Abstract
We present three datasets that were used to conduct an open competition for evaluating the performance of various machine-learning algorithms used in brain-computer interfaces. The datasets were collected for tasks that included: 1) detecting explicit left/right (L/R) button press; 2) predicting imagined L/R button press; and 3) vertical cursor control. A total of ten entries were submitted to the competition, with winning results reported for two of the three datasets.
| Original language | English |
|---|---|
| Pages (from-to) | 184-185 |
| Number of pages | 2 |
| Journal | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| Volume | 11 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2003 Jun |
Keywords
- Brain computer interface (BCI)
- Data analysis competition
- Electroencephalography (EEG)
- Machine learning
ASJC Scopus subject areas
- Internal Medicine
- Neuroscience(all)
- Biomedical Engineering
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Sajda, P., Gerson, A., Müller, K. R., Blankertz, B., & Parra, L. (2003). A data analysis competition to evaluate machine learning algorithms for use in brain-computer interfaces. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 11(2), 184-185. https://doi.org/10.1109/TNSRE.2003.814453