An application of feature selection to on-line P300 detection in brain-computer interface
We propose a new EEG-based wireless brain computer interface (BCI) with which subjects can ldquomind-typerdquo text on a computer screen. The application is based on detecting P300 event-related potentials in EEG signals recorded on the scalp of the subject. The BCI uses a linear classifier which ta...
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| creator | Chumerin, N. Manyakov, N.V. Combaz, A. Suykens, J.A.K. Van Hulle, M.M. |
| description | We propose a new EEG-based wireless brain computer interface (BCI) with which subjects can ldquomind-typerdquo text on a computer screen. The application is based on detecting P300 event-related potentials in EEG signals recorded on the scalp of the subject. The BCI uses a linear classifier which takes as input a set of simple amplitude-based features that are optimally selected using the group method of data handling (GMDH) feature selection procedure. The accuracy of the presented system is comparable to the state-of-the-art systems for on-line P300 detection, but with the additional benefit that its much simpler design supports a power-efficient on-chip implementation. |
| doi_str_mv | 10.1109/MLSP.2009.5306244 |
| format | Conference Proceeding |
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| identifier | ISSN: 1551-2541 |
| ispartof | 2009 IEEE International Workshop on Machine Learning for Signal Processing, 2009, p.1-6 |
| issn | 1551-2541 2378-928X |
| language | eng |
| recordid | cdi_ieee_primary_5306244 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Brain computer interfaces |
| title | An application of feature selection to on-line P300 detection in brain-computer interface |
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