60 15

Toward a compact hybrid brain-computer interface (BCI): Performance evaluation of multi-class hybrid EEG-fNIRS BCIs with limited number of channels

Title
Toward a compact hybrid brain-computer interface (BCI): Performance evaluation of multi-class hybrid EEG-fNIRS BCIs with limited number of channels
Author
임창환
Keywords
MOTOR IMAGERY; NIRS; CLASSIFICATION; SPECTROSCOPY
Issue Date
2020-04
Publisher
PUBLIC LIBRARY SCIENCE
Citation
PLOS ONE, v. 15, no. 3, article no. e0230491
Abstract
It has been demonstrated that the performance of typical unimodal brain-computer interfaces (BCIs) can be noticeably improved by combining two different BCI modalities. This so-called "hybrid BCI" technology has been studied for decades; however, hybrid BCIs that particularly combine electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) (hereafter referred to as hBCIs) have not been widely used in practical settings. One of the main reasons why hBCI systems are so unpopular is that their hardware is generally too bulky and complex. Therefore, to make hBCIs more appealing, it is necessary to implement a lightweight and compact hBCI system with minimal performance degradation. In this study, we investigated the feasibility of implementing a compact hBCI system with significantly less EEG channels and fNIRS source-detector (SD) pairs, but that can achieve a classification accuracy high enough to be used in practical BCI applications. EEG and fNIRS data were acquired while participants performed three different mental tasks consisting of mental arithmetic, right-hand motor imagery, and an idle state. Our analysis results showed that the three mental states could be classified with a fairly high classification accuracy of 77.6 +/- 12.1% using an hBCI system with only two EEG channels and two fNIRS SD pairs.
URI
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0230491https://repository.hanyang.ac.kr/handle/20.500.11754/165799
ISSN
1932-6203
DOI
10.1371/journal.pone.0230491
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > ELECTRICAL AND BIOMEDICAL ENGINEERING(전기·생체공학부) > Articles
Files in This Item:
Toward a compact hybrid brain-computer interface (BCI) Performance evaluation of multi-class hybrid EEG-fNIRS BCIs with limited number of channels.pdfDownload
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE