Causal-aware reliability assessment of single-channel EEG for transformer-based sleep staging

Single-channel EEG-based sleep staging methods are well-suited for wearable applications in home environments, offering a practical solution to reduce the diagnostic burden on clinical institutions and address the growing demand for large-scale sleep monitoring. However, its reliability remains a critical concern compared to multi-channel polysomnography (PSG) used in clinical settings. To address this, we propose a Transformer-based sleep staging model and conduct a systematic investigation into the causal-inspired analysis between EEG channel selection and staging reliability. Our experiments reveal that electrodes positioned over the central brain region yield significantly higher accuracy, macro-F1, and consistency in sleep stage classification compared to those located in frontal or occipital regions. These findings provide causal insights into the spatial determinants of perceptual reliability in EEG-based sleep monitoring, supporting the design of robust wearable systems.