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20242026
most citedAlignment-Based Adversarial Training (ABAT) for Improving the Robustness and Accuracy of EEG-Based BCIs

19 citations · 36 across the 8 of their papers we have counts for

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3 papers · 1 filter

cs.HC2025

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…

cs.HC2025

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…

eess.SP2025

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…