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Conference Paper: Brain-computer interfaces based on attention and complex mental tasks

TitleBrain-computer interfaces based on attention and complex mental tasks
Authors
KeywordsAdhd Rehabilitation
Brain-Computer Interface
Mental Tasks
Neurofeedback
Issue Date2007
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
Lecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2007, v. 4561 LNCS, p. 467-473 How to Cite?
AbstractBrain-Computer Interface (BCI) technology is widely used in rehabilitation field. There are two main applications of BCI systems in assistive technology: regain the movements or communications for people with motor disability and neurofeedback for training the subject to emit a specific brain activity. In this study, we introduce two typical applications of BCI systems in our lab. For the first case, the BCI system based on mental tasks classification for people with motor disability is described. An effective features extraction and classification methods of EEG signals were proposed. For the second case, a neurofeedback (NFB) system was established, which utilized Virtual Reality (VR) to create appropriate feedback information which is more interesting, imaginative and interactive than traditional graphical presentations. Visual & auditory (IVA)-continuous performance test (CPT) results show that it can provide an effective therapy for treating attention deficit hyperactivity disorder (ADHD) children. © Springer-Verlag Berlin Heidelberg 2007.
Persistent Identifierhttp://hdl.handle.net/10722/176249
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorWang, Jen_US
dc.contributor.authorYan, Nen_US
dc.contributor.authorLiu, Hen_US
dc.contributor.authorLiu, Men_US
dc.contributor.authorTai, Cen_US
dc.date.accessioned2012-11-26T09:07:55Z-
dc.date.available2012-11-26T09:07:55Z-
dc.date.issued2007en_US
dc.identifier.citationLecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2007, v. 4561 LNCS, p. 467-473en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/10722/176249-
dc.description.abstractBrain-Computer Interface (BCI) technology is widely used in rehabilitation field. There are two main applications of BCI systems in assistive technology: regain the movements or communications for people with motor disability and neurofeedback for training the subject to emit a specific brain activity. In this study, we introduce two typical applications of BCI systems in our lab. For the first case, the BCI system based on mental tasks classification for people with motor disability is described. An effective features extraction and classification methods of EEG signals were proposed. For the second case, a neurofeedback (NFB) system was established, which utilized Virtual Reality (VR) to create appropriate feedback information which is more interesting, imaginative and interactive than traditional graphical presentations. Visual & auditory (IVA)-continuous performance test (CPT) results show that it can provide an effective therapy for treating attention deficit hyperactivity disorder (ADHD) children. © Springer-Verlag Berlin Heidelberg 2007.en_US
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_US
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
dc.subjectAdhd Rehabilitationen_US
dc.subjectBrain-Computer Interfaceen_US
dc.subjectMental Tasksen_US
dc.subjectNeurofeedbacken_US
dc.titleBrain-computer interfaces based on attention and complex mental tasksen_US
dc.typeConference_Paperen_US
dc.identifier.emailYan, N: nyan@hku.hken_US
dc.identifier.authorityYan, N=rp00978en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-38149085929en_US
dc.identifier.hkuros183219-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-38149085929&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume4561 LNCSen_US
dc.identifier.spage467en_US
dc.identifier.epage473en_US
dc.publisher.placeGermanyen_US
dc.identifier.scopusauthoridWang, J=15066366300en_US
dc.identifier.scopusauthoridYan, N=7102919410en_US
dc.identifier.scopusauthoridLiu, H=25634105600en_US
dc.identifier.scopusauthoridLiu, M=22835742800en_US
dc.identifier.scopusauthoridTai, C=7202900517en_US

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