This code package is based on the methods in our paper: "Optimizing the Feature Set and Electrode Configuration of High-Density Electromyogram via Interpretable Deep Forest", published on Biomedical Signal Processing and Control.

If it is useful, please cite our paper.

Data acquisition: https://physionet.org/content/hd-semg/1.0.0/. (Note:we just use pr_dataset)

You can install some of the required package from the requirements.txt

Run:
1.get_feature.py to obtain the features.
2.main_forest to obtain the results.