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  • 标题:Evidence for sparse synergies in grasping actions
  • 本地全文:下载
  • 作者:Roberto Prevete ; Francesco Donnarumma ; Andrea d’Avella
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2018
  • 卷号:8
  • 期号:1
  • 页码:616
  • DOI:10.1038/s41598-017-18776-y
  • 语种:English
  • 出版社:Springer Nature
  • 摘要:Converging evidence shows that hand-actions are controlled at the level of synergies and not single muscles. One intriguing aspect of synergy-based action-representation is that it may be intrinsically sparse and the same synergies can be shared across several distinct types of hand-actions. Here, adopting a normative angle, we consider three hypotheses for hand-action optimal-control: sparse-combination hypothesis (SC) - sparsity in the mapping between synergies and actions - i.e., actions implemented using a sparse combination of synergies; sparse-elements hypothesis (SE) - sparsity in synergy representation - i.e., the mapping between degrees-of-freedom (DoF) and synergies is sparse; double-sparsity hypothesis (DS) - a novel view combining both SC and SE - i.e., both the mapping between DoF and synergies and between synergies and actions are sparse, each action implementing a sparse combination of synergies (as in SC), each using a limited set of DoFs (as in SE). We evaluate these hypotheses using hand kinematic data from six human subjects performing nine different types of reach-to-grasp actions. Our results support DS, suggesting that the best action representation is based on a relatively large set of synergies, each involving a reduced number of degrees-of-freedom, and that distinct sets of synergies may be involved in distinct tasks.
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