Work

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

Year: 2025

Type: article

Abstract: 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.

Source: Frontiers in Neuroscience

DOI: 10.3389/fnins.2025.1670124

Authors: Yongkang Hu, Xiangbo Yang, Yunhan Xu, Jingpeng Sun

Institution: Anhui University

Language: English

Topic: EEG and Brain-Computer Interfaces

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,801