A Cross-Scale Transformer and Triple-View Attention Based Domain-Rectified Transfer Learning for EEG Classification in RSVP Tasks

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 32; pp. 672 - 683
• Main Authors: Luo, Jie, Cui, Weigang, Xu, Song, Wang, Lina, Chen, Huiling, Li, Yang
• Format: Journal Article
• Language: English
• Published: United States IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Brain; Brain-Computer Interfaces; Brain–computer interface; Classification; Computer applications; Convolution; Deep learning; EEG; Electric Power Supplies; Electroencephalography; Feature extraction; Human-computer interface; Humans; Implants; Information processing; Invariants; Learning; Machine Learning; Representations; RSVP; Source code; Spectrogram; Target detection; Task analysis; Temporal variations; Transfer learning; transformer; Transformers; Visual tasks

Rapid serial visual presentation (RSVP)-based brain-computer interface (BCI) is a promising target detection technique by using electroencephalogram (EEG) signals. However, existing deep learning approaches seldom considered dependencies of multi-scale temporal features and discriminative multi-view...