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PhysioNet 2018 Challenge: Sleep Arousal Detection PSG (Training)

nm000225 · 92 high-confidence citations

1. Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review

   Shenda Hong, Yuxi Zhou, Junyuan Shang, Cao Xiao, Jimeng Sun · 2020 · Computers in Biology and Medicine

   Cites data paper 446 citations

2. U-Sleep: resilient high-frequency sleep staging

   Mathias Perslev, Sune Darkner, Lykke Kempfner, Miki Nikolic, Poul Jennum, Christian Igel · 2021 · npj Digital Medicine

   Cites data paper 332 citations

3. XSleepNet: Multi-View Sequential Model for Automatic Sleep Staging

   Huy Phan, Oliver Y. Chén, Minh C. Tran, Philipp Koch, Alfred Mertins, Maarten De Vos · 2021 · IEEE Transactions on Pattern Analysis and Machine Intelligence

   Cites data paper 267 citations

4. Uncovering the structure of clinical EEG signals with self-supervised\n learning

   Hubert Banville, Omar Chehab, Aapo Hyvärinen, Denis A. Engemann, Alexandre Gramfort · 2020 · arXiv (Cornell University)

   Cites data paper 246 citations

5. Self-Supervised Learning for Electroencephalography

   M. Rafiei, L. Gauthier, H. Adeli, Daniel Takabi · 2022 · IEEE Transactions on Neural Networks and Learning Systems

   Cites data paper 239 citations

6. Deep learning for automated sleep staging using instantaneous heart rate

   Niranjan Sridhar, Ali Shoeb, Philip Stephens, Alaa Kharbouch, David Ben Shimol, Joshua Burkart, Atiyeh Ghoreyshi, Lance Myers · 2020 · npj Digital Medicine

   Cites data paper 138 citations

7. Automatic sleep staging of EEG signals: recent development, challenges, and future directions

   Huy Phan, Kaare B. Mikkelsen · 2022 · Physiological Measurement

   Cites data paper 133 citations

8. U-Time: A Fully Convolutional Network for Time Series Segmentation\n Applied to Sleep Staging

   Mathias Perslev, Michael Hejselbak Jensen, Sune Darkner, Poul Jennum, Christian Igel · 2019 · arXiv (Cornell University)

   Cites data paper 132 citations

9. DeepSleepNet-Lite: A Simplified Automatic Sleep Stage Scoring Model with Uncertainty Estimates

   Luigi Fiorillo, Paolo Favaro, Francesca Dalia Faraci · 2021 · arXiv (Cornell University)

   Cites data paper 110 citations

10. Self-Supervised Contrastive Learning for Medical Time Series: A Systematic Review

    Ziyu Liu, Azadeh Alavi, Minyi Li, Xiang Zhang · 2023 · Sensors

    Cites data paper 99 citations

11. Reinventing polysomnography in the age of precision medicine

    Diane C Lim, Diego R. Mazzotti, Kate Sutherland, Jesse Mindel, Jinyoung Kim, Peter A. Cistulli, Ulysses J. Magalang, Allan I Pack, Philip de Chazal, Thomas Penzel · 2020 · Sleep Medicine Reviews

    Cites data paper 92 citations

12. MAEEG: Masked Auto-encoder for EEG Representation Learning

    H. Chien, Hanlin Goh, Christopher M. Sandino, Joseph Y. Cheng · 2022 · ArXiv

    Cites data paper 91 citations

13. State-of-the-Art Deep Learning Methods on Electrocardiogram Data: Systematic Review

    Γεώργιος Πετμεζάς, Leandros Stefanopoulos, Vassilis Kilintzis, Andreas Tzavelis, John A. Rogers, Aggelos K. Katsaggelos, Nicos Maglaveras · 2022 · JMIR Medical Informatics

    Cites data paper 90 citations

14. Deep learning in the cross-time frequency domain for sleep staging from a single-lead electrocardiogram

    Qiao Li, Qichen Li, Chengyu Liu, Supreeth P. Shashikumar, Shamim Nemati, Gari D. Clifford · 2018 · Physiological Measurement

    Cites data paper 82 citations

15. SleePyCo: Automatic Sleep Scoring with Feature Pyramid and Contrastive Learning

    Seongju Lee, Yeonguk Yu, Seunghyeok Back, H. Seo, Kyoobin Lee · 2022 · ArXiv

    Cites data paper 65 citations

16. Self-supervised Learning for Electroencephalogram: A Systematic Survey

    Weining Weng, Yang Gu, Shuai Guo, Yuan Ma, Zhaohua Yang, Yuchen Liu, Yiqiang Chen · 2024 · ACM Computing Surveys

