Literature DB >> 18049823

Nonlinearities make a difference: comparison of two common Hill-type models with real muscle.

Tobias Siebert1, Christian Rode, Walter Herzog, Olaf Till, Reinhard Blickhan.   

Abstract

Compared to complex structural Huxley-type models, Hill-type models phenomenologically describe muscle contraction using only few state variables. The Hill-type models dominate in the ever expanding field of musculoskeletal simulations for simplicity and low computational cost. Reasonable parameters are required to gain insight into mechanics of movement. The two most common Hill-type muscle models used contain three components. The series elastic component is connected in series to the contractile component. A parallel elastic component is either connected in parallel to both the contractile and the series elastic component (model [CC+SEC]), or is connected in parallel only with the contractile component (model [CC]). As soon as at least one of the components exhibits substantial nonlinearities, as, e.g., the contractile component by the ability to turn on and off, the two models are mechanically different. We tested which model ([CC+SEC] or [CC]) represents the cat soleus better. Ramp experiments consisting of an isometric and an isokinetic part were performed with an in situ cat soleus preparation using supramaximal nerve stimulation. Hill-type models containing force-length and force-velocity relationship, excitation-contraction coupling and series and parallel elastic force-elongation relations were fitted to the data. To test which model might represent the muscle better, the obtained parameters were compared with experimentally determined parameters. Determined in situations with negligible passive force, the force-velocity relation and the series elastic component relation are independent of the chosen model. In contrast to model [CC+SEC], these relations predicted by model [CC] were in accordance with experimental relations. In conclusion model [CC] seemed to better represent the cat soleus contraction dynamics and should be preferred in the nonlinear regression of muscle parameters and in musculoskeletal modeling.

Mesh:

Year:  2007        PMID: 18049823     DOI: 10.1007/s00422-007-0197-6

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  13 in total

1.  Simulation system of spinal cord motor nuclei and associated nerves and muscles, in a Web-based architecture.

Authors:  Rogerio R L Cisi; André F Kohn
Journal:  J Comput Neurosci       Date:  2008-05-28       Impact factor: 1.621

2.  Importance of contraction history on muscle force of porcine urinary bladder smooth muscle.

Authors:  Robin Menzel; Markus Böl; Tobias Siebert
Journal:  Int Urol Nephrol       Date:  2016-12-17       Impact factor: 2.370

3.  Cupiennius salei: biomechanical properties of the tibia-metatarsus joint and its flexing muscles.

Authors:  Tobias Siebert; Tom Weihmann; Christian Rode; Reinhard Blickhan
Journal:  J Comp Physiol B       Date:  2009-09-16       Impact factor: 2.200

4.  Three-Dimensional Muscle Architecture and Comprehensive Dynamic Properties of Rabbit Gastrocnemius, Plantaris and Soleus: Input for Simulation Studies.

Authors:  Tobias Siebert; Kay Leichsenring; Christian Rode; Carolin Wick; Norman Stutzig; Harald Schubert; Reinhard Blickhan; Markus Böl
Journal:  PLoS One       Date:  2015-06-26       Impact factor: 3.240

5.  A multiscale chemo-electro-mechanical skeletal muscle model to analyze muscle contraction and force generation for different muscle fiber arrangements.

Authors:  Thomas Heidlauf; Oliver Röhrle
Journal:  Front Physiol       Date:  2014-12-23       Impact factor: 4.566

6.  Suboptimal Muscle Synergy Activation Patterns Generalize their Motor Function across Postures.

Authors:  M Hongchul Sohn; Lena H Ting
Journal:  Front Comput Neurosci       Date:  2016-02-04       Impact factor: 2.380

7.  Model-based analysis of fatigued human knee extensors : Effects of isometrically induced fatigue on Hill-type model parameters and ballistic contractions.

Authors:  Harald Penasso; Sigrid Thaller
Journal:  Eur J Appl Physiol       Date:  2018-05-05       Impact factor: 3.078

8.  Porcine Stomach Smooth Muscle Force Depends on History-Effects.

Authors:  André Tomalka; Mischa Borsdorf; Markus Böl; Tobias Siebert
Journal:  Front Physiol       Date:  2017-10-18       Impact factor: 4.566

9.  Spreading out muscle mass within a Hill-type model: a computer simulation study.

Authors:  Michael Günther; Oliver Röhrle; Daniel F B Haeufle; Syn Schmitt
Journal:  Comput Math Methods Med       Date:  2012-11-22       Impact factor: 2.238

10.  Implementation and validation of the extended Hill-type muscle model with robust routing capabilities in LS-DYNA for active human body models.

Authors:  Christian Kleinbach; Oleksandr Martynenko; Janik Promies; Daniel F B Haeufle; Jörg Fehr; Syn Schmitt
Journal:  Biomed Eng Online       Date:  2017-09-02       Impact factor: 2.819

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