11 papers
OmniEEG-Bench: A Standardized Evaluation Benchmark for EEG Foundation Models
Ziling Lu, Zongsheng Li, Xinke Shen +11
Electroencephalography (EEG) supports a variety of brain-computer interface (BCI) tasks ranging from brain-state monitoring to human-LLM interactions. EEG foundation models are eme…
Synthetic Data Generation for Brain-Computer Interfaces: Overview, Benchmarking, and Future Directions
Ziwei Wang, Zhentao He, Xingyi He +6
Deep learning has achieved transformative performance across diverse domains, largely driven by large-scale and high-quality training data. In contrast, the development of brain-co…
PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding
Xiaoqing Chen, Tianwang Jia, Yunlu Tu +1
An electroencephalogram (EEG)-based brain-computer interface (BCI) enables direct communication between the brain and external devices. However, such systems face at least three ma…
RAICL: Retrieval-Augmented In-Context Learning for Vision-Language-Model Based EEG Seizure Detection
Siyang Li, Zhuoya Wang, Xiyan Gui +4
Electroencephalogram (EEG) decoding is a critical component of medical diagnostics, rehabilitation engineering, and brain-computer interfaces. However, contemporary decoding method…
SAFE: Secure and Accurate Federated Learning for Privacy-Preserving Brain-Computer Interfaces
Tianwang Jia, Xiaoqing Chen, Dongrui Wu
Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) are widely adopted due to their efficiency and portability; however, their decoding algorithms still face multiple…
MVCNet: Multi-View Contrastive Network for Motor Imagery Classification
Ziwei Wang, Siyang Li, Xiaoqing Chen +1
Electroencephalography (EEG)-based brain-computer interfaces (BCIs) enable neural interaction by decoding brain activity for external communication. Motor imagery (MI) decoding has…