    Cites data paper 63 citations

17. SleepPPG-Net: A Deep Learning Algorithm for Robust Sleep Staging From Continuous Photoplethysmography

    Kevin Kotzen, Peter H. Charlton, Sharon Salabi, L. Amar, A. Landesberg, J. Behar · 2022 · IEEE Journal of Biomedical and Health Informatics

    Cites data paper 58 citations

18. Unsupervised EEG Artifact Detection and Correction

    Sari Saba-Sadiya, Eric Chantland, Tuka Alhanai, Taosheng Liu, Mohammad M. Ghassemi · 2021 · Frontiers in Digital Health

    Cites data paper 55 citations

19. Non-invasive Techniques for Monitoring Different Aspects of Sleep: A Comprehensive Review

    Zawar Hussain, Quan Z. Sheng, Wei Emma Zhang, Jorge Ortiz, Seyedamin Pouriyeh · 2022 · ACM Transactions on Computing for Healthcare

    Cites data paper 53 citations

20. DeepSleep convolutional neural network allows accurate and fast detection of sleep arousal

    Hongyang Li, Yuanfang Guan · 2021 · Communications Biology

    Cites data paper 52 citations

21. Transfer learning from ECG to PPG for improved sleep staging from wrist-worn wearables

    Qiao Li, Qichen Li, Ayse S. Cakmak, Giulia Da Poian, Donald L. Bliwise, Viola Vaccarino, Amit Shah, Gari D. Clifford · 2021 · Physiological Measurement

    Cites data paper 51 citations

22. Sleep Apnea Detection From Variational Mode Decomposed EEG Signal Using a Hybrid CNN-BiLSTM

    Tanvir Mahmud, Ishtiaque Ahmed Khan, Talha Ibn Mahmud, Shaikh Anowarul Fattah, Wei‐Ping Zhu, M. Omair Ahmad · 2021 · IEEE Access

    Cites data paper 50 citations

23. SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals

    R. Thapa, Bryan He, Magnus Ruud Kjær, IV HyattE.Moore, G. Ganjoo, Emmanuel Mignot, James Zou · 2024 · ArXiv

    Cites data paper 50 citations

24. Research and application of deep learning-based sleep staging: Data, modeling, validation, and clinical practice

    Huijun Yue, Zhuqi Chen, Wenbin Guo, Lin Sun, Yidan Dai, Yiming Wang, Wenjun Ma, Xiaomao Fan, Weiping Wen, Wenbin Lei · 2024 · Sleep Medicine Reviews

    Cites data paper 47 citations

25. U-Sleep’s resilience to AASM guidelines

    Luigi Fiorillo, Giuliana Monachino, Julia van der Meer, Marco Pesce, Jan D. Warncke, Markus H. Schmidt, Claudio L. Bassetti, Athina Tzovara, Paolo Favaro, Francesca Dalia Faraci · 2023 · npj Digital Medicine

    Cites data paper 47 citations

26. Robust learning from corrupted EEG with dynamic spatial filtering

    Hubert Banville, Sean U. N. Wood, Chris Aimone, Denis A. Engemann, Alexandre Gramfort · 2022 · NeuroImage

    Cites data paper 46 citations

27. Artifact Detection and Correction in EEG data: A Review

    Sari Saba-Sadiya, Tuka Alhanai, Mohammad M. Ghassemi · 2021 · n/a

    Cites data paper 40 citations

28. Automated Detection of Sleep Arousals From Polysomnography Data Using a Dense Convolutional Neural Network

    Matthew Howe-Patterson, Bahareh Pourbabaee, Frédéric Bénard · 2018 · Computing in cardiology

    Cites data paper 39 citations

29. Multimodal spatio-temporal-spectral fusion for deep learning applications in physiological time series processing: A case study in monitoring the depth of anesthesia

    Nooshin Bahador, Jarno Jokelainen, Seppo Mustola, Jukka Kortelainen · 2021 · Information Fusion

    Cites data paper 39 citations

30. Recent Advancement in Sleep Technologies: A Literature Review on Clinical Standards, Sensors, Apps, and AI Methods

    Gozde Cay, Vignesh Ravichandran, Shehjar Sadhu, Alyssa Hillary Zisk, Amy L. Salisbury, Dhaval Solanki, Kunal Mankodiya · 2022 · IEEE Access

