Status of deep learning for EEG-based brain–computer interface applications

• Published in: Frontiers in computational neuroscience Vol. 16; p. 1006763
• Main Authors: Hossain, Khondoker Murad, Islam, Md. Ariful, Hossain, Shahera, Nijholt, Anton, Ahad, Md Atiqur Rahman
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 16.01.2023; Frontiers Media S.A
• Subjects: Algorithms; Artificial intelligence; BCI; Bioinformatics; Brain; Brain research; Central nervous system; Classification; Computational neuroscience; Computer applications; convolutional neural network (CNN); Datasets; Deep learning; Discriminant analysis; EEG; Electroencephalography; Epilepsy; future challenge; Hemiplegia; Human subjects; Implants; Literature reviews; Machine learning; Mental task performance; Methods; Neurology; Neuroscience; Rehabilitation; Seizures; Signal processing; future challenge; deep learning; BCI; convolutional neural network (CNN); EEG

In the previous decade, breakthroughs in the central nervous system bioinformatics and computational innovation have prompted significant developments in brain–computer interface (BCI), elevating it to the forefront of applied science and research. BCI revitalization enables neurorehabilitation stra...