Document Detail


Optimality in neuromuscular systems.
MedLine Citation:
PMID:  21095783     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
We provide an overview of optimal control methods to nonlinear neuromuscular systems and discuss their limitations. Moreover we extend current optimal control methods to their application to neuromuscular models with realistically numerous musculotendons; as most prior work is limited to torque-driven systems. Recent work on computational motor control has explored the used of control theory and estimation as a conceptual tool to understand the underlying computational principles of neuromuscular systems. After all, successful biological systems regularly meet conditions for stability, robustness and performance for multiple classes of complex tasks. Among a variety of proposed control theory frameworks to explain this, stochastic optimal control has become a dominant framework to the point of being a standard computational technique to reproduce kinematic trajectories of reaching movements (see [12]) In particular, we demonstrate the application of optimal control to a neuromuscular model of the index finger with all seven musculotendons producing a tapping task. Our simulations include 1) a muscle model that includes force- length and force-velocity characteristics; 2) an anatomically plausible biomechanical model of the index finger that includes a tendinous network for the extensor mechanism and 3) a contact model that is based on a nonlinear spring-damper attached at the end effector of the index finger. We demonstrate that it is feasible to apply optimal control to systems with realistically large state vectors and conclude that, while optimal control is an adequate formalism to create computational models of neuro-musculoskeletal systems, there remain important challenges and limitations that need to be considered and overcome such as contact transitions, curse of dimensionality, and constraints on states and controls.
Authors:
Evangelos Theodorou; Francisco J Valero-Cuevas
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference     Volume:  2010     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2010  
Date Detail:
Created Date:  2010-11-24     Completed Date:  2011-03-29     Revised Date:  2014-04-08    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  4510-6     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Computer Simulation
Fingers / innervation,  physiology*
Humans
Models, Neurological*
Motor Neurons / physiology*
Movement / physiology*
Muscle Contraction / physiology*
Muscle, Skeletal / innervation,  physiology*
Neuromuscular Junction / physiology
Synaptic Transmission / physiology*
Grant Support
ID/Acronym/Agency:
AR050520/AR/NIAMS NIH HHS; AR052345/AR/NIAMS NIH HHS

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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