loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Alejandro A. A. Torres-García ; Luis Alfredo Moctezuma and Marta Molinas

Affiliation: Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), Gløshaugen, O. S. Bragstads plass 2, Trondheim, Norway

Keyword(s): EEG Signals, Brain-Computer Interfaces (BCI), Classification, Color Exposure, Idle States, SVM, Random Forest, Discrete Wavelet Transform (DWT), Empirical Mode Decomposition (EMD).

Abstract: Self-paced Brain-Computer Interfaces (BCIs) are desirable for allowing the BCI’s user to control a BCI without a cue to indicate him/her when to send a command or message. As a first step towards a self-paced color-based BCI, we assessed if a machine learning algorithm can learn to distinguish between primary color exposure and idle state. In this paper, we record and analyze the EEG signals from 18 subjects for assessing the feasibility of distinguishing between color exposure and idle states. Specifically, we compare separately the performances obtained in the classification of two different types of idle states (one relaxation-related and another attention-related) and color exposure. We characterize the signals using two different ways based on discrete wavelet transform and Empirical Mode Decomposition (EMD), respectively. We trained and tested two different classifiers, support vector machine (SVM) and random forest. The outcomes provide experimental evidence that a machine lea rning algorithm can distinguish between the two classes (exposure to primary colors and idle states), regardless of the kind of idle state analyzed. The more consistent outcomes were obtained using EMD-based features with accuracies of 92.3% and 91.6% (considering a break and an attention-related task as the idle states). Also, when we discard the epochs’ onset the performances were 91.8% and 94.6%, respectively. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.226.72.194

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
A. Torres-García, A.; Moctezuma, L. and Molinas, M. (2020). Assessing the Impact of Idle State Type on the Identification of RGB Color Exposure for BCI. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIOSIGNALS; ISBN 978-989-758-398-8; ISSN 2184-4305, SciTePress, pages 187-194. DOI: 10.5220/0008923101870194

@conference{biosignals20,
author={Alejandro A. {A. Torres{-}García}. and Luis Alfredo Moctezuma. and Marta Molinas.},
title={Assessing the Impact of Idle State Type on the Identification of RGB Color Exposure for BCI},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIOSIGNALS},
year={2020},
pages={187-194},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008923101870194},
isbn={978-989-758-398-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIOSIGNALS
TI - Assessing the Impact of Idle State Type on the Identification of RGB Color Exposure for BCI
SN - 978-989-758-398-8
IS - 2184-4305
AU - A. Torres-García, A.
AU - Moctezuma, L.
AU - Molinas, M.
PY - 2020
SP - 187
EP - 194
DO - 10.5220/0008923101870194
PB - SciTePress