    Cites data paper 37 citations

31. Automatic Sleep-Arousal Detection with Single-Lead EEG Using Stacking Ensemble Learning

    Ying‐Ren Chien, Cheng-Hsuan Wu, Hen‐Wai Tsao · 2021 · Sensors

    Cites data paper 37 citations

32. Supervised and unsupervised machine learning for automated scoring of sleep–wake and cataplexy in a mouse model of narcolepsy

    Ioannis Exarchos, Anna Rogers, Lauren M. Aiani, Robert E. Gross, Gari D. Clifford, Nigel P. Pedersen, Jon T. Willie · 2019 · SLEEP

    Cites data paper 34 citations

33. MSED: A Multi-Modal Sleep Event Detection Model for Clinical Sleep Analysis

    Alexander Neergaard Zahid, Poul Jennum, Emmanuel Mignot, Helge B. D. Sørensen · 2023 · IEEE Transactions on Biomedical Engineering

    Cites data paper 34 citations

34. A Review of Methods for Sleep Arousal Detection Using Polysomnographic Signals

    Xiangyu Qian, Ye Qiu, Qingzu He, Yuer Lu, Hai Lin, Fei Xu, Fangfang Zhu, Zhi Long Liu, Xiang Li, Yuping Cao, Jianwei Shuai · 2021 · Brain Sciences

    Cites data paper 34 citations

35. Applications of Self-Supervised Learning to Biomedical Signals: A Survey

    Federico Del Pup, Manfredo Atzori · 2023 · IEEE Access

    Cites data paper 32 citations

36. Generalizable Sleep Staging via Multi-Level Domain Alignment

    Jiquan Wang, Sha Zhao, Haiteng Jiang, Shijian Li, Tao Li, Gang Pan · 2024 · Proceedings of the AAAI Conference on Artificial Intelligence

    Cites data paper 29 citations

37. Practical Lessons on 12-Lead ECG Classification: Meta-Analysis of Methods From PhysioNet/Computing in Cardiology Challenge 2020

    Shenda Hong, Wenrui Zhang, Chenxi Sun, Yuxi Zhou, Hongyan Li · 2022 · Frontiers in Physiology

    Cites data paper 28 citations

38. Brain and brain-heart Granger causality during wakefulness and sleep

    Helmi Abdalbari, Mohammad Durrani, Shivam Pancholi, Nikhil Patel, Slawomir J. Nasuto, Nicoletta Nicolaou · 2022 · Frontiers in Neuroscience

    Cites data paper 27 citations

39. EEGMamba: An EEG foundation model with Mamba

    Jiquan Wang, Sha Zhao, Zhiling Luo, Yangxuan Zhou, Shijian Li, Gang Pan · 2025 · Neural networks : the official journal of the International Neural Network Society

    Cites data paper 27 citations

40. Pediatric Automatic Sleep Staging: A Comparative Study of State-of-the-Art Deep Learning Methods

    Huy Phan, Alfred Mertins, Mathias Baumert · 2022 · IEEE Transactions on Biomedical Engineering

    Cites data paper 26 citations

41. Advanced polysomnographic analysis for OSA: A pathway to personalized management?

    Philip de Chazal, Kate Sutherland, Peter A. Cistulli · 2019 · Respirology

    Cites data paper 26 citations

42. Sleep Stage Classification With Multi-Modal Fusion and Denoising Diffusion Model

    Xu Xu, Fengyu Cong, Yongyong Chen, Junxin Chen · 2024 · IEEE Journal of Biomedical and Health Informatics

    Cites data paper 26 citations

43. Automatic Sleep Arousals Detection From Polysomnography Using Multi-Convolution Neural Network and Random Forest

    Yitian Liu, Hongxing Liu, Bufang Yang · 2020 · IEEE Access

    Cites data paper 25 citations

44. EEG Signal Multichannel Frequency-Domain Ratio Indices for Drowsiness Detection Based on Multicriteria Optimization

    Igor Stančin, Nikolina Frid, Mario Cifrek, Alan Jović · 2021 · Sensors

    Cites data paper 25 citations

45. Sleep staging based on single-channel EEG and EOG with Tiny U-Net

    Jingyi Lu, Chang Yan, Jianqing Li, Chengyu Liu · 2023 · Computers in Biology and Medicine

