Analysis Code: An Extensible Platform for Measurement and Modification of Muscle Engagement During Upper-Limb Robot-Facilitated Rehabilitation (ICORR 2025)

Overview

This folder contains the analysis code associated with the paper titled "An Extensible Platform for Measurement and Modification of Muscle Engagement During Upper-Limb Robot-Facilitated Rehabilitation" submitted to the 2025 IEEE International Conference on Rehabilitation Robotics (ICORR). Code can be used alongside the released data set to generate all associated publication plots and statistical analyses.

License

The data, documentation and associated code is provided as-is; however, we invite anyone who wishes to adapt and use it under a Creative Commons Attribution 4.0 International License. Please cite the following publication if you use this code or data in your research:

@inproceedings{AnandRehabPlatform2025,
  title={An Extensible Platform for Measurement and Modification of Muscle Engagement During Upper-Limb Robot-Facilitated Rehabilitation},
  booktitle = {9th IEEE/RAS-EMBS International Conference on Rehabilitation Robotics ({ICORR})},
  author = {Ajay Anand and Chad A. Berghoff and Carson J. Wynn and Evan Cole Falconer and Gabriel Parra and Jono Jenkens and 
  Caleb J. Thomson and W. Caden Hamrick and Jacob A. George and Laura A. Hallock},
  date = {},
  year = {2025},
  pages={},
  isnn ={},
  doi = {},
  ourl = {},
  urldate = {},
  abstract = {},
  eventtitle = {9th IEEE/RAS-EMBS International Conference on Rehabilitation Robotics ({ICORR})},
  keywords = {rehabilitation robotics, human–robot interaction, biomechanics, surface electromyography (sEMG), user-centered design}
}

Installation

Downloading the Code and Data

To Download all modules and scripts, clone and enter the repository via

git clone [email protected]:hrelab/2025-icorr-analysis.git
cd 2025-icorr-analysis

or download and extract the repository ZIP file.

Next, download the processed_data folder from the released data set and place it in the top-level directory. (Due to GDrive's upload limits, this may require downloading, extracting, and re-merging the folder file tree.)

This will result in the following project structure:

2025-icorr-analysis/
├── LICENSE
├── main.py
├── processed_data/
├── pyproject.toml
├── README.md
├── src/
└── tests/

Setting Up Environment and Dependencies

We recommend running this code inside a Python virtual environment via the following commands. From the 2025-icorr-analysis folder, run:

python -m venv .venv

to create a virtual environment, and then source it via

source .venv/bin/activate # you may need to modify this command for non-Unix (i.e., Windows) systems

Once you've sourced your virtual environment successfully (as indicated by which python pointing inside your new .venv folder and/or (.venv) prepending your command line), install all dependencies from pyproject.toml via

python -m pip install -e .

Usage

Once the file tree and dependencies are set up as specified above, run (from the base 2025-icorr-analysis directory):

python main.py --generate_plots

to generate all plots and write them to the (new, unless previously generated) processed_data_plots directory. These plots should match those included in the data release.

Work In Progress Features

We are currently augmenting the code above with additional tools to allow manipulation and display of individual time-series data trials, both raw and processed. Check back soon for additional functionality, or contact [email protected] and [email protected] for a status update.