most citedEMD-Fuzzy: An Empirical Mode Decomposition Based Fuzzy Model for Cross-Stimulus Transfer Learning of SSVEP

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

eess.SP2026

Learning Dynamic Neural Evidence Representations for Time-Adaptive Brain-Computer Interfaces

Beining Cao, Ziyi Zhao, Xiaowei Jiang +5

Brain-computer interfaces (BCIs) decode neural activity into commands, yet most existing systems rely on fixed-window decoding that may result in redundant observation or unreliabl…

cs.HC2026

Online Inference of Human Intention as a Latent Control State from Single-Trial EEG

Xiaowei Jiang, Daniel Leong, Yu-Cheng Chang +2

Human intention can be modeled as a latent internal state that modulates how sensory information is evaluated and translated into action in human-machine systems. However, most exi…

cs.LG2026

iFuzz-Meta: An Interpretable Fuzzy Learning Framework Bridging Top-Down and Bottom-Up Knowledge Integration

Xiaowei Jiang, Daniel Leong, Beining Cao +5

Interpretable representation learning remains a key challenge in modern neural computation, particularly when models are expected not only to perform but also to explain their reas…

cs.HC2026

SASLO: A Scene-Aware Spatial Layout Optimization System for AR-SSVEP

Beining Cao, Xiaowei Jiang, Charlie Li-Ting Tsai +3

Steady-state visual evoked potential (SSVEP) is widely used in brain-computer interfaces (BCIs) due to its reliability. With the integration of augmented reality (AR), AR-SSVEP ena…

cs.CL2025

Pretraining Large Brain Language Model for Active BCI: Silent Speech

Jinzhao Zhou, Zehong Cao, Yiqun Duan +9

This paper explores silent speech decoding in active brain-computer interface (BCI) systems, which offer more natural and flexible communication than traditional BCI applications.…

cs.HC2025★ 1 cited

EMD-Fuzzy: An Empirical Mode Decomposition Based Fuzzy Model for Cross-Stimulus Transfer Learning of SSVEP

Beining Cao, Xiaowei Jiang, Daniel Leong +4

The Brain-Computer Interface (BCI) enables direct brain-to-device communication, with the Steady-State Visual Evoked Potential (SSVEP) paradigm favored for its stability and high a…