Sleep Stage Classification

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Overview

Sleep stage classification labels short segments of overnight recordings, usually polysomnography, as wake, N1, N2, N3, or REM to measure sleep architecture and support screening and research. Common approaches learn signal features with convolutional networks or spectral filters, then model transitions across epochs with recurrent networks, Transformers, state-space models, or sequence decoders; other work combines EEG with EOG, ECG, PPG, or motion and learns reusable representations from large PSG collections. Benchmarks such as Sleep-EDF, SHHS, and ISRUC test accuracy and agreement, while newer evaluations emphasize difficult N1 transitions, cross-cohort transfer, noisy labels, wearable signals, and energy use. Strong benchmark performance does not guarantee reliable clinical deployment: populations and recording channels vary, expert labels disagree, and finer-grained or multimodal predictions must be balanced against interpretability and efficient operation.

Latest papers

CardsList

41 papers4 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

  1. MM-Net: A Multimodal Multi-Task Network for Sleep Staging and Sleep Apnea Assessment After Ischemic Stroke

    Oct 27, 2026Md Wahiduzzaman Suva, Esm E Moula Chowdhury Abha, Md Imtiaj Alam Sajin +2Sleep Stage ClassificationMultimodal Learning

    Department of Computer Science and Engineering, American International University-Bangladesh, Dhaka, 1229, Bangladesh · AI and Big Data Department, Woosong University, Daejeon, Republic of Korea

  2. Evaluating Bayesian deep learning for robust biomedical time-series classification under distribution shift: A sleep scoring case study

    Oct 26, 2026Mads Birch Sørensen, Ulrike Richter, Francois Gastambide +1Distribution Shift RobustnessTime Series Classification

    Technical University of Denmark, Denmark · H. Lundbeck A/S, Denmark

  3. ECG-SDI: Single-lead Electrocardiogram Enables Continuous Sleep Depth Index Profiling and Scalable Digital Biomarkers for Sleep Health

    Oct 16, 2026Donglin Xie, Qingshuo Zhao, Songchi Zhou +5Sleep Stage ClassificationElectrocardiography

    Institute of Medical Technology, Peking University Health Science Center, Beijing, China · National Institute of Health Data Science, Peking University, Beijing, China · Department of Computer Science, Tianjin University of Technology, Tianjin, China +6

  4. SpecBraM: What Should an EEG Foundation Model Predict? Masked Band-Power Prediction versus Waveform Reconstruction

    Oct 5, 2026Peng Xie, Yequan Bie, Jianda Mao +1ElectroencephalographySleep Stage Classification

    The Hong Kong University of Science and Technology

  5. COVER: Learning to Accept More in Selective Sleep Staging

    Oct 2, 2026Yukai Song, Yangfan Deng, Jijun Yin +2Selective PredictionSleep Stage Classification

    Department of Electrical and Computer Engineering, University of Pittsburgh · Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA · Department of Electrical and Computer Engineering, University of Maryland, College Park +1

  6. SemPSG: A Semantic Channel-Aware Foundation Model for Polysomnography Analysis

    Sep 29, 2026Junyu Chen, Chenxi Liu, Shiqin Tang +5Time Series Representation LearningTime-Series Foundation Models

    Center for Artificial Intelligence and Robotics, Hong Kong Institute of Science & Innovation, CAS · Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China · Department of Operations and Technology, Technical University of Munich

  7. Learning transferable human physiology from two million hours of sleep with SleepFM-2

    Sep 6, 2026Rahul Thapa, Christopher Sun, William Theodor Lehn-Schioler +14Clinical Outcome PredictionMultimodal Pretraining

    Department of Biomedical Data Science, Stanford University, Stanford, CA, USA · Department of Computer Science, Stanford University, Stanford, CA, USA · BrainCapture, Kongens Lyngby, Denmark +6

  8. Subject-Relative Micro-Motion and Sleep Dynamics for Near-Infrared Video Sleep Staging

    Sep 3, 2026Kunmin Jang, You Rim Choi, Hun Heo +5Sleep Stage ClassificationVideo Representation Learning

