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Conference Paper: A hybrid brain-computer interface combining the EEG and NIRS

TitleA hybrid brain-computer interface combining the EEG and NIRS
Authors
KeywordsHybrid BCI
EEG
NIRS
Motor imagery
Blood oxygen
Issue Date2012
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000790
Citation
The 2012 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems (VECIMS 2012), Tianjin, China, 2-4 July 2012. In IEEE VECIMS Proceedings, 2012, p. 159-162 How to Cite?
AbstractCompared to the conventional brain-computer interface (BCI) system, the hybrid BCI provides a more efficient way for the communication between the brain and the external device. The Electroencephalography (EEG) signal and the change of oxygenation in the brain are two prevailing approaches used in the BCI. However, single physiological signal couldn't provide enough information for a satisfied BCI. This paper proposes a hybrid BCI system based on the combination of the EEG signal and the cerebral blood oxygen changes measured by the near-infrared spectroscopy system (NIRS) to detect the state of motor imagery (MI). The result shows that the average recognition rate can achieve above 75.04% and the highest rate 91.11%, which are higher than when only using EEG or NIRS. It suggests that the proposed hybrid BCI system has a good performance in the combination of these two different signals. Further investigation may help develop better BCIs with high accuracy and significant efficiency. © 2012 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/181798
ISBN

 

DC FieldValueLanguage
dc.contributor.authorMa, Len_US
dc.contributor.authorZhang, Len_US
dc.contributor.authorWang, Len_US
dc.contributor.authorXu, Men_US
dc.contributor.authorQi, Hen_US
dc.contributor.authorWan, Ben_US
dc.contributor.authorMing, Den_US
dc.contributor.authorHu, Yen_US
dc.date.accessioned2013-03-19T03:58:17Z-
dc.date.available2013-03-19T03:58:17Z-
dc.date.issued2012en_US
dc.identifier.citationThe 2012 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems (VECIMS 2012), Tianjin, China, 2-4 July 2012. In IEEE VECIMS Proceedings, 2012, p. 159-162en_US
dc.identifier.isbn978-1-4577-1759-8-
dc.identifier.urihttp://hdl.handle.net/10722/181798-
dc.description.abstractCompared to the conventional brain-computer interface (BCI) system, the hybrid BCI provides a more efficient way for the communication between the brain and the external device. The Electroencephalography (EEG) signal and the change of oxygenation in the brain are two prevailing approaches used in the BCI. However, single physiological signal couldn't provide enough information for a satisfied BCI. This paper proposes a hybrid BCI system based on the combination of the EEG signal and the cerebral blood oxygen changes measured by the near-infrared spectroscopy system (NIRS) to detect the state of motor imagery (MI). The result shows that the average recognition rate can achieve above 75.04% and the highest rate 91.11%, which are higher than when only using EEG or NIRS. It suggests that the proposed hybrid BCI system has a good performance in the combination of these two different signals. Further investigation may help develop better BCIs with high accuracy and significant efficiency. © 2012 IEEE.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000790-
dc.relation.ispartofIEEE International Symposium on Virtual Environments, Human-Computer Interfaces and Measurement Systems Proceedingsen_US
dc.rightsIEEE International Symposium on Virtual Environments, Human-Computer Interfaces and Measurement Systems Proceedings. Copyright © IEEE.-
dc.rights©2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectHybrid BCI-
dc.subjectEEG-
dc.subjectNIRS-
dc.subjectMotor imagery-
dc.subjectBlood oxygen-
dc.titleA hybrid brain-computer interface combining the EEG and NIRSen_US
dc.typeConference_Paperen_US
dc.identifier.emailHu, Y: yhud@hku.hken_US
dc.identifier.authorityHu, Y=rp00432en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/VECIMS.2012.6273214-
dc.identifier.scopuseid_2-s2.0-84867977362-
dc.identifier.hkuros213623en_US
dc.identifier.spage159-
dc.identifier.epage162-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 130410-

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