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Kinematics Analysis Multimedia System for Rehabilitation

  • Minxiang YeEmail author
  • Cheng Yang
  • Vladimir Stankovic
  • Lina Stankovic
  • Andrew Kerr
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9281)

Abstract

Driven by recent advances in information and communications technology, tele-rehabilitation services based on multimedia processing are emerging. Gait analysis is common for many rehabilitation programs, being, for example, periodically performed in the post-stroke recovery assessment. Since current optical diagnostic and patient assessment tools tend to be expensive and not portable, this paper proposes a novel marker-based tracking system using a single depth camera which provides a cost-effective solution that enables tele-rehabilitation services from home and local clinics. The proposed system can simultaneously generate motion patterns even within a complex background using the proposed geometric model-based algorithm and autonomously provide gait analysis results using a customised user-friendly application that facilitates seamless navigation through the captured scene and multi-view video data processing, designed using feedback from practitioners to maximise user experience. The locally processed rehabilitation data can be accessed by cross-platform mobile devices using cloud-based services enabling emerging tele-rehabilitation practices.

Keywords

Multimedia signal processing Gait analysis Optical marker Multimedia content analysis 

References

  1. 1.
    Yang, C., Ugbolue, U., Carse, B., Stankovic, V., Stankovic, L., Rowe, P.: Multiple marker tracking in a single-camera system for gait analysis. In: ICIP IEEE Int. Conf. Image Processing, pp. 3128–3131. IEEE, October 2013Google Scholar
  2. 2.
    VICON: Gait Analysis (2015). http://www.vicon.com
  3. 3.
    Ugbolue, U.C., et al.: The evaluation of an inexpensive, 2d, video based gait assessment system for clinical use. Gait & Posture 38, 483–489 (2013)CrossRefGoogle Scholar
  4. 4.
    Leu, A., Ristic-Durrant, D., Graser, A.: A robust markerless vision-based human gait analysis system. In: 2011 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI), pp. 415–420, May 2011Google Scholar
  5. 5.
    Liao, T.Y., Miaou, S.G., Li, Y.R.: A vision-based walking posture analysis system without markers. In: 2010 2nd International Conference on Signal Processing Systems (ICSPS), vol. 3, pp. V3–254–V3-258, July 2010Google Scholar
  6. 6.
    Li, Y.R., Miaou, S.G., Hung, C., Sese, J.: A gait analysis system using two cameras with orthogonal view. In: 2011 International Conference on Multimedia Technology (ICMT), pp. 2841–2844, July 2011Google Scholar
  7. 7.
    Kinect for Window software development kit, May 2015. http://www.microsoft.com/en-us/kinectforwindowsdev
  8. 8.
    Kook Jun, S., Zhou, X., Ramsey, D.K., Krovi, V.N.: A comparative study of human motion capture and analysis tools. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.73
  9. 9.
    Nguyen, H.A., Meunier, J.: Gait analysis from video: camcorders vs. kinect. In: Campilho, A., Kamel, M. (eds.) ICIAR 2014, Part II. LNCS, vol. 8815, pp. 66–74. Springer, Heidelberg (2014) Google Scholar
  10. 10.
    Clark, R., Vernon, S., Mentiplay, B., Miller, K., McGinley, J., Pua, Y., Paterson, K., Bower, K.: Instrumenting gait assessment using the kinect in people living with stroke: reliability and association with balance tests. Journal of NeuroEngineering and Rehabilitation 12(1), 15 (2015)CrossRefGoogle Scholar
  11. 11.
    Agosto, M.K.: Bezier curves. In: Computer Graphics and Geometric Modelling: Implementation & Algorithms, pp. 396–404 (2005)Google Scholar
  12. 12.
    Casey Kerrigan, D., Schaufele, M., Wen, M.: Gait analysis. In: Rehabilitation Medicine: Principles and Practice, pp. 167–174 (1998)Google Scholar
  13. 13.
    Lachat, E., Macher, H., Mittet, M.A., Landes, T., Grussenmeyer, P.: First experiences with kinect v2 sensor for close range 3d modelling. In: ISPRS - Int. Archives of the Photogr., Remote Sens. Spatial Inform. Sciences XL-5/W4, pp. 93–100 (2015)Google Scholar
  14. 14.
    Kinect for Windows features: Kinect sensor key features and benefits, May 2015. https://www.microsoft.com/en-us/kinectforwindows/meetkinect/features.aspx
  15. 15.
    Suzuki, S., Be, K.: Topological structural analysis of digitized binary images by border following. Comp. Vision, Graphics and Image Proc. 30(1), 32–46 (1985)CrossRefzbMATHGoogle Scholar
  16. 16.
    Fitzgibbon, A.W., Fisher, R.B.: A buyer’s guide to conic fitting. In: Proc. of the 6th British Conf. Machine Vision, vol. 2, pp. 513–522. BMVC, BMVA Press (1995)Google Scholar
  17. 17.
    Toussaint, G.: Solving geometric problems with the rotating calipers. In: IEEE MELECON 1983, May 1983Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Minxiang Ye
    • 1
    Email author
  • Cheng Yang
    • 1
  • Vladimir Stankovic
    • 1
  • Lina Stankovic
    • 1
  • Andrew Kerr
    • 2
  1. 1.Department of Electronic and Electrical EngineeringUniversity of StrathclydeGlasgowUK
  2. 2.Biomedical Engineering DepartmentUniversity of StrathclydeGlasgowUK

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