Semi-Supervised Learning for Auditory Event-Related Potential-Based Brain-Computer Interface

• Published in: IEEE access Vol. 9; pp. 47008 - 47023
• Main Authors: Ogino, Mikito, Kanoga, Suguru, Ito, Shin-Ichi, Mitsukura, Yasue
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Auditory stimuli; Brain-computer interfaces; brain–computer interface; Datasets; Discriminant analysis; Electroencephalography; event-related potential; Human-computer interface; Imagery; Machine learning; P300; Semi-supervised learning; Semisupervised learning; Support vector machines; Testing; Training; Visualization

A brain-computer interface (BCI) is a communication tool that analyzes neural activity and relays the translated commands to carry out actions. In recent years, semi-supervised learning (SSL) has attracted attention for visual event-related potential (ERP)-based BCIs and motor-imagery BCIs as an eff...