    Cites data paper 22 citations

46. Machine-Learning-Based-Approaches for Sleep Stage Classification Utilising a Combination of Physiological Signals: A Systematic Review

    Haifa Almutairi, Ghulam Mubashar Hassan, Amitava Datta · 2023 · Applied Sciences

    Cites data paper 21 citations

47. Hybrid scattering-LSTM networks for automated detection of sleep arousals

    Philip Warrick, Vincent Lostanlen, Masun Nabhan Homsi · 2019 · Physiological Measurement

    Cites data paper 21 citations

48. A foundational transformer leveraging full night, multichannel sleep study data accurately classifies sleep stages

    Benjamin Fox, Joy Jiang, Sajila Wickramaratne, Patricia Kovatch, Mayte Suárez‐Fariñas, Neomi Shah, Ankit Parekh, Girish N. Nadkarni · 2025 · SLEEP

    Cites data paper 20 citations

49. Automated Recognition of Sleep Arousal Using Multimodal and Personalized Deep Ensembles of Neural Networks

    Andrea Patanè, Shadi Ghiasi, Enzo Pasquale Scilingo, Marta Kwiatkowska · 2018 · Computing in cardiology

    Cites data paper 19 citations

50. Dimensionality reduction for EEG-based sleep stage detection: comparison of autoencoders, principal component analysis and factor analysis

    Alexandra-Maria Tăuţan, Alessandro C. Rossi, Ruben de Francisco, Bogdan Ionescu · 2020 · Biomedizinische Technik/Biomedical Engineering

    Cites data paper 19 citations

51. Multimodal Polysomnography-Based Automatic Sleep Stage Classification via Multiview Fusion Network

    Yiwei Lin, Mengying Wang, Fengdan Hu, Xu Cheng, Jinshan Xu · 2023 · IEEE Transactions on Instrumentation and Measurement

    Cites data paper 18 citations

52. Cross-scenario automatic sleep stage classification using transfer learning and single-channel EEG

    Zhengling He, Minfang Tang, Peng Wang, Lidong Du, Xianxiang Chen, Gang Cheng, Zhen Fang · 2022 · Biomedical Signal Processing and Control

    Cites data paper 18 citations

53. Automatic sleep-stage classification of heart rate and actigraphy data using deep and transfer learning approaches

    Yaopeng J. X. Ma, Johannes Zschocke, M. Glos, Maria Kluge, T. Penzel, J. Kantelhardt, R. Bartsch · 2023 · Computers in biology and medicine

    Cites data paper 18 citations

54. Automatic Detection of Target Regions of Respiratory Effort-Related Arousals Using Recurrent Neural Networks

    H.M. þráinsson, Hanna Ragnarsdóttir, Guðni Fannar Kristjánsson, Bragi Marinósson, Eysteinn Finnsson, Eysteinn Gunnlaugsson, Sigurður Ægir Jónsson, Jón S. Ágústsson, Halla Helgadóttir · 2018 · Computing in cardiology

    Cites data paper 17 citations

55. Promoting cross-modal representations to improve multimodal foundation models for physiological signals

    Ching Fang, Chris Sandino, Behrooz Mahasseni, Juri Minxha, Hadi Pouransari, Erdrin Azemi, Ali Moin, Ellen L. Zippi · 2024 · ArXiv

    Cites data paper 17 citations

56. Automatic Sleep Stage Detection: A Study on the Influence of Various PSG Input Signals

    Alexandra-Maria Tăuţan, Alessandro C. Rossi, Ruben de Francisco, Bogdan Ionescu · 2020 · n/a

    Cites data paper 16 citations

57. MSleepNet: A Semi-Supervision-Based Multiview Hybrid Neural Network for Simultaneous Sleep Arousal and Sleep Stage Detection

    Hongmei Liu, Haibo Zhang, Baozhu Li, Xinge Yu, Yuan Zhang, Thomas Penzel · 2024 · IEEE Transactions on Instrumentation and Measurement

