File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/VECIMS.2012.6273214
- Scopus: eid_2-s2.0-84867977362
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Conference Paper: A hybrid brain-computer interface combining the EEG and NIRS
Title | A hybrid brain-computer interface combining the EEG and NIRS |
---|---|
Authors | |
Keywords | Hybrid BCI EEG NIRS Motor imagery Blood oxygen |
Issue Date | 2012 |
Publisher | IEEE. 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 Conference Proceedings, 2012, p. 159-162 How to Cite? |
Abstract | Compared 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 Identifier | http://hdl.handle.net/10722/181798 |
ISBN |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ma, L | en_US |
dc.contributor.author | Zhang, L | en_US |
dc.contributor.author | Wang, L | en_US |
dc.contributor.author | Xu, M | en_US |
dc.contributor.author | Qi, H | en_US |
dc.contributor.author | Wan, B | en_US |
dc.contributor.author | Ming, D | en_US |
dc.contributor.author | Hu, Y | en_US |
dc.date.accessioned | 2013-03-19T03:58:17Z | - |
dc.date.available | 2013-03-19T03:58:17Z | - |
dc.date.issued | 2012 | en_US |
dc.identifier.citation | The 2012 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems (VECIMS 2012), Tianjin, China, 2-4 July 2012. In Conference Proceedings, 2012, p. 159-162 | en_US |
dc.identifier.isbn | 978-1-4577-1759-8 | - |
dc.identifier.uri | http://hdl.handle.net/10722/181798 | - |
dc.description.abstract | Compared 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.language | eng | en_US |
dc.publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000790 | - |
dc.relation.ispartof | Proceedings of IEEE International Symposium on Virtual Environments, Human-Computer Interfaces & Measurement Systems, VECIMS 2012 | en_US |
dc.subject | Hybrid BCI | - |
dc.subject | EEG | - |
dc.subject | NIRS | - |
dc.subject | Motor imagery | - |
dc.subject | Blood oxygen | - |
dc.title | A hybrid brain-computer interface combining the EEG and NIRS | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Hu, Y: yhud@hku.hk | en_US |
dc.identifier.authority | Hu, Y=rp00432 | en_US |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/VECIMS.2012.6273214 | - |
dc.identifier.scopus | eid_2-s2.0-84867977362 | - |
dc.identifier.hkuros | 213623 | en_US |
dc.identifier.spage | 159 | - |
dc.identifier.epage | 162 | - |
dc.publisher.place | United States | - |
dc.customcontrol.immutable | sml 130410 | - |