Optimal control and synergic pattern analysis of upper limb reaching-grasping movements

Yiyong Yang, Rencheng Wang, Ming Zhang, Dewen Jin, Fangfang Wu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


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.

Original languageEnglish
Title of host publicationDigital Human Modeling - First International Conference on Digital Human Modeling, ICDHM 2007. Held as Part of HCI International 2007, Proceedings
Number of pages8
Publication statusPublished - 1 Dec 2007
Event1st International Conference on Digital Human Modeling, ICDHM 2007 - Beijing, China
Duration: 22 Jul 200727 Jul 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4561 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference1st International Conference on Digital Human Modeling, ICDHM 2007


  • Optimal control
  • Reaching to grasp movements
  • Synergic pattern
  • Upper limb

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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