Skip to content

"User Training with Error Augmentation for Electromyogram-based Gesture Classification"

License

Notifications You must be signed in to change notification settings

neu-spiral/emg-feedback-user-training

Repository files navigation

Code for "User Training with Error Augmentation for Electromyogram-based Gesture Classification" by Yunus Bicer, Niklas Smedemark-Margulies, Basak Celik, Elifnur Sunger, Ryan Orendorff, Stephanie Naufel, Tales Imbiriba, Deniz Erdo˘gmus¸, Eugene Tunik, and Mathew Yarossi

Setup and Usage

Use make to create python environment, install dependencies, and install pre-commit hooks.

To reproduce our experiments and analysis:

  1. Unzip the included dataset (see below for dataset details):
unzip dataset.zip
  1. Run analyses and generate figures:
source venv/bin/activate
python emg_feedback_user_training/main.py

Dataset

Included in the repo is a file dataset.zip containing the dataset used for our analyses.

Subjects are organized into folders based on the experiment group they were assigned to (Control, Veridical, and Modified) Each subject's folder contains 3 subfolders: calibration, instructed_games and free_games, corresponding to 3 blocks of the experiment.

  • calibration contains features, labels, and pre-trained weights for a model trained after this block.
  • instructed_games contains the same as calibration.
  • free_games contains the same, plus the length of each game in moves (since user planning and model decisions could affect these outcomes) and predicted probabilities computed for each move.

Random seed was not controlled when training models during the experiments; thus we include pre-trained model weights to ensure reproducibility.

Gestures are labeled with an integer, corresponding to these 9 possible classes: ["Up", "Thumb", "Right", "Pinch", "Down", "Fist", "Left", "Open", "Rest"]

For details on feature extraction, see the paper.

PDF

To read our paper, see: https://ieeexplore.ieee.org/document/10457576

Citation

If you use this code or dataset, please cite our paper:

@article{bicer_2024,
  author={
    Bicer, Yunus and
    Smedemark-Margulies, Niklas and
    Celik, Basak and
    Sunger, Elifnur and
    Orendorff, Ryan and
    Naufel, Stephanie and
    Imbiriba, Tales and
    Erdoğmuş, Deniz and
    Tunik, Eugene and
    Yarossi, Mathew
    },
  journal={IEEE Transactions on Neural Systems and Rehabilitation Engineering}, 
  title={User Training With Error Augmentation for sEMG-Based Gesture Classification}, 
  year={2024},
  doi={10.1109/TNSRE.2024.3372512}
}

About

"User Training with Error Augmentation for Electromyogram-based Gesture Classification"

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published