    Seoul National University · Seoul National University Hospital

  9. NanoSleep: A Parameter-Efficient Hybrid Temporal Convolutional Network for Single-Channel Sleep Stage Classification

    Aug 19, 2026S M Asif Hossain, Shruti KshirsagarSleep Stage ClassificationLightweight CNNs

    School of Computing, Wichita State University, Kansas, USA

  10. DualStabSleepNet: A Dual-Domain Diffusion Stabilization Network for Robust Sleep Staging

    Aug 17, 2026Chongjian Wang, Chen Liu, Junjie Gao +3Diffusion-Based DenoisingSleep Stage Classification

    School of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, 266590, Shandong, China · School of Artificial Intelligence, Shandong Women’s University, Jinan, 250352, Shandong, China · School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510641, Guangdong, China

  11. Comparative Analysis of State-of-the-Art Foundation Models for Sleep Analysis Under Channel Reduction

    Aug 14, 2026Hassan Mehdi, Riku Klen, Ayse Kosal Bulbul +5Sleep Stage ClassificationEEG Foundation Models

    Institute of Biomedicine, University of Turku, Finland · Turku PET Centre, University of Turku and Turku University Hospital, Finland · University College Cork, Ireland +3

  12. Personalized Scorer Modeling: A Learning-Based Framework for Deriving Robust Sleep Stage Labels from Multiple Experts

    Aug 12, 2026Seyyed Ali Hoseini, Javad Baseri, Hamid Saadatfar +2Sleep Stage ClassificationHuman-in-the-Loop Annotation

    Department of Electrical and Computer Engineering, University of Birjand, Birjand, South Khorasan, Iran

  13. SWINSleepNet: A Hierarchical Context-Aware Framework for Sleep Staging (v2)

    Aug 3, 2026Chongjian Wang, Junjie GaoSleep Stage ClassificationHybrid CNN-Transformer Architectures

    School of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, Shandong, China · School of Artificial Intelligence, Shandong Women’s University, Jinan 250352, Shandong, China

  14. Rethinking PPG-based Sleep Staging: Datasets, Metrics, and Benchmarks

    Aug 2, 2026Shuntian Zheng, Jiawei Wang, Cong Fu +4Sleep Stage ClassificationPhotoplethysmography

    Department of Computer Science, The University of Warwick · School of Engineering, The University of Warwick · Department of Neurology, Huashan Hospital, Fudan University +2

  15. LGFNet: A CTC-Guided Local-Global Fusion Framework for Single-Channel Sleep Staging

    Jul 28, 2026Chongjian Wang, Zhenghang Hou, Junjie Gao +3Cross-Subject EEG DecodingElectroencephalography

    School of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, 266590, Shandong, China · School of Artificial Intelligence, Shandong Women’s University, Jinan, 250352, Shandong, China · School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510641, Guangdong, China

  16. StageGuard: Physiologically Constrained Sleep Staging

    Jul 25, 2026Juntang Wang, Yihan Wang, Hao Wu +3Constrained DecodingSleep Stage Classification

    Zu Chongzhi Center, Duke Kunshan University Kunshan, China

  17. The RG-Flow Transformer: Encoding Scale-Free Dynamics in Scarce EEG

    Jul 11, 2026Dibakar SigdelTransformer InterpretabilityElectroencephalography

    Mindverse Computing LLC, Lynnwood, WA 98087 · 1Mindverse Computing LLC, Lynnwood, WA 98087

  18. Lightweight ML-Based Automatic Sleep Staging Framework with Constrained CNN and Mamba for Small-Sample EEG Datasets

    Jul 6, 2026Zihao Wei, Yulin Gong, Yudan LvEfficient Neural Network InferenceElectroencephalography

    School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun 130022, Jilin Province, China · Jilin University, Changchun 130012, Jilin Province, China

  19. SleepBand: Single-Source Domain Generalization for Sleep Staging via Physiologically Structured Spectral Modeling

    Jul 6, 2026Zhi Lu, Yang Hu, Yan ChenSleep Stage ClassificationEEG Decoding

    Laboratory of Intelligent Collaborative Computing, University of Electronic Science and Technology of China, Chengdu 611731, China · School of Information Science and Technology, University of Science and Technology of China, Hefei 230026, China · School of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, China

