Title :
MLSP Competition, 2010: Description of second place method
Author_Institution :
Dept. of Electron. & Commun. Eng., Istanbul Tech. Univ., Istanbul, Turkey
fDate :
Aug. 29 2010-Sept. 1 2010
Abstract :
In this paper, the classification method which generated the second highest AUC (the area under the ROC curve) in the MLSP 2010 Competition is presented. After application of some pre-processing steps to the dataset, by using statistical information, proper weights are found which maximize the separability between the P300 and the non-P300 responses. The classification method is simple and very suitable for online brain-computer interface (BCI) applications due to its fast algorithm.
Keywords :
brain-computer interfaces; medical signal processing; pattern classification; statistical analysis; classification method; online brain-computer interface applications; statistical information; Band pass filters; Computer interfaces; Correlation; Equations; Feature extraction; Principal component analysis; Training; BCI; P300; PCA; T-statistic;
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop on
Conference_Location :
Kittila
Print_ISBN :
978-1-4244-7875-0
Electronic_ISBN :
1551-2541
DOI :
10.1109/MLSP.2010.5589246
