Adaptive EEG thought pattern classifier for advanced wheelchair control

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dc.contributor.author Craig, Daniel en_US
dc.contributor.author Nguyen, Hung en_US
dc.contributor.editor Clark, J.
dc.contributor.editor Dittmar, A; Clark, J en_US
dc.date.accessioned 2009-11-09T05:36:36Z
dc.date.available 2009-11-09T05:36:36Z
dc.date.issued 2007 en_US
dc.identifier 2007000027 en_US
dc.identifier.citation Craig Daniel and Nguyen Hung 2007, 'Adaptive EEG thought pattern classifier for advanced wheelchair control', IEEE, Lyon, France, pp. 2544-2547. en_US
dc.identifier.issn 1-4244-0788-5 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/2765
dc.description.abstract This paper presents a real-time Electroencephalogram (EEG) classification system, with the goal of enhancing the control of a head-movement controlled power wheelchair for patients with chronic Spinal Cord Injury (SCI). Using a 32 channel recording device, mental command data was collected from 10 participants. This data was used to classify three different mental commands, to supplement the five commands already available using head movement control. Of the 32 channels that were recorded only 4 were used in the classification, achieving an average classification rate of 82%. This paper also demonstrates that there is an advantage to be gained by doing adaptive training of the classifier. That is, customizing the classifier to a person previously unseen by the classifier caused their average recognition rates to improve from 52.5% up to 77.5%. en_US
dc.publisher IEEE en_US
dc.relation.isbasedon http://dx.doi.org/10.1109/IEMBS.2007.4352847 en_US
dc.title Adaptive EEG thought pattern classifier for advanced wheelchair control en_US
dc.parent Proceedings of the 29th International Conference of the IEEE Engineering in Medicine and Biology Society en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Lyon, France en_US
dc.identifier.startpage 2544 en_US
dc.identifier.endpage 2547 en_US
dc.cauo.name FEIT. A/DRsch Ctre for Health Technologies en_US
dc.conference Verified OK en_US
dc.conference.location Lyon, France en_US
dc.for 090300 en_US
dc.personcode 930162 en_US
dc.personcode 840115 en_US
dc.percentage 100 en_US
dc.classification.name Biomedical Engineering en_US
dc.classification.type FOR-08 en_US
dc.custom IEEE Engineering in Medicine and Biology Society Annual Conference en_US
dc.date.activity 20070823 en_US
dc.location.activity Lyon, France en_US
dc.description.keywords EEG Classifier, wheelchair control, thought pattern en_US
dc.staffid 840115 en_US


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