Extracting motor synergies from random movements for low-dimensional task-space control of musculoskeletal robots.

@article{Fu2015ExtractingMS,
  title={Extracting motor synergies from random movements for low-dimensional task-space control of musculoskeletal robots.},
  author={Kin Chung Denny Fu and Fabio Dalla Libera and Hiroshi Ishiguro},
  journal={Bioinspiration \& biomimetics},
  year={2015},
  volume={10 5},
  pages={
          056016
        }
}
In the field of human motor control, the motor synergy hypothesis explains how humans simplify body control dimensionality by coordinating groups of muscles, called motor synergies, instead of controlling muscles independently. In most applications of motor synergies to low-dimensional control in robotics, motor synergies are extracted from given optimal control signals. In this paper, we address the problems of how to extract motor synergies without optimal data given, and how to apply motor… 
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