EFS-Net Fuses EEG and fNIRS for Hybrid BCI Decoding
Researchers proposed EFS-Net, an end-to-end network that aligns fast EEG activity with slower fNIRS haemodynamic signals through temporal, spatial and cross-modal branches. In subject-specific leave-one-session-out validation, the model reached 77.71% accuracy on a word-generation dataset and 81.69% on a mental-arithmetic dataset.