Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy...

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Veröffentlicht in:	Frontiers in computational neuroscience Jg. 8; S. 21
Hauptverfasser:	Hayashibe, Mitsuhiro, Shimoda, Shingo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Research Foundation 28.02.2014 Frontiers Frontiers Media S.A
Schlagworte:	Adaptability Adaptation Automatic Control Engineering Behavior Bernstein problem Bioengineering Central nervous system Computer applications Computer Science Energy efficiency Feedback Feedback Error Learning Kinematics Life Sciences Mechanical properties Motor skill learning Motor synergies Motor task performance Neuroscience Neurosciences optimality Optimization redundancy Robotics Robots Tacit Learning Trends feedback error learning Bernstein problem interaction torques motor synergy tacit learning optimality redundancy Motor synergy Redundancy Interaction torques Optimality Tacit learning Feedback error learning
ISSN:	1662-5188, 1662-5188
Online-Zugang:	Volltext
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