8 papers
FAConformer: Frequency-Aware Convolutional Transformer for Auditory Attention Decoding
Ziwei Wang, Xingyi He, Tianwang Jia +2
Auditory attention decoding (AAD) aims to infer the attended speaker from neural responses in multi-speaker acoustic environments and is a key problem for neuro-steered hearing sys…
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…
Backpropagation-Free Test-Time Adaptation for Lightweight EEG-Based Brain-Computer Interfaces
Siyang Li, Jiayi Ouyang, Zhenyao Cui +4
Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) face significant deployment challenges due to inter-subject variability, signal non-stationarity, and computationa…
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…
DBConformer: Dual-Branch Convolutional Transformer for EEG Decoding
Ziwei Wang, Hongbin Wang, Tianwang Jia +3
Electroencephalography (EEG)-based brain-computer interfaces (BCIs) transform spontaneous/evoked neural activity into control commands for external communication. While convolution…