Brain-Computer Interface (BCI) is a communication system, which enables the user to control special computer applications by using only his or her thoughts. A BCI allows a person to communicate with or control the external world without using the brain as normal output pathways of peripheral nerves and muscles. Messages and commands are expressed not by muscle contractions, but rather by electrophysiological signals from the brain.

This page is about our participation in the BCI Competition 2003. The goal of the BCI Competition 2003 competition was to validate signal processing and classification methods for Brain Computer Interfaces (BCIs). This competition had 6 different categories, which for each category some EEG data set was presented via Internet. For each data set specific goals was given in the respective description. Technically speaking, each data set consists of single trials of spontaneous EEG activity, one part labeled (training data) and another part unlabeled (test data), and a performance measure. The goal is to infer labels for the test set from training data that maximize the performance measure for the true (but to the participant unknown) test labels.

Our BCI team entered in 4 categories, and took 3rd place in category III, 6th in category Ib, 11th in category Ia, and finally 15th in category IV. Below you can find very short reports about methods used by our BCI team. You can access competition results here.

Ia Dataset
Ib Dataset
III Dataset
IV Dataset