Simplified and effective motor control based on muscle synergies to exploit musculoskeletal dynamics
Name
Berniker-2009-Simplified and effec.pdf
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Author(s)
Berniker, Max
Jarc, Anthony
Bizzi, Emilio
Tresch, Matthew C.
Date Issued
April 2009
Journal
Proceedings of the National Academy of Sciences of the United States of America
Publisher
National Academy of Sciences
Citation
Berniker, Max et al. “Simplified and effective motor control based on muscle synergies to exploit musculoskeletal dynamics.” Proceedings of the National Academy of Sciences 106.18 (2009): 7601-7606.
Version
Final published version
Abstract
The basic hypothesis of producing a range of behaviors using a small set of motor commands has been proposed in various forms to explain motor behaviors ranging from basic reflexes to complex voluntary movements. Yet many fundamental questions regarding this long-standing hypothesis remain unanswered. Indeed, given the prominent nonlinearities and high dimensionality inherent in the control of biological limbs, the basic feasibility of a low-dimensional controller and an underlying principle for its creation has remained elusive. We propose a principle for the design of such a controller, that it endeavors to control the natural dynamics of the limb, taking into account the nature of the task being performed. Using this principle, we obtained a low-dimensional model of the hindlimb and a set of muscle synergies to command it. We demonstrate that this set of synergies was capable of producing effective control, establishing the viability of this muscle synergy hypothesis. Finally, by combining the low-dimensional model and the muscle synergies we were able to build a relatively simple controller whose overall performance was close to that of the system's full-dimensional nonlinear controller. Taken together, the results of this study establish that a low-dimensional controller is capable of simplifying control without degrading performance.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
McGovern Institute for Brain Research at MIT
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
http://dx.dor.org/10.1073/pnas.0901512106
