EEG Motor Imagery Classification using Fusion Convolutional Neural Network

Wassim Zouch, Amira Echtioui

2022

Abstract

Brain-Computer Interfaces (BCIs) are systems that can help people with limited motor skills interact with their environment without the need for outside help. Therefore, the signal is representative of a motor area in the active brain system. It is used to recognize MI-EEG tasks via a deep learning techniques such as Convolutional Neural Network (CNN), which poses a potential problem in maintaining the integrity of frequency-time-space information and then the need for exploring the CNNs fusion. In this work, we propose a method based on the fusion of three CNN (3CNNs). Our proposed method achieves an interesting precision, recall, F1-score, and accuracy of 61.88%, 62.50%, 61.47%, 64.75% respectively when tested on the 9 subjects from the BCI Competition IV 2a dataset. The 3CNNs model achieved higher results compared to the state-of-the-art.

Paper Citation

in Harvard Style

Zouch W. and Echtioui A. (2022). EEG Motor Imagery Classification using Fusion Convolutional Neural Network. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: SDMIS, ISBN 978-989-758-547-0, pages 548-553. DOI: 10.5220/0010975600003116

in Bibtex Style

@conference{sdmis22,
author={Wassim Zouch and Amira Echtioui},
title={EEG Motor Imagery Classification using Fusion Convolutional Neural Network},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: SDMIS,},
year={2022},
pages={548-553},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010975600003116},
isbn={978-989-758-547-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: SDMIS,
TI - EEG Motor Imagery Classification using Fusion Convolutional Neural Network
SN - 978-989-758-547-0
AU - Zouch W.
AU - Echtioui A.
PY - 2022
SP - 548
EP - 553
DO - 10.5220/0010975600003116