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+Description
+---
+
+This folder contains python scripts and Jupyter notebooks used for modeling and
+simulation of a simplified arm model, that is both kinematicaly and dynamically
+redundant.
+
+Dependencies
+---
+
+The scripts are compatible with python 2. Dependencies can be installed through
+python package manager (pip). The following libraries were used in the project:
+
+- scipy (`pip install scipy`)
+- pydy (`pip install pydy`)
+- numpy (`pip install numpy`)
+- sympy (`pip install sympy`)
+- pandas (`pip install pandas`)
+- seaborn (`pip install seaborn`)
+- matplotlib (`pip install matplotlib`)
+- pycddlib (`pip install pycddlib`)
+- cython
+- tqdm (`pip install tqdm`)
+
+For the feasible muscle space analysis we use the command **convert** from
+imagemagic to collect the results and generate the .gif file.
+
+
+Demos
+---
+
+The user can execute the *main.py* script and choose between the different case
+studies or use the interactive Jupyter notebooks (.ipynb) provided in the
+folder. Folder results contains the results that are generated by the scripts
+and the .html files are read only file based on the Jupyter notebooks.
+
+- [Arm Model](model.ipynb) presents a case study using muscle space
+  projection to study the response of segmental level reflexes
+
+- [Muscle Space Projection](muscle_space_projection.ipynb)
+  demonstrates muscle space projection in the context of segmental level
+  (reflex) modeling
+
+- [Feasible Muscle Forces](feasible_muscle_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