P300 Detection Based on Feature Extraction in On-line Brain-Computer Interface
| Autor: | Chumerin, Nikolay, Manyakov, Nikolay V, Combaz, Adrien, Yazicioglu, Refet Firat, Suykens, Johan, Torfs, Tom, Merken, Patrick, Neves, Herc P, Van Hoof, Christiaan, Van Hulle, Marc, Van Hoof, C |
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| Přispěvatelé: | Mertsching, B, Hund, M |
| Rok vydání: | 2009 |
| Předmět: |
Computer science
Feature extraction power-efficient on-chip implementation Feature selection Linear classifier Electroencephalography event-related potential feature selection on-line P300 detection linear classifier medicine wireless brain computer interface EEG P300 BCI medical signal processing group method-of-data handling Brain–computer interface signal classification data recording medicine.diagnostic_test business.industry feature extraction brain-computer interface Pattern recognition Mutual information Artificial intelligence business Classifier (UML) electroencephalography |
| Zdroj: | KI 2009: Advances in Artificial Intelligence ISBN: 9783642046162 KI |
| DOI: | 10.1007/978-3-642-04617-9_43 |
| Popis: | 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. ispartof: pages:339-346 ispartof: Lecture Notes in Computer Science vol:5803 pages:339-346 ispartof: 32nd Annual Conference on Artificial Intelligence location:Paderborn, Germany date:15 Sep - 18 Sep 2009 status: published |
| Databáze: | OpenAIRE |
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