invasive method by introducing a specially designed high-speed vision system that can calculate the frame-to-frame difference at a frame rate of 240 fps. A quantification algorithm is also implemented for distinguishing the scratching behavior from other behaviors. In fact, we evaluate the effectiveness of our system by demonstrating the experimental results of scratching behavior detection during the long-time observation of several ICR mice. The results also show the objectiveness and accuracy.

Keywords

Automatic behavior quantification Real-time vision Frame-to-frame difference New drugs development 

References

  1. 1.
    Kuraishi, Y., Nagasawa, T., Hayashi, K., Satoh, M.: Scratching behavior induced by pruritogenic but not algesiogenic agents in mice. Eur. J. Pharmacol. 275, 229–233 (1995)CrossRefGoogle Scholar
  2. 2.
    Benyon, R.C., Church, M.K., Clegg, L.S., Holgate, S.T.: Dispersion and characterization of mast cells from human skin. Int. Arch. Allerg. Immunol. 79, 332–334 (1986)Google Scholar
  3. 3.
    Barrett, K.E., Ali, H., Pearce, F.L.: Studies on histamine secretion from enzymically dispersed cutaneous mast cells of the rat. J. Invest. Dermatol. 84:22–26 (1985)CrossRefGoogle Scholar
  4. 4.
    Inagaki, N., Nakamura, N., Nagao M., Musoh, K., Kawasaki, H., Nagai, H.: Participation of histamine H1 and H2 receptors in passive cutaneous anaphylaxis-induced scratching behavior in ICR mice. Eur. J. Pharmacol. 367, 361–371 (1999) CrossRefGoogle Scholar
  5. 5.
    Thomsen, J.S., Simonsen, L., Benfeldt, E., Jensen, S.B., Serup, J.: The effect of topically applied salicylic compounds on serotonin-induced scratching behaviour in hairless rats. Clin. Exp. Dermatol. 11, 370–375 (2002)CrossRefGoogle Scholar
  6. 6.
    Miyamoto, T., Nojima, H., Shinkado, T., Nakahashi, T., Kuraishi, Y.: Itch-associated response induced by experimental dry skin in mice. Jpn. J. Pharmcol. 88, 285–292 (2002)CrossRefGoogle Scholar
  7. 7.
    Inagaki, N., Igeta, K., Shiraishi, N., Kim, J.F., Nagao, M., Nakamura, N., Nagai, H.: Evaluation and characterization of mouse scratching behavior by a new apparatus, MicroAct. Skin Pharmacol. Appl. Skin Physiol. 16(3), 165–175 (2003)Google Scholar
  8. 8.
    Moeslund, T.B., Hilton, A., Kräger, V.: A survey of advances in vision-based human motion capture and analysis. Comp. Vis. Image Understanding 104(2–3), 90–126 (2006)CrossRefGoogle Scholar
  9. 9.
    Ke, Y., Sukthankar, R., Hebert, M.: Spatio-temporal shape and flow correlation for action recognition. IEEE Conf. Comp. Vis. Patt. Recogn. 1–8 (2007)Google Scholar
  10. 10.
    Niebles, J.C., Fei-Fei, L.: A hierarchical model of shape and appearance for human action classification. IEEE Comp. Vis. Patt. Recogn. 17—22:1–8 (2007)Google Scholar
  11. 11.
    Xu, D., Chang, S.F.: Video event recognition using kernel methods with multilevel temporal alignment. IEEE Trans. Patt. Anal. Mach. Intell. Arch. 30(11), 1985–1997 (2008)CrossRefGoogle Scholar
  12. 12.
    Savarese, S., Pozo, A.D., Niebles, J.C., Fei-Fei, L.: Spatial–temporal correlations for unsupervised action classification. IEEE Workshop on Motion and Video Computing. Copper Mountain, Colorado (2008)Google Scholar
  13. 13.
