Título:
EEG signal pre-processing for the P300 speller
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Autor:
Patrone, Martín
Lecumberry, Federico
Martín Menoni, Alvaro
Ramírez Paulino, Ignacio
Seroussi, Gadiel
Lecumberry, Federico
Martín Menoni, Alvaro
Ramírez Paulino, Ignacio
Seroussi, Gadiel
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Tipo de documento:
Ponencia
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Palabras clave:
EEG
ERP
BCI
P300 speller
SSVEP
ERP
BCI
P300 speller
SSVEP
Descriptores:
Procesamiento de Señales
Año de publicación:
2015
Contenido:
Resumen:
One of the workhorses of Brain Computer Interfaces (BCI) is the P300 speller, which allows a person to spell text by looking at the corresponding letters that are laid out on a flashing grid. The device functions by detecting the Event Related Potentials (ERP), which can be measured in an electroencephalogram (EEG), that occur when the letter that the subject is looking at flashes (unexpectedly). In this work, after a careful analysis of the EEG signals involved, we propose a preprocessing method that allows us to improve on the state-of-the-art results for this kind of applications. Our results are comparable, and sometimes better, than the best results published, and do not require a feature (channel) selection step, which is extremely costly, and which must be applied to each user of the P300 speller separately
Descripción:
Trabajo presentado en Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2015
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Citación:
Patrone, M., Lecumberry, F., Martín, Á., Ramirez, I., Seroussi, G. "EEG Signal Pre-Processing for the P300 Speller". Publicado en: Pardo, A., Kittler, J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2015. Lecture Notes in Computer Science, v. 9423. Springer, Cham. https://doi.org/10.1007/978-3-319-25751-8_67
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Departamento académico:
Procesamiento de Señales
Grupo de investigación:
Tratamiento de Imágenes
Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| PLMRS15.pdf | — | 486.69 KB | Adobe PDF |