Enhancing SSVEP-Based BCI Performance via Consensus Information Transfer Among Subjects

• Published in: IEEE transaction on neural networks and learning systems Vol. 36; no. 8; pp. 13833 - 13847
• Main Authors: Zhang, Xinyi, Wei, Wei, Qiu, Shuang, Li, Xujin, Wang, Yijun, He, Huiguang
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.08.2025
• Subjects: Accuracy; Adult; Algorithms; Brain modeling; Brain-computer interface (BCI); Brain-Computer Interfaces; Consensus; Correlation; Data models; Decoding; deep learning (DL); electroencephalogram (EEG); Electroencephalography; Electroencephalography - methods; Evoked Potentials, Visual - physiology; Feature extraction; Female; Humans; Knowledge engineering; Male; Neural Networks, Computer; Photic Stimulation - methods; steady-state visual evoked potential (SSVEP); Training; Visualization; Young Adult

The brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP) has received considerable attention for its high communication speed. While large datasets provide an important opportunity to enhance decoding accuracies, the key challenge lies in the exploration of existing d...