File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Non-invasive EEG based mental state identification using nonlinear combination

TitleNon-invasive EEG based mental state identification using nonlinear combination
Authors
Issue Date2013
Citation
2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013, 2013, p. 2160-2165 How to Cite?
AbstractNon-invasive EEGs are very useful in human-machine integration development and medical diagnosis. Mental state, especially mental fatigue, is one of the main causes of the tragic accidents. In order to prevent accidents caused by mental fatigue, it is crucial to identify such mental state. Based on the mental state, the human-machine systems would obtain beneficial effects for reducing their accident rate. Using non-invasive EEG recordings, the features of EEG are extracted based on nonlinear combination among EEG four frequency components. The index of mental state can be represented by a polynomial equation. The method is more flexible and provides a quantitative analysis way to acquire the more accurate mental state. The effectiveness of the method is well demonstrated through experimental results. © 2013 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/213397

 

DC FieldValueLanguage
dc.contributor.authorChen, Feng-
dc.contributor.authorJia, Yunyi-
dc.contributor.authorXi, Ning-
dc.date.accessioned2015-07-28T04:07:09Z-
dc.date.available2015-07-28T04:07:09Z-
dc.date.issued2013-
dc.identifier.citation2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013, 2013, p. 2160-2165-
dc.identifier.urihttp://hdl.handle.net/10722/213397-
dc.description.abstractNon-invasive EEGs are very useful in human-machine integration development and medical diagnosis. Mental state, especially mental fatigue, is one of the main causes of the tragic accidents. In order to prevent accidents caused by mental fatigue, it is crucial to identify such mental state. Based on the mental state, the human-machine systems would obtain beneficial effects for reducing their accident rate. Using non-invasive EEG recordings, the features of EEG are extracted based on nonlinear combination among EEG four frequency components. The index of mental state can be represented by a polynomial equation. The method is more flexible and provides a quantitative analysis way to acquire the more accurate mental state. The effectiveness of the method is well demonstrated through experimental results. © 2013 IEEE.-
dc.languageeng-
dc.relation.ispartof2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013-
dc.titleNon-invasive EEG based mental state identification using nonlinear combination-
dc.typeConference_Paper-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ROBIO.2013.6739789-
dc.identifier.scopuseid_2-s2.0-84898796159-
dc.identifier.spage2160-
dc.identifier.epage2165-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats