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Open access Aug 2026

MTGNet: A task-oriented and spectrally guided framework for EEG denoising.

OBJECTIVE Electroencephalography (EEG) is widely used in brain-computer interfaces (BCIs), but its microvolt-level signals are easily contaminated by electromyography (EMG), electrooculography (EOG), and mixed physiological artifacts. This study develops an EEG denoising framework that suppresses artifacts while preser...

Jin-Cheng Hu, Zhongke Gao, Yushi Hao et al. · 0 citations
Aug 2026

Graph convolution neural network channel selection with attention for motor imagery EEG decoding.

Accurate decoding of motor imagery electroencephalography (MI-EEG) signals is critical for practical brain-computer interface (BCI) systems. However, conventional approaches typically rely on dense multi-channel recordings, which not only introduce data redundancy but may also incorporate noise, thereby hindering real-...

Hao-Yu Li, Wei-Dong Dang, Lei Liu et al. · 0 citations

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