- Author:
- pmr2.import <nobody@models.cellml.org>
- Date:
- 2008-07-25 03:56:25+12:00
- Desc:
- committing version01 of cheng_brown_loeb_2000
- Permanent Source URI:
- https://models.cellml.org/workspace/cheng_brown_loeb_2000/rawfile/3fb1c0c38d09b42a36ee60e3fe45a3ecd7d912b5/cheng_brown_loeb_2000.cellml
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<documentation xmlns="http://cellml.org/tmp-documentation">
<article>
<articleinfo>
<title>Virtual muscle: a computational approach to understanding the effects of muscle properties on motor control</title>
<author>
<firstname>Catherine</firstname>
<surname>Lloyd</surname>
<affiliation>
<shortaffil>Bioengineering Institute, University of Auckland</shortaffil>
</affiliation>
</author>
</articleinfo>
<section id="sec_status">
<title>Model Status</title>
<para>
This CellML model has been checked in both COR and PCEnv. Currently it can be opened in COR but due to the presence of 'circular arguments' the model does not run. However, the model can be opened in the latest snapshot of PCEnv (which contains a DAE solver), but although it does run, the model quickly produces NaNs and crashes. We are currently curating this CellML model in an attempt to get it to run to recreate the published results.
</para>
</section>
<sect1 id="sec_structure">
<title>Model Structure</title>
<para>
Abstract: This paper describes a computational approach to modeling the complex mechanical properties of muscles and tendons under physiological conditions of recruitment and kinematics. It is embodied as a software package for use with Matlab™ and Simulink that allows the creation of realistic musculotendon elements for use in motor control simulations. The software employs graphic user interfaces (GUI) and dynamic data exchange (DDE) to facilitate building custom muscle model blocks and linking them to kinetic analyses of complete musculoskeletal systems. It is scalable in complexity and accuracy. The model is based on recently published data on muscle and tendon properties measured in feline slow- and fast-twitch muscle, and incorporates a novel approach to simulating recruitment and frequency modulation of different fiber-types in mixed muscles. This software is distributed freely over the Internet at <ulink url="http://ami.usc.edu/mddf/virtualmuscle">http://ami.usc.edu/mddf/virtualmuscle</ulink>.
</para>
<informalfigure float="0" id="fig_reaction_diagram">
<mediaobject>
<imageobject>
<objectinfo>
<title>reaction diagram</title>
</objectinfo>
<imagedata fileref="cheng_2000.png"/>
</imageobject>
</mediaobject>
<caption>Schematic representation of the model equations and terms. These elements were designed to have a one-to-one correspondence with the physiological substrates of muscle contraction. The behavior of each element is governed by an equation driven by one to four input variables, with one to seven user-modifiable coefficients. The coefficients can be modified in the BuildFiberTypes function. Complete descriptions of these elements can be found in Brown and Loeb, 2000 and Brown. FPE1 represents the passive visco-elastic properties of stretching a muscle. FPE2 represents the passive resistance to compression of the thick filaments at short muscle lengths. FL represents the tetanic, isometric force–length relationship. FV represents the tetanic force–velocity (FV) relationship. Af represents the isometric, activation–frequency (Af) relationship. feff represents the time lag between changes in firing frequency and internal activation (i.e. rise and fall times). Leff represents the time lag between changes in length and the effect of length on the Af relationship. S represents the effects of ‘sag’ on the activation during a constant stimulus frequency. Y represents the effects of yielding (on activation) following movement during sub-maximal activation. </caption>
</informalfigure>
<para>
The complete original paper reference is cited below:
</para>
<para>
Virtual muscle: a computational approach to understanding the effects of muscle properties on motor control, Ernest J. Cheng, Ian E. Brown and Gerald E. Loeb, 2000, <ulink url="http://www.sciencedirect.com/science/journal/01650270">
<emphasis>Journal of Neuroscience Methods</emphasis>
</ulink>, 101, 117-130. (<ulink url="http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6T04-416BY5F-3&_user=140507&_coverDate=09%2F15%2F2000&_rdoc=3&_fmt=high&_orig=browse&_srch=doc-info(%23toc%234852%232000%23998989997%23209761%23FLA%23display%23Volume)&_cdi=4852&_sort=d&_docanchor=&_ct=11&_acct=C000011498&_version=1&_urlVersion=0&_userid=140507&md5=ca802b2b2cab8ff0771952f693059a04">Full text</ulink> and PDF versions of the article are available to journal subscribers on the <emphasis>Journal of Neuroscience Methods</emphasis> website.) <ulink url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=10996372&query_hl=1&itool=pubmed_docsum">PubMed ID: 10996372</ulink>
</para>
</sect1>
</article>
</documentation>
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<vCard:Given>Ernest</vCard:Given>
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<dc:publisher>The University of Auckland, Bioengineering Institute</dc:publisher>
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<vCard:Given>Gerald</vCard:Given>
<vCard:Family>Loeb</vCard:Family>
<vCard:Other>E</vCard:Other>
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<rdf:value>This CellML model has been checked in both COR and PCEnv. Currently it can be opened in COR but due to the presence of 'circular arguments' the model does not run. However, the model can be opened in the latest snapshot of PCEnv (which contains a DAE solver), but although it does run, the model quickly produces NaNs and crashes. We are currently curating this CellML model in an attempt to get it to run to recreate the published results</rdf:value>
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<dc:title>Journal of Neuroscience Methods</dc:title>
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<dcterms:W3CDTF>2000-09-15 00:00</dcterms:W3CDTF>
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<vCard:Orgname>The University of Auckland</vCard:Orgname>
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<dcterms:W3CDTF>2008-07-25T00:00:00+00:00</dcterms:W3CDTF>
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<vCard:Given>Ian</vCard:Given>
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<vCard:Given>Catherine</vCard:Given>
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