5 papers
Coordinate-Queryable Neural Field Reconstruction for EEG Spatial Super-Resolution with Unseen-Electrode Generation
Hongjun Liu, Leyu Zhou, Zijianghao Yang +1
EEG spatial super-resolution (EEGSR) in real deployments is challenged by random channel missingness, unstable electrode quality, and changing visible-channel patterns caused by ba…
Semantic Compensation via Adversarial Removal for Robust Zero-Shot ECG Diagnosis
Hongjun Liu, Rujun Han, Leyu Zhou +1
Recent ECG--language pretraining methods enable zero-shot diagnosis by aligning cardiac signals with clinical text, but they do not explicitly model robustness to partial observati…
Step-Aware Residual-Guided Diffusion for EEG Spatial Super-Resolution
Hongjun Liu, Leyu Zhou, Zijianghao Yang +1
For real-world BCI applications, lightweight Electroencephalography (EEG) systems offer the best cost-deployment balance. However, such spatial sparsity of EEG limits spatial fidel…
CAFE: Channel-Autoregressive Factorized Encoding for Robust Biosignal Spatial Super-Resolution
Hongjun Liu, Leyu Zhou, Zijianghao Yang +4
High-density biosignal recordings are critical for neural decoding and clinical monitoring, yet real-world deployments often rely on low-density (LD) montages due to hardware and o…
Spatial Imputation Drives Cross-Domain Alignment for EEG Classification
Hongjun Liu, Chao Yao, Yalan Zhang +2
Electroencephalogram (EEG) signal classification faces significant challenges due to data distribution shifts caused by heterogeneous electrode configurations, acquisition protocol…