Cross-subject spatial filter transfer method for SSVEP-EEG feature recognition

• Published in: Journal of neural engineering Vol. 19; no. 3; pp. 36008 - 36019
• Main Authors: Yan, Wenqiang, Wu, Yongcheng, Du, Chenghang, Xu, Guanghua
• Format: Journal Article
• Language: English
• Published: England IOP Publishing 12.05.2022
• Subjects: Algorithms; Brain-Computer Interfaces; cross-subject; electroencephalogram (EEG); Electroencephalography - methods; ensemble learning; Evoked Potentials, Visual; Photic Stimulation; spatial filter; steady-state visual evoked potential (SSVEP); transfer learning; ensemble learning; transfer learning; cross-subject; spatial filter; electroencephalogram (EEG); steady-state visual evoked potential (SSVEP)

Objective. Steady-state visual evoked potential (SSVEP) is an important control method of the brain–computer interface (BCI) system. The development of an efficient SSVEP feature decoding algorithm is the core issue in SSVEP-BCI. It has been proposed to use user training data to reduce the spontaneo...