  20. Omni-Sleep: A Sleep Foundation Model via Hierarchical Contrastive Learning of CNS-ANS Dynamics

    Jul 4, 2026Zhoujie Hou, Song Wang, Kexin Lou +3Sleep Stage ClassificationLatent Dynamics Modeling

    Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China · Omni-Intelligence, Shenzhen, China · Shenzhen Loop Area Institute, Shenzhen, China

  21. Deep Sleep Classification via EEG Signal Criticality: A Passive BCI Approach for Sleep-Improvement Neurofeedback

    Jun 11, 2026Stanisław Narębski, Tomasz Komendziński, Tomasz M. RutkowskiSleep Stage ClassificationBrain-Computer Interfaces

    Nicolaus Copernicus University, Toru´n, Poland · Araya Inc., Tokyo, Japan · The University of Tokyo, Tokyo, Japan

  22. Next-Token Prediction Learns Generalisable Representations of Sleep Physiology

    Jun 8, 2026Jonathan F. Carter, Lionel TarassenkoSleep Stage ClassificationTime Series Classification

    Institute of Biomedical Engineering University of Oxford

  23. SleepExplain: Explainable Non-Rapid Eye Movement and Rapid Eye Movement Sleep Stage Classification from EEG Signal

    Jun 5, 2026Rafsan Jany, Md. Hamjajul Ashmafee, Iqram Hussain +1Sleep Stage ClassificationTime Series Classification

    Islamic University of Technology · Seoul National University

  24. Efficient Temporal Modeling for Mobile Sleep Staging via Lightweight Random Attention

    May 31, 2026Guisong Liu, Pengfei Wei, Jainsong Zhang +1Sleep Stage ClassificationAttention Mechanisms

    School of Biological Science and Medical Engineering Southeast University Nanjing, China · School of Computer Science & Software Engineering Shenzhen University Shenzhen, China · Donders Institute for Brain, Cognition and Behaviour Radboud University Medical Center Nijmegen, The Netherlands

  25. Sleep-stage efficient classification using a lightweight self-supervised model

    May 25, 2026Eldiane Borges dos Santos Durães, João Batista FlorindoEfficient Neural Network InferenceSleep Stage Classification

    Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Street Sergio Buarque de Holanda, 651, Campinas, Brazil

  26. Staging by the Book: Automatic Sleep Stage Classification Using Scoring Rules

    May 19, 2026Emil Hardarson, Konstantin Popov, Sigridur Sigurdardottir +3Sleep Stage ClassificationTime Series Classification

    Department of Computer Science, Reykjavik University, Reykjavik, Iceland · Reykjavik University Sleep Institute, Reykjavik University, Reykjavik, Iceland · Department of Engineering, Reykjavik University, Reykjavik, Iceland +1

  27. A Conflict-aware Evidential Framework for Reliable Sleep Stage Classification

    May 16, 2026Yunzhi Tian, Dekui Wang, Qirong Bu +3Sleep Stage ClassificationEvidential Deep Learning

    College of Computer Science, Northwest University, Xi’an, China.

  28. Rethinking Random Transformers as Adaptive Sequence Smoothers for Sleep Staging

    May 11, 2026Guisong Liu, Xin Gao, Martin Dresler +2Sleep Stage ClassificationTransformer

    School of Biological Science and Medical Engineering Southeast University Nanjing, China · University of Bath Bath, England · Donders Institute for Brain, Cognition and Behaviour Radboud University Medical Center Nijmegen, The Netherlands +1

  29. STDA-Net: Spectrogram-Based Domain Adaptation for cross-dataset Sleep Stage Classification

    May 7, 2026Unaza Tallal, Shruti Kshirsagar, Ankita ShuklaElectroencephalographySleep Stage Classification

    School of Computing, Wichita State University, 1845 N. Fairmount, Wichita, KS 67260, USA · Computer Science and Engineering Department, University of Nevada, Reno, NV, USA

  30. Demographic-Aware Transfer Learning for Sleep Stage Classification in Clinical Polysomnography

    May 4, 2026S M Asif Hossain, Shruti KshirsagarSleep Stage ClassificationFine-Tuning

    School of Computing, Wichita State University, Wichita, Kansas, USA