Assessing the Impact of Idle State Type on the Identification of RGB Color Exposure for BCI

Alejandro Torres-García, Luis Moctezuma, Marta Molinas

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 learning 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.

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Paper Citation


in Harvard Style

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 - Volume 4: BIOSIGNALS, ISBN 978-989-758-398-8, pages 187-194. DOI: 10.5220/0008923101870194


in Bibtex Style

@conference{biosignals20,
author={Alejandro Torres-García and Luis 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 - Volume 4: BIOSIGNALS,},
year={2020},
pages={187-194},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008923101870194},
isbn={978-989-758-398-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS,
TI - Assessing the Impact of Idle State Type on the Identification of RGB Color Exposure for BCI
SN - 978-989-758-398-8
AU - Torres-García A.
AU - Moctezuma L.
AU - Molinas M.
PY - 2020
SP - 187
EP - 194
DO - 10.5220/0008923101870194