Advertisement

Optimal Control and Synergic Pattern Analysis of Upper Limb Reaching-Grasping Movements

  • Yiyong Yang
  • Rencheng Wang
  • Ming Zhang
  • Dewen Jin
  • Fangfang Wu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4561)

Abstract

A three-dimension, neuromusculoskeletal model of the human upper limb, consisting of 30 muscle–tendon systems, was combined with dynamic optimization theory to simulate reaching-grasping movements. The model was verified using experimental kinematics, muscle forces, and electromyographic(EMG) data from volunteer subjects performing reaching-grasping movements. Despite joint redundancy, the topological invariance was observed in the trajectories of different task performance, and the linear relationships between joints covariation were exhibited. Quantitative comparisons of the model predictions and muscle activations obtained from experiment show that the minimum torque-change criterion is a valid measure of reaching-grasping performance.

Keywords

Synergic Pattern Optimal Control Upper limb Reaching to grasp movements 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bernstein, N A.: The co-ordination and regulation of movements, pp. 15–28. Pergamon Press, Oxford, London (1967)Google Scholar
  2. 2.
    Lemay, M.A, Patrick, E.C.: A dynamic model for simulating movements of the elbow, forearm, wrist. J. Biomechanics 29, 1319–1330 (1996)CrossRefGoogle Scholar
  3. 3.
    Gottlieb, G.L., Song, Q., Hong, D.A., et al.: Coordinating movement at two joints: A principle of linear covariance. Journal of Neurophysiology 75, 1760–1730 (1996)Google Scholar
  4. 4.
    Weinberg, A.M., Pietsch, I.T., Helm, M.B.: A new kinematic model of pro-and supination of the human forearm. Journal of Biomechanics 33, 487–491 (2000)CrossRefGoogle Scholar
  5. 5.
    Schmidt, R., Disselhorst-Klug, C., Silny, J., et al.: A marker-based measurement procedure for unconstrained wrist and elbow motions. Journal of Biomechanicals 32, 615–621 (1999)CrossRefGoogle Scholar
  6. 6.
    Chao, E.Y.S., An, K.N., Cooney III., et al.: Biomechanics of the Hand. A Basic Research Study, pp. 60–66. World Scientific, Singapore (1989)Google Scholar
  7. 7.
    Yi-yong, Y.: Motion synergy and Control of Human Neuromusculoskeletal System. Ph.D. thesis, pp. 57–78, Tsinghua University Press, BeiJing (2004)Google Scholar
  8. 8.
    Crowninshield, R.D, Brand, R.A.: A physiologically based criterion of muscle force prediction in locomotion. Journal of Biomechanics 14, 793–801 (1981)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Yiyong Yang
    • 1
  • Rencheng Wang
    • 2
  • Ming Zhang
    • 3
  • Dewen Jin
    • 2
  • Fangfang Wu
    • 2
  1. 1.School of Engineering and Technology, China University of Geosciences (Beijing), Beijing 100083China
  2. 2.Division of Intelligent and Biomechanical System, State Key Laboratory of Tribology, Tsinghua University, Beijing, 100084China
  3. 3.Jockey Club Rehabilitation Engineering Centre, The Hong Kong Polytechnic University, Hong KongChina

Personalised recommendations