A Novel Fast ICA-FBCCA Algorithm and Convolutional Neural Network for Single-Flicker SSVEP-Based BCIs

A Novel Fast ICA-FBCCA Algorithm and Convolutional Neural Network for Single-Flicker SSVEP-Based BCIs

Brain-computer interface (BCI) systems have been developed to assist individuals with neuromuscular disorders to communicate with their surroundings using their brain signals. One attractive branch of BCI is steady-state visual evoked potential (SSVEP), which has acceptable speed and accuracy and is...

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Bibliographic Details
Main Authors: Seyedeh Nadia Aghili, Sepideh Kilani, Ehsan Rouhani, Amir Akhavan
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Brain–computer interface (BCI)
single-flicker steady-state visual evoked potential
fast independent component analysis (fast ICA)
filter-bank canonical correlation analysis (FBCCA)
convolutional neural network (CNN)
Online Access:https://ieeexplore.ieee.org/document/10374086/

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