EPFL deep learning model (DLM) to predict glenogumeral joint force components in scapula coordinate system

This DLM was developed at the EPFL by Pezhman Eghbalishamsabadi. It is implemented in Python.

Getting Started

The following instructions will get you a copy of the project locally.

• Clone the repository locally
• Open the .ipynb file with jupyter (lab or notebook) or google colab.
• Put the model.h5 file in the same directory (upload the file in the case of using google colab).

If you are using google colab you can follow the notebook, otherwise you need to install the libraries. https://www.tensorflow.org/install

https://scikit-learn.org/stable/install.html

Prerequisites

The model is coded with Python 3.10 and tensorflow 2.12.0.

• 1. Authors
• Pezhman Eghbalishamsabadi (EPFL-LBO).

• 1. Contributors
• Léa Pistorius (EPFL-LBO): performed first automatic simulation of the virtual subjects and developed a machine learning model to predict the glenohumeral joint force magnitude.
• Alexandre Terrier (EPFL-LBO): biomechanical supervision

License

This should be discussed with Technology Transfer office (TTO) of EPFL

Acknowledgments

The project was financially supported by the Swiss National Science Foundation (SNSF)

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