BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal
Electroencephalography (EEG) is highly susceptible to artifact contamination, such as electrooculographic (EOG) and electromyographic (EMG) interference, which severely degrades signal quality and hinders reliable interpretation in applications including neurological diagnosis, brain-computer interfaces (BCIs), etc. Effective EEG denoising remains challenging because different artifact sources exhibit diverse and temporally varying distributions, together with distinct spectral characteristics across frequency bands. To address these issues, we propose BandRouteNet, an adaptive frequency-aware neural network for EEG denoising that jointly exploits band-specific processing and full-band co...
| Authors | Phat Lam |
|---|---|
| Primary category | eess.SP |
| Published | 27 April 2026 |
| Last updated at source | 11 May 2026 |
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