A Robust Hand Pose Estimation Algorithm for Hand Rehabilitation

  • Francesca Cordella
  • Francesco Di Corato
  • Loredana Zollo
  • Bruno Siciliano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8158)

Abstract

During a rehabilitation session, patient activity should be continuously monitored in order to correct wrong movements and to follow patient improvements. Therefore, the application of human motion tracking techniques to rehabilitation is finding more and more consensus. The aim of this paper is to propose a novel, low-cost method for hand pose estimation by using a monocular motion sensing device and a robust marker-based pose estimation approach based on the Unscented Kalman Filter. The hand kinematics is used to enclose geometrical constraints in the estimation process. The approach is applied for evaluating some significant kinematic parameters necessary for understanding human hand motor improvements during rehabilitation. In particular, the parameters evaluated for the hand fingers are joint positions, angles, Range Of Motion and trajectory. Moreover, the position, orientation and velocity of the wrist are estimated.

Keywords

hand pose estimation rehabilitation Unscented Kalman Filter 

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References

  1. 1.
    Pellegrino, G., Tomasevic, L., Tombini, M., Assenza, G., Gallotta, E., Sterzi, S., Giacobbe, V., Zollo, L., Guglielmelli, E., Cavallo, G., Vernieri, F., Tecchio, F.: Interhemispheric coupling changes associate with motor improvements after robotic stroke rehabilitation. Restorative Neurology and Neuroscience (2012)Google Scholar
  2. 2.
    Formica, D., Zollo, L., Guglielmelli, E.: Torque-dependent compliance control in the joint space of an operational robotic machine for motor therapy. ASME Journal of Dynamic Systems, Measurement, and Control 128, 152–158 (2006)CrossRefGoogle Scholar
  3. 3.
    Zhou, H., Hu, H.: Human motion tracking for rehabilitation–A survey. Biomedical Signal Processing and Control 3, 1–18 (2008)CrossRefGoogle Scholar
  4. 4.
    Cerveri, P., De Momi, E., Lopomo, N., Baud-Bovy, G., Barros, R.M., Ferrigno, G.: Finger kinematic modeling and real-time hand motion estimation. Annals of Biomedical Engineering 35, 1989–2002 (2007)CrossRefGoogle Scholar
  5. 5.
    Erol, A., Bebis, G., Nicolescu, M., Boyle, R.D., Twombly, X.: A Review on Vision-Based Full DOF Hand Motion Estimation. In: Conf. on Computer Vision and Pattern Recognition, pp. 75–82 (2005)Google Scholar
  6. 6.
    Deutscher, J., Blake, A., Reid, I.: Articulated body motion capture by annealed particle filtering. In: Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 126–133 (2000)Google Scholar
  7. 7.
    Bray, M., Koller-Meier, E., Van Gool, L.: Smart particle filtering for 3D hand tracking. In: Conf. on Automatic Face & Gesture Recognition, pp. 675–680 (2004)Google Scholar
  8. 8.
    Lin, J.Y., Wu, Y., Huang, T.S.: 3D model-based hand tracking using stochastic direct search method. In: Conf. on Automatic Face & Gesture Recognition, pp. 693–698 (2004)Google Scholar
  9. 9.
    Chang, W.Y., Chen, C.S., Hung, Y.P.: Appearance-guided particle filtering for articulated hand tracking. In: Conf. on Computer Vision and Pattern Recognition, vol. 1, pp. 235–242 (2005)Google Scholar
  10. 10.
    Stenger, B., Thayananthan, A., Torr, P.H.S., Cipolla, R.: Hand pose estimation using hierarchical detection. In: Sebe, N., Lew, M., Huang, T.S. (eds.) ECCV/HCI 2004. LNCS, vol. 3058, pp. 105–116. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  11. 11.
    Chua, C.S., Guan, H.Y., Ho, Y.K.: Model-based finger posture estimation. In: Asian Conference on Computer Vision (2000)Google Scholar
  12. 12.
    Lee, J., Kunii, T.: Constraint-based hand animation. In: Models and Techniques in Computer Animation, 110–127 (1993)Google Scholar
  13. 13.
    Lin, J., Wu, Y., Huang, T.S.: Modeling the Constraints of Human Hand Motion. In: Proceeding Workshop on Human Motion, pp. 121–126 (2000)Google Scholar
  14. 14.
    Parasuraman, S., Zhen, C.C.S.: Development of Robot Assisted Hand Stroke Rehabilitation System. In: Conf. on Computer and Automation Engineering, pp. 70–74 (2009)Google Scholar
  15. 15.
    Cordella, F., Di Corato, F., Zollo, L., Siciliano, B., van der Smagt, P.: Patient performance evaluation using Kinect and Monte Carlo-Based fnger tracking. In: Conf. on Biomedical Robotics and Biomechatronics, pp. 1967–1972 (2012)Google Scholar
  16. 16.
    Di Corato, F.: A Unified Framework for Constrained Visual-Inertial Navigation with Guaranteed Convergence. PhD Dissertation, University of Pisa (May 2013)Google Scholar
  17. 17.
    Kandepu, R., Foss, B., Imsland, L.: Applying the unscented Kalman filter for nonlinear state estimation. Journal of Process Control 18(7-8), 753–768 (2008)CrossRefGoogle Scholar
  18. 18.
    Wan, E.A., Van der Merwe, R.: The unscented Kalman filter for nonlinear estimation. In: Symposium on Adaptive Systems for Signal Processing, Communications, and Control, pp. 153–158 (2000)Google Scholar
  19. 19.
    Zollo, L., Rossini, L., Bravi, M., Magrone, G., Sterzi, S., Guglielmelli, E.: Quantitative evaluation of upper-limb motor control in robot-aided rehabilitation. Medical and Biological Engineering and Computing 9(49), 1131–1144 (2011)CrossRefGoogle Scholar
  20. 20.
    Formica, D., Krebs, H.I., Charles, S.K., Zollo, L., Guglielmelli, E., Hogan, N.: Passive wrist joint stiffness estimation. Journal of Neurophysiology (2012)Google Scholar
  21. 21.
    Berger, R.A., Weiss, A.P.C.: Hand surgery (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Francesca Cordella
    • 1
  • Francesco Di Corato
    • 2
  • Loredana Zollo
    • 3
  • Bruno Siciliano
    • 1
  1. 1.PRISMA Lab, Department of Electrical Engineering and Information TechnologyUniversità di Napoli Federico IINapoliItaly
  2. 2.Research Center “E. Piaggio”Università di PisaPisaItaly
  3. 3.Laboratory of Biomedical Robotics and BiomicrosystemsUniversità Campus Bio-MedicoRomaItaly

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