P300 Detection Based on Feature Extraction in On-line Brain-Computer Interface

Abstract. 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.

• Type: Conference
• Year: 2009
• Where: KI
• Authors: Nikolay Chumerin, Nikolay V. Manyakov, Adrien Combaz, Johan A. K. Suykens, Refet Firat Yazicioglu, Tom Torfs, Patrick Merken, Herc P. Neves, Chris Van Hoof, Marc M. Van Hulle
• Keywords: Artificial Intelligence, EEG-based Wireless Brain, Event-related Potentials, KI 2009, On-line P300 Detection