Cargando…
A Transform-Based Feature Extraction Approach for Motor Imagery Tasks Classification
In this paper, we present a new motor imagery classification method in the context of electroencephalography (EEG)-based brain–computer interface (BCI). This method uses a signal-dependent orthogonal transform, referred to as linear prediction singular value decomposition (LP-SVD), for feature extra...
Formato: | Online Artículo Texto |
---|---|
Lenguaje: | English |
Publicado: |
IEEE
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4861551/ https://www.ncbi.nlm.nih.gov/pubmed/27170898 http://dx.doi.org/10.1109/JTEHM.2015.2485261 |
Ejemplares similares
-
Classification of motor imagery tasks for BCI with multiresolution analysis and multiobjective feature selection
por: Ortega, Julio, et al.
Publicado: (2016) -
Robust Motor Imagery Tasks Classification Approach Using Bayesian Neural Network
por: Milanés-Hermosilla, Daily, et al.
Publicado: (2023) -
Relevant Feature Integration and Extraction for Single-Trial Motor Imagery Classification
por: Li, Lili, et al.
Publicado: (2017) -
Investigating Feature Ranking Methods for Sub-Band and Relative Power Features in Motor Imagery Task Classification
por: Mohdiwale, Samrudhi, et al.
Publicado: (2021) -
Local and global convolutional transformer-based motor imagery EEG classification
por: Zhang, Jiayang, et al.
Publicado: (2023)