Multi-subject Identification of Hand Movements Using Machine Learning

This repository contains the data and source code employed during our research; the ZIP file 'EMG_data_for_gestures-master.zip' contains raw data as available in UCI Machine Learning Repository and the Jupyter Notebook 'Multi-subject Identification of Hand Movements Using Machine Learning.ipynb' contains the source code.

Citing

If you use our project for your research or if you find this paper and repository helpful, please consider citing the work:

Mora-Rubio A. et al. (2022) Multi-subject Identification of Hand Movements Using Machine Learning. In: Corchado J.M., Trabelsi S. (eds) Sustainable Smart Cities and Territories. SSCTIC 2021. Lecture Notes in Networks and Systems, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-030-78901-5_11

@InProceedings{10.1007/978-3-030-78901-5_11,
author="Mora-Rubio, Alejandro
and Alzate-Grisales, Jesus Alejandro
and Arias-Garz{\'o}n, Daniel
and Buritic{\'a}, Jorge Iv{\'a}n Padilla
and Var{\'o}n, Cristian Felipe Jim{\'e}nez
and Bravo-Ortiz, Mario Alejandro
and Arteaga-Arteaga, Harold Brayan
and Hassaballah, Mahmoud
and Orozco-Arias, Simon
and Isaza, Gustavo
and Tabares-Soto, Reinel",
editor="Corchado, Juan M.
and Trabelsi, Saber",
title="Multi-subject Identification of Hand Movements Using Machine Learning",
booktitle="Sustainable Smart Cities and Territories",
year="2022",
publisher="Springer International Publishing",
address="Cham",
pages="117--128"
}

This paper was published as a journal paper in Springer International Publishing. (Webpage)