Prediction of Event Related Potential Speller Performance Using Resting-State EEG
Abstract
Event-related potential (ERP) speller can be utilized in device control and communication for locked-in or severely injured patients. However, problems such as inter-subject performance instability and ERP-illiteracy are still unresolved. Therefore, it is necessary to predict classification performance before performing an ERP speller in order to use it efficiently. In this study, we investigated the correlations with ERP speller performance using a resting-state before an ERP speller. In specific, we used spectral power and functional connectivity according to four brain regions and five frequency bands. As a result, the delta power in the frontal region and functional connectivity in the delta, alpha, gamma bands are significantly correlated with the ERP speller performance. Also, we predicted the ERP speller performance using EEG features in the resting-state. These findings may contribute to investigating the ERP-illiteracy and considering the appropriate alternatives for each user.
Cite
@article{arxiv.2005.01325,
title = {Prediction of Event Related Potential Speller Performance Using Resting-State EEG},
author = {Gi-Hwan Shin and Minji Lee and Hyeong-Jin Kim and Seong-Whan Lee},
journal= {arXiv preprint arXiv:2005.01325},
year = {2020}
}
Comments
Accepted to IEEE EMBC 2020