    Wang, L., Suter, D.: Visual learning and recognition of sequential data manifolds with applications to human movement analysi. Comp. Vis. Image Understanding 110(2):153–172 (2008)CrossRefGoogle Scholar
  14. 14.
    Sundaresan, A., Chodhury, A.R., Chellappa, R.: A hidden markov model based framework for recognition of humans from gait sequences. In: International Conference on Image Processing, vol. 2, 93–96 (2003)Google Scholar
  15. 15.
    Yang, X., Zhou, Y., Zhang, T., Shu, G., Yang, J.: Gait recognition based on dynamic region analysis. Signal Signal Process. 88(9), 2350–2356 (2008)MATHCrossRefGoogle Scholar
  16. 16.
    Cheng, M.H., Ho, M.F., Huang, C.L.: Gait analysis for human identification through manifold learning and HMM. Patt. Recogn. 41(8), 2541–2553 (2008)MATHCrossRefGoogle Scholar
  17. 17.
    Guerra, E., Villalobos, J.R.: A three-dimensional automated visual inspection system for SMT assembly. Comp. Ind. Eng. 40, 175–190 (2001)CrossRefGoogle Scholar
  18. 18.
    Zhang, L., Dehghani, A., Su, Z., King, T., Greenwood, B., Levesley, M.: Real-time automated visual inspection system for contaminant removal from wool. Real-Time Imaging 11, 257–269 (2005)CrossRefGoogle Scholar
  19. 19.
    Ishii, I., Yamamoto, K., Doi, K., Tsuji, T.: High-speed 3D image acquisition using coded structured light projection. IEEE/RSJ Int. Conf. Intell. Robots Syst. 925–930 (2007)Google Scholar
  20. 20.
    Elliott, G.R., Vanwersch, R.A., Bruijnzeel, P.L.: An automated method for registering and quantifying scratching activity in mice: use for drug evaluation. J. Pharmacol. Toxicol. Methods 44, 453–459 (2000)CrossRefGoogle Scholar
  21. 21.
    Brash, H.M., McQueen, D.S., Christie, D., Bell, J.K., Bond, S.M., Rees, J.L.: A repetitive movement detector used for automatic monitoring and quantification of scratching in mice. Neurosci. Methods 142(1), 107–114 (2005)CrossRefGoogle Scholar
  22. 22.
    Umeda, K., Noro, Y., Murakami, T., Tokime, K., Sugisaki, H., Yamanaka, K., Kurokawa, I., Kuno, K., Tsutsui, H., Nakanishi, K., Mizutani, H.: A novel acoustic evaluation system of scratching in mouse dermatitis: rapid and specific detection of invisibly rapid scratch in an atopic dermatitis model mouse Life Sci. 79, 2144–2150 (2006)CrossRefGoogle Scholar
  23. 23.
    Orito, K., Chida, Y., Fujisawa, C., Arkwright, P.D., Matsuda, H.: A new analytical system for quantification scratching behaviour in mice. Br. J. Dermatol. 150, 33–38 (2004)CrossRefGoogle Scholar
  24. 24.
    Ishii, I., Kurozumi, S., Orito, K., Matsuda, H.: Automatic scratching pattern detection for laboratory mice using high-speed video images. IEEE Trans. Autom. Sci. Eng. 5(1), 176–182 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Yuman Nie
    • 1
  • Idaku Ishii
    • 1
  • Kenkichi Yamamoto
    • 1
  • Kensuke Orito
    • 2
  • Hiroshi Matsuda
    • 3
  1. 1.Robotics Laboratory, Department of Artificial Complex Systems EngineeringHiroshima UniversityHigashi-hiroshimaJapan
  2. 2.Department of Pharmacology, School of Veterinary MedicineAzabu UniversitySagamiharaKanagawaJapan
  3. 3.Division of Animal Life Science, Institute of Symbiotic Science and TechnologyTokyo University of Agriculture and TechnologyFuchuTokyoJapan

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