    Cites data paper 15 citations

58. Sleep Apnea Detection Using EEG: A Systematic Review of Datasets, Methods, Challenges, and Future Directions

    Shireen Fathima, Maaz Ahmed · 2025 · Annals of Biomedical Engineering

    Cites data paper 15 citations

59. Sleep staging algorithm based on smartwatch sensors for healthy and sleep apnea populations

    Fernanda B. Silva, Luisa Fernanda Suárez Uribe, Felipe X. Cepeda, Vitor F.S. Alquati, Joao Paulo Guimaraes, Yuri G.A. Silva, Orlem L. dos Santos, Alberto A. de Oliveira, Gabriel H. M. de Aguiar, Mônica L. Andersen, Sérgio Tufik, Won Yong Lee, Lin Tzy Li, Otávio A. B. Penatti · 2024 · Sleep Medicine

    Cites data paper 14 citations

60. Deep convolutional architecture‐based hybrid learning for sleep arousal events detection through single‐lead EEG signals

    Andia Foroughi, Fardad Farokhi, Fereidoun Nowshiravan Rahatabad, Alireza Kashaninia · 2023 · Brain and Behavior

    Cites data paper 14 citations

61. Using Auxiliary Loss to Improve Sleep Arousal Detection With Neural Network

    Bálint Varga, Márton Görög, Péter Hajas · 2018 · Computing in cardiology

    Cites data paper 14 citations

62. Multimodal Sleep Signals-Based Automated Sleep Arousal Detection

    Guangxin Zhou, Runzhi Li, Shuo Zhang, Jing Wang, Jingzhe Ma · 2020 · IEEE Access

    Cites data paper 13 citations

63. SleepViTransformer: Patch-based sleep spectrogram transformer for automatic sleep staging

    L. Peng, Yanzhen Ren, Zhiheng Luan, Xiong Chen, Xiuping Yang, Weiping Tu · 2023 · Biomed. Signal Process. Control.

    Cites data paper 13 citations

64. A systematic review of deep learning methods for modeling electrocardiograms during sleep

    Chenxi Sun, Shenda Hong, Jingyu Wang, Xiaosong Dong, Fang Han, Hongyan Li · 2022 · Physiological Measurement

    Cites data paper 12 citations

65. Macro-Sleep Staging With ECG-Derived Instantaneous Heart Rate and Respiration Signals and Multi-Input 1-D CNN–BiGRU

    Roneel V. Sharan, Hiroki Takeuchi, Akifumi Kishi, Yoshiharu Yamamoto · 2024 · IEEE Transactions on Instrumentation and Measurement

    Cites data paper 11 citations

66. Learning with self-supervision on EEG data

    Alexandre Gramfort, Hubert Banville, Omar Chehab, Aapo Hyvärinen, Denis A. Engemann · 2021 · n/a

    Cites data paper 11 citations

67. AI-driven approaches for automatic detection of sleep apnea/hypopnea based on human physiological signals: a review

    Dandan Peng, Le Sun, Qian Zhou, Yanchun Zhang · 2024 · Health Information Science and Systems

    Cites data paper 11 citations

68. State-of-the-art sleep arousal detection evaluated on a comprehensive clinical dataset

    Franz Ehrlich, Tony Sehr, Moritz Brandt, Martin Schmidt, Hagen Malberg, Martin Sedlmayr, Miriam Goldammer · 2024 · Scientific Reports

    Cites data paper 11 citations

69. SleepTight: Identifying Sleep Arousals Using Inter and Intra-Relation of Multimodal Signals

    Tanuka Bhattacharjee, Deepan Das, Shahnawaz Alam, Achuth Rao M V, Prasanta Ghosh, Ayush Ranjan Lohani, Rohan Banerjee, Anirban Dutta Choudhury, Arpan Pal · 2018 · Computing in cardiology

    Cites data paper 10 citations

70. Assessment of Cardiorespiratory Interactions during Apneic Events in Sleep via Fuzzy Kernel Measures of Information Dynamics

    Ivan Lazić, Riccardo Pernice, Tatjana Lončar-Turukalo, Gorana Mijatović, Luca Faes · 2021 · Entropy

    Cites data paper 10 citations

71. Healthy Young POLes – HYPOL database with synchronised beat-to-beat heart rate and blood pressure signals

    Przemysław Guzik, Tomasz Krauze, Andrzej Wykrętowicz, Jarosław Piskorski · 2023 · Journal of Medical Science

    Cites data paper 10 citations

72. SelANet: decision-assisting selective sleep apnea detection based on confidence score

    Beomjun Bark, Borum Nam, In Young Kim · 2023 · BMC Medical Informatics and Decision Making

