Identification of Human Limb Stiffness in 5 DoF and Estimation via EMG

  • Dominic LakatosEmail author
  • Daniel Rüschen
  • Justin Bayer
  • Jörn Vogel
  • Patrick van der Smagt
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 88)


To approach robustness and optimal performance, biological musculoskeletal systems can adapt their impedance while interacting with their environment. This property has motivated modern robotic designs including variable-impedance actuators and control methods, based on the capability to vary visco-elastic properties actively or passively. Even though variable-impedance actuation and impedance control in robotics is resolved to a great part, a general set of rules by which impedance is adjusted related to the task at hand is still lacking. This paper aims to fill this gap by providing a method to estimate the stiffness of the human arm in more than two degrees of freedom by perturbation. To overcome ill-conditionedness of the impedance and inertial matrices, we propose and validate methods to separately identify inertial and stiffness parameters. Finally, a model is proposed to estimate the joint stiffness from EMG-measurements of muscle activities.


Inverse Kinematic Impedance Parameter Inertial Parameter Torque Sensor Human Limb 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Biryukova, E., Roby-Brami, A., Frolov, A., Mokhtari, M.: Kinematics of human arm reconstructed from spatial tracking system recordings. Journal of Biomechanics 33, 985–995 (2000)CrossRefGoogle Scholar
  2. 2.
    Burdet, E., Osu, R., Franklin, D.W., Yoshioka, T., Milner, T.E., Kawato, M.: A method for measuring endpoint stiffness during multi-joint arm movements. Journal of Biomechanics 33, 1705–1709 (2000)CrossRefGoogle Scholar
  3. 3.
    Chen, Y., McInroy, J.E.: Estimation of symmetric positive-definite matrices from imperfect measurements. IEEE Transaction on Automatic Control 47, 1721–1725 (2002)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Gomi, H., Kawato, M.: Human arm stiffness and equilibrium-point trajectory during multi-joint movement. Biological Cybernetics 76, 163–171 (1997)zbMATHCrossRefGoogle Scholar
  5. 5.
    Gomi, H., Osu, R.: Task-dependent viscoelasticity of human multijoint arm and its spatial characteristics for interaction with environments. The Journal of Neuroscience 18, 8965–8978 (1998)Google Scholar
  6. 6.
    Hogan, N.: The mechanics of multi-joint posture and movement control. Biological Cybernetics 52, 315–331 (1985)zbMATHCrossRefGoogle Scholar
  7. 7.
    Lakatos, D., Petit, F., van der Smagt, P.: Conditioning vs. excitation time for estimating impedance parameters of the human arm. IEEE Humanoids (2011)Google Scholar
  8. 8.
    Mussa-Ivaldi, F.A., Hogan, N., Bizzi, E.: Neural, mechanical, and geometric factors subserving arm posture in humans. The Journal of Neuroscience 5, 2732–2743 (1985)Google Scholar
  9. 9.
    Ngiam, J., Koh, P.W., Chen, Z., Bhaskar, S., Ng, A.: Sparse filtering. In: Shawe-Taylor, J., Zemel, R., Bartlett, P., Pereira, F., Weinberger, K. (eds.) Advances in Neural Information Processing Systems 24, pp. 1125–1133 (2011)Google Scholar
  10. 10.
    Perreault, E.J., Kirsch, R.F., Acosta, A.M.: Multiple-input, multiple-output system identification for characterization of limb stiffness dynamics. Biological Cybernetics 80, 327–337 (1999)zbMATHCrossRefGoogle Scholar
  11. 11.
    Perreault, E.J., Kirsch, R.F., Crago, P.E.: Effects of voluntary force generation on the elastic components of endpoint stiffness. Experimental Brain Research 141, 312–323 (2001)CrossRefGoogle Scholar
  12. 12.
    Tsuji, T., Morasso, P.G., Goto, K., Ito, K.: Human hand impedance characteristics during maintained posture. Biological Cybernetics 72, 475–485 (1995)zbMATHCrossRefGoogle Scholar
  13. 13.
    Venture, G., Yamane, K., Nakamura, Y., Yamamoto, T.: Identification of Human Limb Viscoelasticity using Robotics Methods to Support the Diagnosis of Neuromuscular Diseases. The International Journal of Robotics Research 28(10), 1322–1333 (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Dominic Lakatos
    • 1
    Email author
  • Daniel Rüschen
    • 1
  • Justin Bayer
    • 2
  • Jörn Vogel
    • 1
  • Patrick van der Smagt
    • 3
  1. 1.Institute of Robotics and MechatronicsGerman Aerospace Center (DLR)OberpfaffenhofenGermany
  2. 2.Chair for Robotics and Embedded Systems of the Department of InformaticsTechnische Universität MünchenMünchenGermany
  3. 3.Institute for InformaticsTechnische Universität MünchenMünchenGermany

Personalised recommendations