MLSP competition, 2010: Description of second place method


2010 IEEE 20th International Workshop on Machine Learning for Signal Processing, MLSP 2010, Kittila, Finland, 29 August - 01 September 2010, pp.114-115 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/mlsp.2010.5589246
  • City: Kittila
  • Country: Finland
  • Page Numbers: pp.114-115
  • Keywords: BCI, P300, PCA, T-statistic
  • Istanbul Medipol University Affiliated: No


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. ©2010 IEEE.