Neural Network Based Posture Control of a Human Arm Model in the Sagittal Plane

  • Shan Liu
  • Yongji Wang
  • Jian Huang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)


In this paper posture control of a human arm in the sagittal plane is investigated by means of model simulations. The arm is modeled by a nonlinear neuromusculoskeletal model with two degrees of freedom and six muscles. A multilayer perceptron network is used in this paper, and effectively adapted by Levenberg-Marquardt training algorithm. The duration of next movement is regulated according as current feedback states. Simulation Results indicate that this method can maintain two joints at different location in allowable bound. The control scheme provides novel insight into neural prosthesis control and robotic control.


Posture Control Feedforward Control Elbow Angle Motor Control System Passive Torque 


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  1. 1.
    Schouten, A.C., de Vlugt, E., van der Helm, F.C.T., Brouwn, G.G.: Optimal Posture Control of a Musculo-Skeletal Arm Model. Biol. Cybern. 84, 143–152 (2001)CrossRefGoogle Scholar
  2. 2.
    Brown, I.E., Cheng, E.J., Leob, G.: Measured and Modeled Properties of Mammalian Skeletal Muscle. II. the Effects of Stimulus Frequency on Force-Length and Force-Velocity Relationships. J. of Muscle Research and Cell Motility 20, 627–643 (1999)CrossRefGoogle Scholar
  3. 3.
    Franklin, D.W., Milner, T.E.: Adaptive Control of Stiffness to Stabilize Hand Position with Large Loads. Exp. Brain Res. 152, 211–220 (2003)CrossRefGoogle Scholar
  4. 4.
    Cheng, E.J., Brown, I.E., Loeb, G.E.: Virtual Muscle: a Computational Approach to Understanding the Effects of Muscle Properties on Motor Control. Journal of Neuroscience Methods 101, 117–130 (2000)CrossRefGoogle Scholar
  5. 5.
    Katayama, M., Inoue, S., Kawato, M.: A Strategy of Motor Learning Using Adjustable Parameters for Arm Movement. In: Chang, H.K., Zhang, Y.T. (eds.) Proceeding of 20th IEEE EMBS. IEEE Engineering in Medicine and Biology Society, vol. 20, pp. 2370–2373. IEEE Press, New Jersey (1998)Google Scholar
  6. 6.
    Hagan, M.T., Demuth, H.B., Beale, M.H.: Neural Network Design. PWS Publishing, Boston (1996)Google Scholar
  7. 7.
    Lan, N.: Analysis of an Optimal Control Model of Multi-Joint Arm Movements. Biol. Cybern. 76, 207–117 (1997)Google Scholar
  8. 8.
    Sanner, R.M., Kosha, M.: A Mathematical Model of the Adaptive Control of Human Arm Motions. Biol. Cybern. 80, 369–382 (1999)MATHCrossRefGoogle Scholar
  9. 9.
    Stroeve, S.H.: Impedance Characteristics of a Neuromusculoskeletal Model of the Human Arm. I. Posture Control. Biol. Cybern. 81, 475–494 (1999)MATHGoogle Scholar
  10. 10.
    Li, W., Todorov, E., Pan, X.: Hierarchical Optimal Control of Redundant Biomechanical Systems. In: Hudson, D., Liang, Z.P. (eds.) Proceeding of 26th IEEE EMBS. IEEE Engineering in Medicine and Biology Society, vol. 26, pp. 4618–4621. IEEE Press, New Jersey (2004)Google Scholar
  11. 11.
    Todorov, E., Li, W.: A Generalized Iterative LQG Method for Locally-optiml Feedback Control of Constrained Nonlinear Stochastic Systems. In: Suhada, J., Balakrishnan, S.N. (eds.) Proceeding of 2005 ACC. American Control Conference, vol. 1, pp. 300–306. IEEE Press, New Jersey (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shan Liu
    • 1
  • Yongji Wang
    • 1
  • Jian Huang
    • 1
  1. 1.Department of Control Science and EngineeringHuazhong University of Science and TechnologyWuhanChina

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