Single-Channel Selection for Detecting Steady-State Visual Evoked Potentials in a Brain-Computer Interface Speller

Single-Channel Selection for Detecting Steady-State Visual Evoked Potentials in a Brain-Computer Interface Speller

Purpose: Brain-Computer Interface (BCI) provides a secondary communication pathway for patients with neuromuscular diseases such as amyotrophic lateral sclerosis (ALS) or brainstem stroke in which they are almost incapacitated to move or talk. BCI enacts neural oscillations to generate a command si...

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Bibliographic Details
Main Authors: Farzad Saffari, Ali Khadem
Format: Article
Language:English
Published: Tehran University of Medical Sciences 2021-09-01
Series:Frontiers in Biomedical Technologies
Subjects:
Brain-Computer Interface Speller
Steady-State Visual Evoked Potential
Deep Learning
Convolutional Neural Networks
Single-Channel Electroencephalogram
Online Access:https://fbt.tums.ac.ir/index.php/fbt/article/view/315

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