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Conference Paper: Brain-computer interface technique for electro-acupuncture stimulation control

TitleBrain-computer interface technique for electro-acupuncture stimulation control
Authors
KeywordsBrain-computer interface
Electro-acupuncture stimulation
Event related desynchronization
Imaginary movement
Mahalanobis classifier
Issue Date2010
PublisherIEEE.
Citation
The 2010 IEEE International Conference on Virtual Environments Human-Computer Interfaces and Measurement Systems (VECIMS), Taranto, Apulia, Italy, 6-8 September 2010. In Proceedings of the IEEE-VECIMS, , 2010, p. 33-37 How to Cite?
Abstract
Electro-acupuncture stimulation (EAS) technique applies the electrical nerve stimulation therapy on traditional acupuncture points to restore the muscle tension. The rapid rise and development of brain-computer interface (BCI) technology makes the thought-control of EAS possible. This paper designed a new BCI-controls-EAS (BCICEAS) system by using event related desynchronization (ERD) of EEG signal evoked by imaginary movement. The Fisher parameters were extracted from feature frequency bands of EEG and classified into EAS control commands by Mahalanobis Classifier. A feedback training technique was introduced to enhance the signal feature through a visual feedback interface with a virtual liquid column, which height varied along with EEG power spectral feature. Experimental results demonstrated the validity of the proposed method, including the effective improvement of feedback training on signal feature and reliable control of EAS. It is hoped the BCICEAS can explore a new way for EAS system design and help people who sufferers with severe movement dysfunction. © 2010 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/142877
ISBN
References

 

Author Affiliations
  1. The University of Hong Kong
  2. Tianjin University
DC FieldValueLanguage
dc.contributor.authorMing, Den_HK
dc.contributor.authorBai, Yen_HK
dc.contributor.authorLiu, Xen_HK
dc.contributor.authorAn, Xen_HK
dc.contributor.authorQi, Hen_HK
dc.contributor.authorWan, Ben_HK
dc.contributor.authorHu, Yen_HK
dc.contributor.authorLuk, KDKen_HK
dc.date.accessioned2011-10-28T02:57:58Z-
dc.date.available2011-10-28T02:57:58Z-
dc.date.issued2010en_HK
dc.identifier.citationThe 2010 IEEE International Conference on Virtual Environments Human-Computer Interfaces and Measurement Systems (VECIMS), Taranto, Apulia, Italy, 6-8 September 2010. In Proceedings of the IEEE-VECIMS, , 2010, p. 33-37en_US
dc.identifier.isbn978-1-4244-5905-6en_US
dc.identifier.urihttp://hdl.handle.net/10722/142877-
dc.description.abstractElectro-acupuncture stimulation (EAS) technique applies the electrical nerve stimulation therapy on traditional acupuncture points to restore the muscle tension. The rapid rise and development of brain-computer interface (BCI) technology makes the thought-control of EAS possible. This paper designed a new BCI-controls-EAS (BCICEAS) system by using event related desynchronization (ERD) of EEG signal evoked by imaginary movement. The Fisher parameters were extracted from feature frequency bands of EEG and classified into EAS control commands by Mahalanobis Classifier. A feedback training technique was introduced to enhance the signal feature through a visual feedback interface with a virtual liquid column, which height varied along with EEG power spectral feature. Experimental results demonstrated the validity of the proposed method, including the effective improvement of feedback training on signal feature and reliable control of EAS. It is hoped the BCICEAS can explore a new way for EAS system design and help people who sufferers with severe movement dysfunction. © 2010 IEEE.en_HK
dc.languageengen_US
dc.publisherIEEE.en_US
dc.relation.ispartofVECIMS 2010 - 2010 IEEE International Conference on Virtual Environments, Human-Computer Interfaces and Measurement Systems, Proceedingsen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsIEEE International Conference on Virtual Environments, Human-Computer Interfaces and Measurements Systems Proceedings. Copyright © IEEE.-
dc.rights©2010 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.subjectBrain-computer interfaceen_HK
dc.subjectElectro-acupuncture stimulationen_HK
dc.subjectEvent related desynchronizationen_HK
dc.subjectImaginary movementen_HK
dc.subjectMahalanobis classifieren_HK
dc.titleBrain-computer interface technique for electro-acupuncture stimulation controlen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=978-1-4244-5904-9&volume=&spage=33&epage=37&date=2010&atitle=Brain-computer+interface+technique+for+electro-acupuncture+stimulation+controlen_US
dc.identifier.emailHu, Y:yhud@hku.hken_HK
dc.identifier.emailLuk, KDK:hcm21000@hku.hken_HK
dc.identifier.authorityHu, Y=rp00432en_HK
dc.identifier.authorityLuk, KDK=rp00333en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/VECIMS.2010.5609342en_HK
dc.identifier.scopuseid_2-s2.0-78650122411en_HK
dc.identifier.hkuros197086en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78650122411&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage33en_HK
dc.identifier.epage37en_HK
dc.description.otherThe 2010 IEEE International Conference on Virtual Environments Human-Computer Interfaces and Measurement Systems (VECIMS), Taranto, Apulia, Italy, 6-8 September 2010. In Proceedings of the IEEE-VECIMS, , 2010, p. 33-37-
dc.identifier.scopusauthoridMing, D=9745824400en_HK
dc.identifier.scopusauthoridBai, Y=35108689200en_HK
dc.identifier.scopusauthoridLiu, X=35109400600en_HK
dc.identifier.scopusauthoridAn, X=35975600200en_HK
dc.identifier.scopusauthoridQi, H=7202348852en_HK
dc.identifier.scopusauthoridWan, B=7102316798en_HK
dc.identifier.scopusauthoridHu, Y=7407116091en_HK
dc.identifier.scopusauthoridLuk, KDK=7201921573en_HK

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