Classification of mental arithmetic and resting-state based on Ear-EEG

Soo-In Choi, G. Choi, Hyung-Tak Lee, Han-Jeong Hwang, Jaeyoung Shin
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引用次数: 12

Abstract

Electroencephalography (EEG) has been mainly utilized for developing brain-computer interface (BCI) systems. In recent, use of Ear-EEG measured around the ears has been proposed to enhance the practicality of conventional EEG-based BCI systems. Most of BCI systems based on Ear-EEG have used exogenous BCI paradigms employing external stimuli. In this study, we investigated the feasibility of using Ear-EEG in developing an endogenous BCI system that uses self-modulated brain signals. EEG data was measured while subjects performed mental arithmetic (MA) and baseline (BL) task. EEG data analysis was performed after dividing the whole brain area into four regions of interest (frontal, central, occipital, and ear area) to compare their EEG characteristics and classification performance. Similar event-related (de)synchronization (ERD/ERS) patterns were observed between the four ROIs, and classification performance was insignificant between them, except occipital area (frontal: 72.6 %, central: 76.7 %, occipital: 82.6 % and ear: 75.6 %). From the results, we could confirm the possibility of using Ear-EEG for developing an endogenous BCI system.
基于耳脑电图的心算分类与静息状态
脑电图(EEG)主要用于开发脑机接口(BCI)系统。近年来,为了提高传统的基于脑电图的脑机接口(BCI)系统的实用性,人们提出了使用耳朵周围测量的脑电图(Ear-EEG)。基于耳-脑电图的脑机接口系统大多采用外源性脑机接口模式。在这项研究中,我们研究了使用Ear-EEG开发内源性脑机接口系统的可行性,该系统使用自调制脑信号。在受试者执行心算和基线任务时测量脑电数据。将整个脑区划分为4个感兴趣的脑区(额区、中枢区、枕区和耳区),对EEG数据进行分析,比较其EEG特征和分类性能。4个roi之间的事件相关(de)同步(ERD/ERS)模式相似,除枕区(额区:72.6%,中央区:76.7%,枕区:82.6%,耳区:75.6%)外,其余4个roi之间的分类表现不显著。从结果来看,我们可以证实利用Ear-EEG开发内源性脑机接口系统的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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