Enhanced performance by a hybrid NIRS-EEG brain computer interface
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Klaus-Robert Muller | - |
dc.contributor.author | Siamac Fazli | - |
dc.date.accessioned | 2021-09-03T09:52:31Z | - |
dc.date.available | 2021-09-03T09:52:31Z | - |
dc.date.created | 2021-06-21 | - |
dc.date.issued | 2012-01 | - |
dc.identifier.issn | 1053-8119 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/84562 | - |
dc.description.abstract | Noninvasive Brain Computer Interfaces (BCI) have been promoted to be used for neuroprosthetics. However, reports on applications with electroencephalography (EEG) show a demand for a better accuracy and stability. Here we investigate whether near-infrared spectroscopy (NIRS) can be used to enhance the EEG approach. In our study both methods were applied simultaneously in a real-time Sensory Motor Rhythm (SMR)-based BCI paradigm, involving executed movements as well as motor imagery. We tested how the classification of NIRS data can complement ongoing real-time EEG classification. Our results show that simultaneous measurements of NIRS and EEG can significantly improve the classification accuracy of motor imagery in over 90% of considered subjects and increases performance by 5% on average (p<0:01). However, the long time delay of the hemodynamic response may hinder an overall increase of bit-rates. Furthermore we find that EEG and NIRS complement each other in terms of information content and are thus a viable multimodal imaging technique, suitable for BCI. (C) 2011 Elsevier Inc. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ACADEMIC PRESS INC ELSEVIER SCIENCE | - |
dc.title | Enhanced performance by a hybrid NIRS-EEG brain computer interface | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Klaus-Robert Muller | - |
dc.contributor.affiliatedAuthor | Siamac Fazli | - |
dc.identifier.bibliographicCitation | NEUROIMAGE, v.59, pp.519 - 529 | - |
dc.relation.isPartOf | NEUROIMAGE | - |
dc.citation.title | NEUROIMAGE | - |
dc.citation.volume | 59 | - |
dc.citation.startPage | 519 | - |
dc.citation.endPage | 529 | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | Combined NIRS-EEG | - |
dc.subject.keywordAuthor | Hybrid BCI | - |
dc.subject.keywordAuthor | Meta-classifier | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.