L-SeqSleepNet: Whole-cycle Long Sequence Modeling for Automatic Sleep Staging
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Marina De Vos | Kaare B. Mikkelsen | A. Mertins | M. Baumert | Huy P Phan | P. Koch | E. Heremans | Oliver Y. Ch'en | Kristian P. Lorenzen | Minh C. Tran
[1] Kaare B. Mikkelsen,et al. Automatic sleep scoring using patient-specific ensemble models and knowledge distillation for ear-EEG data , 2023, Biomed. Signal Process. Control..
[2] Shuicai Wu,et al. MRASleepNet: a multi-resolution attention network for sleep stage classification using single-channel EEG , 2022, Journal of neural engineering.
[3] S. Sanei,et al. SleepFCN: A Fully Convolutional Deep Learning Framework for Sleep Stage Classification Using Single-Channel Electroencephalograms , 2022, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[4] Heung-Il Suk,et al. TransSleep: Transitioning-Aware Attention-Based Deep Neural Network for Sleep Staging , 2022, IEEE Transactions on Cybernetics.
[5] Maarten De Vos,et al. Feature matching as improved transfer learning technique for wearable EEG , 2021, Biomed. Signal Process. Control..
[6] Kaare B. Mikkelsen,et al. Automatic sleep staging of EEG signals: recent development, challenges, and future directions , 2021, Physiological measurement.
[7] Kaare B. Mikkelsen,et al. Sleep Monitoring Using Ear-Centered Setups: Investigating the Influence From Electrode Configurations , 2021, IEEE Transactions on Biomedical Engineering.
[8] F. Faraci,et al. DeepSleepNet-Lite: A Simplified Automatic Sleep Stage Scoring Model With Uncertainty Estimates , 2021, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[9] Youfang Lin,et al. SalientSleepNet: Multimodal Salient Wave Detection Network for Sleep Staging , 2021, IJCAI.
[10] Maarten De Vos,et al. SleepTransformer: Automatic Sleep Staging With Interpretability and Uncertainty Quantification , 2021, IEEE Transactions on Biomedical Engineering.
[11] Cuntai Guan,et al. An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG , 2021, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[12] C. Igel,et al. U-Sleep: resilient high-frequency sleep staging , 2021, npj Digital Medicine.
[13] Babak Mohammadzadeh Asl,et al. Automatic Sleep Stage Classification Using Temporal Convolutional Neural Network and New Data Augmentation Technique from Raw Single-Channel EEG , 2021, Comput. Methods Programs Biomed..
[14] V. Thorey,et al. RobustSleepNet: Transfer Learning for Automated Sleep Staging at Scale , 2021, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[15] Behnam Neyshabur,et al. What is being transferred in transfer learning? , 2020, NeurIPS.
[16] Alexander Neergaard Olesen,et al. Automatic sleep stage classification with deep residual networks in a mixed-cohort setting , 2020, Sleep.
[17] Seunghyeok Back,et al. Intra- and inter-epoch temporal context network (IITNet) using sub-epoch features for automatic sleep scoring on raw single-channel EEG , 2020, Biomed. Signal Process. Control..
[18] Maarten De Vos,et al. XSleepNet: Multi-View Sequential Model for Automatic Sleep Staging , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[19] Akara Supratak,et al. TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG , 2020, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).
[20] Zheru Chi,et al. A Residual Based Attention Model for EEG Based Sleep Staging , 2020, IEEE Journal of Biomedical and Health Informatics.
[21] S. Redline,et al. Characterisation of cyclic alternating pattern during sleep in older men and women using large population studies. , 2020, Sleep.
[22] Preben Kidmose,et al. Accurate whole-night sleep monitoring with dry-contact ear-EEG , 2019, Scientific Reports.
[23] V. Thorey,et al. Dreem Open Datasets: Multi-Scored Sleep Datasets to Compare Human and Automated Sleep Staging , 2019, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[24] Mathias Baumert,et al. Automatic A-Phase Detection of Cyclic Alternating Patterns in Sleep Using Dynamic Temporal Information , 2019, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[25] Maarten De Vos,et al. Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning , 2019, IEEE Transactions on Biomedical Engineering.
[26] U. Rajendra Acharya,et al. SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach , 2019, PloS one.
[27] Stefan Debener,et al. Sleep EEG Derived From Behind-the-Ear Electrodes (cEEGrid) Compared to Standard Polysomnography: A Proof of Concept Study , 2018, Front. Hum. Neurosci..
[28] Stefan Debener,et al. Machine‐learning‐derived sleep–wake staging from around‐the‐ear electroencephalogram outperforms manual scoring and actigraphy , 2018, Journal of sleep research.
[29] Oliver Y. Chén,et al. SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging , 2018, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[30] Maarten De Vos,et al. DNN Filter Bank Improves 1-Max Pooling CNN for Single-Channel EEG Automatic Sleep Stage Classification , 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[31] Guo-Qiang Zhang,et al. The National Sleep Research Resource: towards a sleep data commons , 2018, BCB.
[32] Laurent Vercueil,et al. A convolutional neural network for sleep stage scoring from raw single-channel EEG , 2018, Biomed. Signal Process. Control..
[33] R. Stickgold,et al. Characterizing sleep spindles in 11,630 individuals from the National Sleep Research Resource , 2017, Nature Communications.
[34] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[35] Michael Labanowski,et al. Physiology, Sleep Stages , 2017 .
[36] Chao Wu,et al. DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[37] Hao Dong,et al. Mixed Neural Network Approach for Temporal Sleep Stage Classification , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[38] Geoffrey E. Hinton,et al. Layer Normalization , 2016, ArXiv.
[39] Aaron C. Courville,et al. Recurrent Batch Normalization , 2016, ICLR.
[40] S. Debener,et al. Unobtrusive ambulatory EEG using a smartphone and flexible printed electrodes around the ear , 2015, Scientific Reports.
[41] Christopher D. Manning,et al. Effective Approaches to Attention-based Neural Machine Translation , 2015, EMNLP.
[42] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[43] R. Rosenberg,et al. The American Academy of Sleep Medicine inter-scorer reliability program: sleep stage scoring. , 2013, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.
[44] S. Debener,et al. How about taking a low-cost, small, and wireless EEG for a walk? , 2012, Psychophysiology.
[45] Aeilko H. Zwinderman,et al. Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the EEG , 2000, IEEE Transactions on Biomedical Engineering.
[46] Jeffrey M. Hausdorff,et al. Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .
[47] J. Samet,et al. The Sleep Heart Health Study: design, rationale, and methods. , 1997, Sleep.
[48] S. Hochreiter,et al. Long Short-Term Memory , 1997, Neural Computation.
[49] E. Wolpert. A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects. , 1969 .
[50] I. Andersen,et al. Validation of the Danish STOP-Bang obstructive sleep apnoea questionnaire in a public sleep clinic. , 2018, Danish medical journal.
[51] A. Chesson,et al. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology, and Techinical Specifications , 2007 .