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An analysis of the accuracy of the P300 BCI
Nitzan S. Artzi
,
Oren Shriki
Department of Cognitive and Brain Sciences
Research output
:
Contribution to journal
›
Article
›
peer-review
8
Scopus citations
Overview
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Keyphrases
Brain-computer Interface
100%
P300
100%
Spelling Accuracy
100%
Signal-to-noise Ratio
66%
P300 Potential
66%
Communication Channels
33%
Strong Correlation
33%
Noise Level
33%
P300 Speller
33%
Event-related Potential Signal
33%
Electrode Selection
33%
Temporal Noise
33%
P300 Signal
33%
Gaussian Noise Model
33%
Severely Disabled
33%
Spatial Noise
33%
Engineering
Brain-Computer Interface
100%
Signal-to-Noise Ratio
66%
Communication Channel
33%
Real Data
33%
Potential Application
33%
Noise Level
33%
Gaussian White Noise
33%
Computer Science
Computer Interface
100%
Noise-to-Signal Ratio
66%
Gaussian White Noise
33%
Potential Application
33%
Linear Discriminant Analysis
33%
Disabled People
33%
Physics
Signal-to-Noise Ratio
100%
Random Noise
50%
Earth and Planetary Sciences
Random Noise
100%