Inter- and Intra-Subject transfer learning for High-Performance SSVEP-BCI with extremely little calibration effort

• Published in: Expert systems with applications Vol. 276; p. 127208
• Main Authors: Li, Hui, Xu, Guanghua, Li, Zejin, Zhang, Kai, Jiang, Hanli, Guo, Xiaobing, Zhu, Yongzhen, Yang, Xuwei, Zhao, Yihua, Han, Chengcheng
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2025
• Subjects: Brain-computer interface (BCI); electroencephalography (EEG); Inter-subject transfer learning; Intra-subject transfer learning; steady-state visual evoked potential (SSVEP); electroencephalography (EEG); Brain-computer interface (BCI); Intra-subject transfer learning; Inter-subject transfer learning; steady-state visual evoked potential (SSVEP)

High-performance steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) typically requires large amounts of calibration data to derive individual-specific model parameters. This imposes a significant burden on the use of SSVEP-BCI and limits its practical applications. Exi...