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ICMLA
2009
13 years 3 months ago
Feature Extraction and Classification of EEG Signals for Rapid P300 Mind Spelling
The Mind Speller is a Brain-Computer Interface which enables subjects to spell text on a computer screen by detecting P300 Event-Related Potentials in their electroencephalograms....
Adrien Combaz, Nikolay V. Manyakov, Nikolay Chumer...
ICPR
2004
IEEE
14 years 6 months ago
High Accuracy Classification of EEG Signal
Improving classification accuracy is a key issue to advancing brain computer interface (BCI) research from laboratory to real world applications. This article presents a high accu...
Chng Eng Siong, Cuntai Guan, Jiankang Wu, M. Thula...
IUI
2010
ACM
14 years 2 months ago
A POMDP approach to P300-based brain-computer interfaces
Most of the previous work on non-invasive brain-computer interfaces (BCIs) has been focused on feature extraction and classification algorithms to achieve high performance for the...
Jaeyoung Park, Kee-Eung Kim, Sungho Jo
CORR
2006
Springer
93views Education» more  CORR 2006»
13 years 5 months ago
Functional dissipation microarrays for classification
In this article, we describe a new method of extracting information from signals, called functional dissipation, that proves to be very effective for enhancing classification of h...
D. Napoletani, Daniele C. Struppa, T. Sauer, V. Mo...
WSCG
2004
188views more  WSCG 2004»
13 years 6 months ago
Recognition of Motor Imagery Electroencephalography Using Independent Component Analysis and Machine Classifiers
Motor imagery electroencephalography (EEG), which embodies cortical potentials during mental simulation of left or right finger lifting tasks, can be used as neural input signals ...
Chih-I. Hung, Po-Lei Lee, Yu-Te Wu, Hui-Yun Chen, ...