19 citations · 36 across the 8 of their papers we have counts for
8 papers · 1 filter
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…
AFPM: Alignment-based Frame Patch Modeling for Cross-Dataset EEG Decoding
Xiaoqing Chen, Siyang Li, Dongrui Wu
Electroencephalogram (EEG) decoding models for brain-computer interfaces (BCIs) struggle with cross-dataset learning and generalization due to channel layout inconsistencies, non-s…
Multimodal Brain-Computer Interfaces: AI-powered Decoding Methodologies
Siyang Li, Hongbin Wang, Xiaoqing Chen +1
Brain-computer interfaces (BCIs) enable direct communication between the brain and external devices. This review highlights the core decoding algorithms that enable multimodal BCIs…
Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer Interfaces
Lubin Meng, Xue Jiang, Xiaoqing Chen +3
A brain-computer interface (BCI) enables direct communication between the brain and an external device. Electroencephalogram (EEG) is a common input signal for BCIs, due to its con…
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…
User-wise Perturbations for User Identity Protection in EEG-Based BCIs
Xiaoqing Chen, Siyang Li, Yunlu Tu +2
Objective: An electroencephalogram (EEG)-based brain-computer interface (BCI) is a direct communication pathway between the human brain and a computer. Most research so far studied…
Alignment-Based Adversarial Training (ABAT) for Improving the Robustness and Accuracy of EEG-Based BCIs
Xiaoqing Chen, Ziwei Wang, Dongrui Wu
Machine learning has achieved great success in electroencephalogram (EEG) based brain-computer interfaces (BCIs). Most existing BCI studies focused on improving the decoding accura…