文献类型：期刊文献

英文题名：G-CMTF Net: Spectro-Temporal Disentanglement and Reliability-Aware Gated Cross-Modal Temporal Fusion for Robust PSG Sleep Staging

作者：Ye, Jiongyao[1];Li, Pengfei[1]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China

年份：2026

卷号：18

期号：2

外文期刊名：SYMMETRY-BASEL

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001701253800001)】；

基金：This work was supported by the National Natural Science Foundation of China (82374561, 82174490), the Zhejiang Provincial Natural Science Foundation of China (LY24H270003), the Key Project of Zhejiang Provincial Administration of Traditional Chinese Medicine (GZY-ZJ-KJ-23072), Research Project of Zhejiang Chinese Medical University (2022FSYYZZ07, 2025FSYYZY10).

语种：英文

外文关键词：automatic sleep staging; multimodal polysomnography; gated cross-modal fusion; spectro-temporal learning; noise-robust modeling

摘要：Automatic sleep staging from polysomnography is challenged by marked spectro-temporal heterogeneity and non-stationary cross-channel artifacts, which often undermine na & iuml;ve multimodal fusion. To address this, a Gated Cross-Modal and Temporal Fusion Network (G-CMTF Net) is proposed as an end-to-end model operating on 30 s EEG epochs and auxiliary EOG and EMG signals, in which cross-modal contributions are regulated through reliability-aware gating. A spectro-temporal disentanglement frontend learns multi-scale temporal features while incorporating FFT-derived band-power embeddings to preserve physiologically meaningful oscillatory cues. At the epoch level, gated fusion suppresses artifact-prone auxiliary inputs, thereby limiting noise transfer into a shared latent space. Long-range sleep dynamics are modeled via a convolution-augmented self-attention encoder that captures both local morphology and transition structure. On Sleep-EDF-20 and Sleep-EDF-78, G-CMTF Net achieves Macro-F1/ACC of 81.3%/85.5% and 78.2%/83.4%, respectively, while maintaining high sensitivity and geometric-mean performance on transitional epochs, consistent with the function of reliability-aware gated fusion under non-stationary auxiliary artifacts. From a symmetry perspective, the proposed framework enforces a structured balance between heterogeneous modalities by promoting representational consistency while adaptively suppressing asymmetric noise contributions.