#+TITLE: Modeling musculoskeletal kinematic and dynamic redundancy using null space projection
#+AUTHOR: Dimitar Stanev
#+EMAIL: stanev@ece.upatras.gr
#+OPTIONS: email:t date:nil toc:nil \n:nil num:nil
#+LATEX_HEADER: \usepackage{fullpage}
#+LATEX_HEADER: \usepackage{parskip}

* Overview

  This repository contains the setup scripts, documentation and source code
  relevant to the publication "D. Stanev and Konstantinos Moustakas, Modeling
  musculoskeletal kinematic and dynamic redundancy using null space projection,
  PLoS ONE, 14(1): e0209171, Jan. 2019, DOI:
  https://doi.org/10.1371/journal.pone.0209171".

* How to run the Docker image

  In order to provide a portable setup on which the published simulations and
  analyses can be interactively reviewed, modified and executed, the provided
  environment is built as a Docker image. Docker is available a multitude of
  platforms and detailed installation instructions are provided as [[https://docs.docker.com/install/][part of the
  project's online documentation]]. After installation, switch to the toplevel
  directory of this repository and build the docker image:
  #+BEGIN_SRC bash :exports code
docker build -t ubuntu_opensim_stanev .
  #+END_SRC
  You can change the name of the image (here =ubuntu_opensim_stanev=) to your
  liking. After building, which should take a few minutes, the image can be run
  in a container with the following command:
  #+BEGIN_SRC bash :exports code
docker run -it -p 4000:80 ubuntu_opensim_stanev
  #+END_SRC
  The =-it= option instructs =docker= to run in interactive terminal mode, while
  the =-p 4000:80= option bind the port 80 of the image to the port 4000 of the
  localhost. Of course, the image name should match the one used in the build
  command and the port 4000 can be substituted with any available port on the
  localhost. After running the docker, open [[http://localhost:4000]] in your
  browser and fill in the string 'stanev' (without the quotes) in the password
  prompt.

* Demos

  The user can navigate into the corresponding folders and inspect the source
  code. The following case studies are provided in the form of interactive
  Jupyter notebooks:

- *arm\under{}model/model.ipynb* presents a case study using muscle space
  projection to study the response of segmental level reflexes

- *arm\under{}model/muscle\under{}space\underprojection.ipynb* demonstrates
  muscle space projection in the context of segmental level (reflex) modeling

- *arm\under{}model/feasible\under{}muscle\under{}forces.ipynb* uses task space
  projection to simulate a simple hand movement, where the feasible muscle
  forces that satisfy this task are calculated and analyzed

- *feasible\under{}joint\under{}reaction\under{}loads/python/feasible\under{}joint\under{}reaction\under{}loads.ipynb*
  demonstrates the utilization of the feasible muscle forces to calculate the
  bounds of the joint reaction loads during walking

The .html files corresponding to the .ipynb notebooks included in the folders
contain the pre-executed results of the demos.