Endpoint stiffness of the arm is directionally tuned to instability in the environment

David W. Franklin*, Gary Liaw, Theodore E. Milner, Rieko Osu, Etienne Burdet, Mitsuo Kawato

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

228 Citations (Scopus)


It has been shown that humans are able to selectively control the endpoint impedance of their arms when moving in an unstable environment. However, directional instability was only examined for the case in which the main contribution was from coactivation of biarticular muscles. The goal of this study was to examine whether, in general, the CNS activates the sets of muscles that contribute to selective control of impedance in particular directions. Subjects performed reaching movements in three differently oriented unstable environments generated by a robotic manipulandum. After subjects had learned to make relatively straight reaching movements in the unstable force field, the endpoint stiffness of the limb was measured at the midpoint of the movements. For each force field, the endpoint stiffness increased in a specific direction, whereas there was little change in stiffness in the orthogonal direction. The increase in stiffness was oriented along the direction of instability in the environment, which caused the major axis of the stiffness ellipse to rotate toward the instability in the environment. This study confirms that the CNS is able to control the endpoint impedance of the limbs and selectively adapt it to the environment. Furthermore, it supports the idea that the CNS incorporates an impedance controller that acts to ensure stability, reduce movement variability, and reduce metabolic cost.

Original languageEnglish
Pages (from-to)7705-7716
Number of pages12
JournalJournal of Neuroscience
Issue number29
Publication statusPublished - 2007 Jul 18
Externally publishedYes


  • EMG
  • Impedance control
  • Motor control
  • Motor learning
  • Muscle cocontraction
  • Stability
  • Stiffness

ASJC Scopus subject areas

  • Neuroscience(all)


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