Cargando…
Detection of motor execution using a hybrid fNIRS-biosignal BCI: a feasibility study
BACKGROUND: Brain-computer interfaces (BCIs) were recently recognized as a method to promote neuroplastic effects in motor rehabilitation. The core of a BCI is a decoding stage by which signals from the brain are classified into different brain-states. The goal of this paper was to test the feasibil...
Autores principales: | Zimmermann, Raphael, Marchal-Crespo, Laura, Edelmann, Janis, Lambercy, Olivier, Fluet, Marie-Christine, Riener, Robert, Wolf, Martin, Gassert, Roger |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3637588/ https://www.ncbi.nlm.nih.gov/pubmed/23336819 http://dx.doi.org/10.1186/1743-0003-10-4 |
Ejemplares similares
-
LASSO Homotopy-Based Sparse Representation Classification for fNIRS-BCI
por: Gulraiz, Asma, et al.
Publicado: (2022) -
System Derived Spatial-Temporal CNN for High-Density fNIRS BCI
Publicado: (2023) -
Hybrid EEG–fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control
por: Khan, Muhammad Jawad, et al.
Publicado: (2017) -
A Computationally Efficient Method for Hybrid EEG-fNIRS BCI Based on the Pearson Correlation
por: Hasan, Mustafa A. H., et al.
Publicado: (2020) -
Toward a Hybrid Passive BCI for the Modulation of Sustained Attention Using EEG and fNIRS
por: Karran, Alexander J., et al.
Publicado: (2019)