Computational tools for neuromechanical simulation and analysis
We use a number of different computational tools to generate neuromechanical simulations and to perform analysis of the data we collect in the lab. A number are in development and others are available for download or purchase.
Neuromechanic Software
We are developing neuromechanical modeling software to simulate and analyze dynamic characteristics of complex musculoskeletal models. This program was developed by Nate Bunderson, and is being developed for release to the research community. Automated linearization, stability analysis, and forward simulation used in Bunderson, Burkholder, and Ting 2008 were performed using this software. Beta version anticipated in mid-2010.
Four-bar Applet: Is wide stance more stable?
This java applet is provided as a demonstration of how configuration and delayed feedback can produce non-intuitive results. Specifically, as wide stance increases, feedback gains must decrease or instability may occur. Full analysis of this model is presented in a manuscript by Bingham, Choi and Ting submitted to the Journal of Neurophysiology 2011.
Matlab Tutorial: NMF vs PCA in muscle synergy analysis
Companion material for a chapter entitled "Muscle synergy analysis for posture and movement: methods and interpretation" by Ting and Chvatal, to appear in Progress in Motor Control, Danion and Latash, eds., 2010. We use intuitive tutorials to compare the different properties of principal components analysis and non-negative matrix factorization in the decomposition of electromyographic data.
Animatlab Software
This is a graphics-based neuromechanical modeling software package developed in the lab of Don Edwards at Georgia State University. It allow the user to link together models of neurons, muscles, limbs, and sensory receptors and to simulation how they work. A great way for a biologist to gain an intuitive understanding of neuromechanical interaction in an interactive simulation environment.
Autolev Software
This software generate equations of motion and simulates the motion of rigid bodies using Kane's method. It can also generate Matlab, C, or Fortran code for running the simulations to which models of neural control can be added.In addition to the available texts and tutorials, we recommended the following texts:- Dynamic Modeling of Musculoskeletal Motion - A Vectorized Approach for Biomechanical Analysis in Three Dimensions by Gary T. Yamaguchi
- Dynamics: Theory and Applications by Thomas R. Kane and David A. Levinson