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Conference Paper: Brain-computer interfaces based on attention and complex mental tasks
Title | Brain-computer interfaces based on attention and complex mental tasks |
---|---|
Authors | |
Keywords | Adhd Rehabilitation Brain-Computer Interface Mental Tasks Neurofeedback |
Issue Date | 2007 |
Publisher | Springer 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? |
Abstract | Brain-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 Identifier | http://hdl.handle.net/10722/176249 |
ISSN | 2023 SCImago Journal Rankings: 0.606 |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, J | en_US |
dc.contributor.author | Yan, N | en_US |
dc.contributor.author | Liu, H | en_US |
dc.contributor.author | Liu, M | en_US |
dc.contributor.author | Tai, C | en_US |
dc.date.accessioned | 2012-11-26T09:07:55Z | - |
dc.date.available | 2012-11-26T09:07:55Z | - |
dc.date.issued | 2007 | en_US |
dc.identifier.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 | en_US |
dc.identifier.issn | 0302-9743 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/176249 | - |
dc.description.abstract | Brain-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.language | eng | en_US |
dc.publisher | Springer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/ | en_US |
dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | en_US |
dc.subject | Adhd Rehabilitation | en_US |
dc.subject | Brain-Computer Interface | en_US |
dc.subject | Mental Tasks | en_US |
dc.subject | Neurofeedback | en_US |
dc.title | Brain-computer interfaces based on attention and complex mental tasks | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Yan, N: nyan@hku.hk | en_US |
dc.identifier.authority | Yan, N=rp00978 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.scopus | eid_2-s2.0-38149085929 | en_US |
dc.identifier.hkuros | 183219 | - |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-38149085929&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 4561 LNCS | en_US |
dc.identifier.spage | 467 | en_US |
dc.identifier.epage | 473 | en_US |
dc.publisher.place | Germany | en_US |
dc.identifier.scopusauthorid | Wang, J=15066366300 | en_US |
dc.identifier.scopusauthorid | Yan, N=7102919410 | en_US |
dc.identifier.scopusauthorid | Liu, H=25634105600 | en_US |
dc.identifier.scopusauthorid | Liu, M=22835742800 | en_US |
dc.identifier.scopusauthorid | Tai, C=7202900517 | en_US |
dc.identifier.issnl | 0302-9743 | - |