Title :
MLSP Competition, 2010: Description of first place method
Author :
Leiva, Jose M. ; Martens, Suzanna M M
Author_Institution :
Dept. of Signal Theor. & Comms, Univ. Carlos III de Madrid, Leganés, Spain
fDate :
Aug. 29 2010-Sept. 1 2010
Abstract :
Our winning approach to the 2010 MLSP Competition is based on a generative method for P300-based BCI decoding, successfully applied to visual spellers. Here, generative has a double meaning. On the one hand, we work with a probability density model of the data given the target/non target labeling, as opposed to discriminative (e.g. SVM-based) methods. On the other hand, the natural consequence of this approach is a decoding based on comparing the observation to templates generated from the data.
Keywords :
brain-computer interfaces; decoding; probability; MLSP competition; P300-based BCI decoding; probability density model; visual spellers; Additives; Band pass filters; Decorrelation; Noise measurement; Principal component analysis; Signal to noise ratio;
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.2010.5589243