A computational model of limb impedance control based on principles of internal model uncertainty

Djordje Mitrovic*, Stefan Klanke, Rieko Osu, Mitsuo Kawato, Sethu Vijayakumar


研究成果: Article査読

42 被引用数 (Scopus)


Efficient human motor control is characterized by an extensive use of joint impedance modulation, which is achieved by co-contracting antagonistic muscles in a way that is beneficial to the specific task. While there is much experimental evidence available that the nervous system employs such strategies, no generally-valid computational model of impedance control derived from first principles has been proposed so far. Here we develop a new impedance control model for antagonistic limb systems which is based on a minimization of uncertainties in the internal model predictions. In contrast to previously proposed models, our framework predicts a wide range of impedance control patterns, during stationary and adaptive tasks. This indicates that many well-known impedance control phenomena naturally emerge from the first principles of a stochastic optimization process that minimizes for internal model prediction uncertainties, along with energy and accuracy demands. The insights from this computational model could be used to interpret existing experimental impedance control data from the viewpoint of optimality or could even govern the design of future experiments based on principles of internal model uncertainty.

ジャーナルPloS one
出版ステータスPublished - 2010

ASJC Scopus subject areas

  • 生化学、遺伝学、分子生物学(全般)
  • 農業および生物科学(全般)
  • 一般


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