Influence of the Number of Channels and Classification Algorithm on the Performance Robustness to Electrode Shift in Steady-State Visual Evoked Potential-Based Brain-Computer Interfaces

There remains an active investigation on elevating the classification accuracy and information transfer rate of brain-computer interfaces based on steady-state visual evoked potential. However, it has often been ignored that the performance of steady-state visual evoked potential (SSVEP)-based brain...

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Detalles Bibliográficos
Autores principales: Kim, Hodam, Im, Chang-Hwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8569408/
https://www.ncbi.nlm.nih.gov/pubmed/34744677
http://dx.doi.org/10.3389/fninf.2021.750839

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8569408/
https://www.ncbi.nlm.nih.gov/pubmed/34744677
http://dx.doi.org/10.3389/fninf.2021.750839

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