Cargando…
An Efficient P300-based BCI Using Wavelet Features and IBPSO-based Channel Selection
We present a novel and efficient scheme that selects a minimal set of effective features and channels for detecting the P300 component of the event-related potential in the brain–computer interface (BCI) paradigm. For obtaining a minimal set of effective features, we take the truncated coefficients...
Autores principales: | Perseh, Bahram, Sharafat, Ahmad R. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3660708/ https://www.ncbi.nlm.nih.gov/pubmed/23717804 |
Ejemplares similares
-
Parallel Computing Sparse Wavelet Feature Extraction for P300 Speller BCI
por: Huang, Zhihua, et al.
Publicado: (2018) -
Enhancing P300 Wave of BCI Systems Via Negentropy in Adaptive Wavelet Denoising
por: Vahabi, Z, et al.
Publicado: (2011) -
Empathy, motivation, and P300 BCI performance
por: Kleih, Sonja C., et al.
Publicado: (2013) -
Attention and P300-based BCI performance in people with amyotrophic lateral sclerosis
por: Riccio, Angela, et al.
Publicado: (2013) -
A novel P300 BCI speller based on the Triple RSVP paradigm
por: Lin, Zhimin, et al.
Publicado: (2018)