Document Detail


A user-friendly SSVEP-based brain-computer interface using a time-domain classifier.
MedLine Citation:
PMID:  20332551     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
We introduce a user-friendly steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) system. Single-channel EEG is recorded using a low-noise dry electrode. Compared to traditional gel-based multi-sensor EEG systems, a dry sensor proves to be more convenient, comfortable and cost effective. A hardware system was built that displays four LED light panels flashing at different frequencies and synchronizes with EEG acquisition. The visual stimuli have been carefully designed such that potential risk to photosensitive people is minimized. We describe a novel stimulus-locked inter-trace correlation (SLIC) method for SSVEP classification using EEG time-locked to stimulus onsets. We studied how the performance of the algorithm is affected by different selection of parameters. Using the SLIC method, the average light detection rate is 75.8% with very low error rates (an 8.4% false positive rate and a 1.3% misclassification rate). Compared to a traditional frequency-domain-based method, the SLIC method is more robust (resulting in less annoyance to the users) and is also suitable for irregular stimulus patterns.
Authors:
An Luo; Thomas J Sullivan
Publication Detail:
Type:  Comparative Study; Evaluation Studies; Journal Article     Date:  2010-03-23
Journal Detail:
Title:  Journal of neural engineering     Volume:  7     ISSN:  1741-2552     ISO Abbreviation:  J Neural Eng     Publication Date:  2010 Apr 
Date Detail:
Created Date:  2010-03-24     Completed Date:  2010-06-30     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101217933     Medline TA:  J Neural Eng     Country:  England    
Other Details:
Languages:  eng     Pagination:  26010     Citation Subset:  IM    
Affiliation:
NeuroSky Inc., San Jose, CA, USA. aluo@neurosky.com
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MeSH Terms
Descriptor/Qualifier:
Adult
Algorithms
Brain / physiology*
Computers
Electrodes / economics
Electroencephalography / economics,  instrumentation,  methods*
Evoked Potentials, Visual*
Female
Humans
Male
Middle Aged
Photic Stimulation
Signal Processing, Computer-Assisted*
Time Factors
User-Computer Interface*
Visual Perception / physiology*
Young Adult

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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