Linked Life Data

21436527

Source:http://linkedlifedata.com/resource/pubmed/id/21436527

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2011-4-6
pubmed:abstractText
Recently, electroencephalogram-based brain-computer interfaces (BCIs) have attracted much attention in the fields of neural engineering and rehabilitation due to their noninvasiveness. However, the low communication speed of current BCI systems greatly limits their practical application. In this paper, we present a high-speed BCI based on code modulation of visual evoked potentials (c-VEP). Thirty-two target stimuli were modulated by a time-shifted binary pseudorandom sequence. A multichannel identification method based on canonical correlation analysis (CCA) was used for target identification. The online system achieved an average information transfer rate (ITR) of 108 ± 12 bits min(-1) on five subjects with a maximum ITR of 123 bits min(-1) for a single subject.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1741-2552
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
8
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
025015
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
A high-speed BCI based on code modulation VEP.
pubmed:affiliation
Biomedical Engineering Department, Tsinghua University, 100084, Beijing, People's Republic of China.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't