DocumentCode
662926
Title
An integrated model of the neuromuscular system
Author
Heidlauf, Thomas ; Negro, Francesco ; Farina, Dario ; Rohrle, Oliver
Author_Institution
Stuttgart Res. Centre for Simulation Technol. (SimTech), Univ. of Stuttgart, Stuttgart, Germany
fYear
2013
fDate
6-8 Nov. 2013
Firstpage
227
Lastpage
230
Abstract
A modeling framework for the neuromuscular system unifying five components is presented. The components are: (1) a biophysical model of the motoneuron pool predicting motor unit recruitment and motor unit firing times; (2) a biophysically based description of the excitation-contraction coupling in the sarcomeres, which determines the cross-bridge-cycling induced stress of a sarcomere; (3) action potential propagation along skeletal muscle fibers based on the monodomain model; (4) a continuum-mechanical, three-dimensional description of the muscle geometry including a realistic spatially-varying motor unit distribution for computing the deformations and the exerted force; and (5) phenomenological models of muscle spindles providing sensory feedback to the central nervous system. The individual components are strongly coupled to each other through a flow of information making a decoupled solution strategy of the different submodels impossible. The integrated model allows the simulation of the entire pathway from supraspinal input to force production enabling the investigation of various phenomena of the neuromuscular system, and the analysis of different physiological hypotheses.
Keywords
bioelectric potentials; biomechanics; cellular biophysics; deformation; feedback; neurophysiology; physiological models; somatosensory phenomena; action potential propagation; biophysical model; central nervous system; continuum-mechanical model; cross-bridge-cycling induced stress; deformation computation; excitation-contraction coupling; force computation; integrated modeling framework; monodomain model; motoneuron pool; motor unit firing time prediction; motor unit recruitment prediction; neuromuscular system; phenomenological muscle spindle models; physiological hypotheses; sarcomeres; sensory feedback; skeletal muscle fibers; supraspinal pathway simulation; three-dimensional muscle geometry; Biological system modeling; Computational modeling; Force; Manganese; Mathematical model; Muscles; Physiology;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on
Conference_Location
San Diego, CA
ISSN
1948-3546
Type
conf
DOI
10.1109/NER.2013.6695913
Filename
6695913
Link To Document