A Type of EEG-ITNet for Motor Imagery EEG Signal Classification

Maryam Khoshkhooy Titkanlou, Ehsan Monjezi, Roman Mouček

2024

Abstract

The brain-computer interface (BCI) is an emerging technology that has the potential to revolutionize the world, with numerous applications ranging from healthcare to human augmentation. Electroencephalogram (EEG) motor imagery (MI) is among the most common BCI paradigms used extensively in healthcare applications such as rehabilitation. Recently, neural networks, particularly deep architectures, have received substantial attention for analyzing EEG signals (BCI applications). EEG-ITNet is a classification algorithm proposed to improve the classification accuracy of motor imagery EEG signals in a noninvasive brain-computer interface. The resulting EEG-ITNet classification accuracy and precision were 75.45% and 76.43%, using a motor imagery dataset of 29 healthy subjects, including males aged 21-26 and females aged 18-23. Three different methods have also been implemented to augment this dataset.

Paper Citation

in Harvard Style

Khoshkhooy Titkanlou M., Monjezi E. and Mouček R. (2024). A Type of EEG-ITNet for Motor Imagery EEG Signal Classification. In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-688-0, SciTePress, pages 257-262. DOI: 10.5220/0012569400003657

in Bibtex Style

@conference{healthinf24,
author={Maryam Khoshkhooy Titkanlou and Ehsan Monjezi and Roman Mouček},
title={A Type of EEG-ITNet for Motor Imagery EEG Signal Classification},
booktitle={Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2024},
pages={257-262},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012569400003657},
isbn={978-989-758-688-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - A Type of EEG-ITNet for Motor Imagery EEG Signal Classification
SN - 978-989-758-688-0
AU - Khoshkhooy Titkanlou M.
AU - Monjezi E.
AU - Mouček R.
PY - 2024
SP - 257
EP - 262
DO - 10.5220/0012569400003657
PB - SciTePress