Electrode subset selection methods for an EEG-based P300 brain-computer interface.
Purpose: An electroencephalography (EEG)-based P300 speller is a type of brain-computer interface (BCI) that uses EEG to allow a user to select characters without physical movement. In general, using fewer electrodes for such a system makes it easier to set up and less expensive. This study addresse...
| Publicado en: | Disability & Rehabilitation: Assistive Technology Vol. 10; no. 3; pp. 216 - 221 |
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| Autores principales: | , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
May2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103776695&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103776695 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17483107 1X04 jtl: Disability & Rehabilitation: Assistive Technology issn: 17483107 maglogo: Y pubinfo: dt: May2015 vid: 10 iid: 3 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 103776695 101602421 10.3109/17483107.2014.884174 NLM24506528 103776695 ppf: 216 ppct: 5 formats: fmt: @attributes: type: P tig: atl: Electrode subset selection methods for an EEG-based P300 brain-computer interface. aug: au: McCann, Michael T. Thompson, David E. Syed, Zeeshan H. Huggins, Jane E. affil: Department of Biomedical Engineering, University of Michigan Ann Arbor, MI USA sug: subj: Electroencephalography Brain-Computer Interfaces Electrodes Human Funding Source Equipment Design Male Female Adult Descriptive Statistics Repeated Measures Analysis of Variance Adult: 19-44 years Male Female ab: Purpose: An electroencephalography (EEG)-based P300 speller is a type of brain-computer interface (BCI) that uses EEG to allow a user to select characters without physical movement. In general, using fewer electrodes for such a system makes it easier to set up and less expensive. This study addresses the question of electrode selection for EEG-based P300 systems. Methods: Data from 13 subjects collected with a 16-electrode cap was analyzed. The optimal subsets of electrodes of sizes 1-15 were calculated for each subject and for the group as a whole. The methods of exhaustive search, forward selection, and backward elimination were then compared to each other and to these optimal subsets. Results: The results show that, while none of the methods consistently picked the best-performing electrode subsets, all methods were able to find small electrode subsets that provided acceptable accuracy both for individuals and for the whole group. The computationally intensive exhaustive search method provided no statistically significant increase in performance over the much quicker forward and backward selection methods. Conclusions: The forward and backward selection methods are preferred for electrode selection. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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