P300 Detection Based on Feature Extraction in On-line Brain-Computer Interface
- Cite this paper as:
- Chumerin N. et al. (2009) P300 Detection Based on Feature Extraction in On-line Brain-Computer Interface. In: Mertsching B., Hund M., Aziz Z. (eds) KI 2009: Advances in Artificial Intelligence. KI 2009. Lecture Notes in Computer Science, vol 5803. Springer, Berlin, Heidelberg
We propose a new EEG-based wireless brain computer interface (BCI) with which subjects can “mind-type” 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 simple classifier which relies on a linear feature extraction approach. The accuracy of the presented system is comparable to the state-of-the-art for on-line P300 detection, but with the additional benefit that its much simpler design supports a power-efficient on-chip implementation.
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