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A high-speed brain-computer interface (BCI) using dry EEG electrodes.
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- Author(s): Spüler M;Spüler M
- Source:
PloS one [PLoS One] 2017 Feb 22; Vol. 12 (2), pp. e0172400. Date of Electronic Publication: 2017 Feb 22 (Print Publication: 2017).- Publication Type:
Journal Article- Language:
English - Source:
- Additional Information
- Source: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
- Publication Information: Original Publication: San Francisco, CA : Public Library of Science
- Subject Terms:
- Abstract: Recently, brain-computer interfaces (BCIs) based on visual evoked potentials (VEPs) have been shown to achieve remarkable communication speeds. As they use electroencephalography (EEG) as non-invasive method for recording neural signals, the application of gel-based EEG is time-consuming and cumbersome. In order to achieve a more user-friendly system, this work explores the usability of dry EEG electrodes with a VEP-based BCI. While the results show a high variability between subjects, they also show that communication speeds of more than 100 bit/min are possible using dry EEG electrodes. To reduce performance variability and deal with the lower signal-to-noise ratio of the dry EEG electrodes, an averaging method and a dynamic stopping method were introduced to the BCI system. Those changes were shown to improve performance significantly, leading to an average classification accuracy of 76% with an average communication speed of 46 bit/min, which is equivalent to a writing speed of 8.8 error-free letters per minute. Although the BCI system works substantially better with gel-based EEG, dry EEG electrodes are more user-friendly and still allow high-speed BCI communication.
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Conf Proc IEEE Eng Med Biol Soc. 2011;2011:4580-3. (PMID: 22255357) - Publication Date: Date Created: 20170223 Date Completed: 20170821 Latest Revision: 20190208
- Publication Date: 20231215
- Accession Number: PMC5321409
- Accession Number: 10.1371/journal.pone.0172400
- Accession Number: 28225794
- Source:
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