    Cites data paper 10 citations

73. Automatic Scoring of Non-Apnoea Arousals Using the Polysomnogram

    Nadi Sadr, Philip de Chazal · 2018 · Computing in cardiology

    Cites data paper 9 citations

74. Knowledge extraction based on wavelets and DNN for classification of physiological signals: Arousals case

    Edwar Macias Toro, Antoni Morell, Javier Serrano, José López Vicario · 2018 · Computing in cardiology

    Cites data paper 9 citations

75. Novel welch-transform based enhanced spectro-temporal analysis for cognitive microsleep detection using a single electrode EEG

    Jash Shah, Amit Chougule, Vinay Chamola, Amir Hussain · 2023 · Neurocomputing

    Cites data paper 9 citations

76. DeepSleep 2.0: Automated Sleep Arousal Segmentation via Deep Learning

    Róbert Fónod · 2022 · AI

    Cites data paper 9 citations

77. Boosting automated sleep staging performance in big datasets using population subgrouping

    Samaneh Nasiri, Gari D. Clifford · 2021 · SLEEP

    Cites data paper 9 citations

78. Advances in Modeling and Interpretability of Deep Neural Sleep Staging: A Systematic Review

    Reza Soleimani, Jeffrey Barahona, Yuhan Chen, Alper Bozkurt, Michael A. Daniele, Vladimir A. Pozdin, Edgar Lobatón · 2023 · Physiologia

    Cites data paper 9 citations

79. Development of generalizable automatic sleep staging using heart rate and movement based on large databases

    Joonnyong Lee, Hee Chan Kim, Yu Jin Lee, Saram Lee · 2023 · Biomedical Engineering Letters

    Cites data paper 9 citations

80. Interbeat interval-based sleep staging: work in progress toward real-time implementation

    G. Garcia-Molina, Jiewei Jiang · 2022 · Physiological Measurement

    Cites data paper 9 citations

81. Automated Sleep Arousal Detection Based on EEG Envelograms

    Filip Plešinger, Petr Nejedlý, Ivo Viščor, Petr Andrla, Josef Halámek, Pavel Jurák · 2018 · Computing in cardiology

    Cites data paper 8 citations

82. Comparison of deep transfer learning algorithms and transferability measures for wearable sleep staging

    Samuel H. Waters, Gari D. Clifford · 2022 · BioMedical Engineering OnLine

    Cites data paper 8 citations

83. Automatic detection of non-apneic sleep arousal regions from polysomnographic recordings

    Jamileh Karimi, Babak Mohammadzadeh Asl · 2021 · Biomedical Signal Processing and Control

    Cites data paper 8 citations

84. Multi-View Self-Supervised Learning For Multivariate Variable-Channel Time Series

    Thea Brüsch, Mikkel N. Schmidt, T. Alstrøm · 2023 · 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)

    Cites data paper 8 citations

85. Obstructive Sleep Apnea Detection Using Sleep Architecture

    Juan Liu, Qin Li, Yi Xin, Lu Xiao · 2020 · n/a

    Cites data paper 7 citations

86. Classification of Sleep Arousal using Compact CNN

    Ahmed M. Eldaraa, Hamza Baali, Abdesselam Bouzerdoum, Samir Brahim Belhaouari, Tanvir Alam, Anas S. Abdel Rahman · 2020 · 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies (ICIoT)

    Cites data paper 7 citations

87. Evaluating Convolutional and Recurrent Neural Network Architectures for Respiratory-Effort Related Arousal Detection during Sleep

    Niranjan Sridhar, Ali Shoeb · 2018 · Computing in cardiology

    Cites data paper 7 citations

88. Arousal Detection in Obstructive Sleep Apnea using Physiology-Driven Features

    Sandya Subramanian, Shubham Chamadia, S. Chakravarty · 2018 · Computing in cardiology

    Cites data paper 7 citations

89. An Automatic Sleep Staging Model Combining Feature Learning and Sequence Learning

    Yinghao Li, Zhenghui Gu, Zichao Lin, Zhuliang Yu, Yuanqing Li · 2020 · n/a

    Cites data paper 7 citations

90. Sleep Quality Evaluation Based on Single-Lead Wearable Cardiac Cycle Acquisition Device

    Yang Li, Jianqing Li, Chang Yan, Kejun Dong, Zhiyu Kang, Hongxing Zhang, Chengyu Liu · 2022 · Sensors

    Cites data paper 7 citations

91. PhysioNet 2018 Challenge: Sleep Arousal Detection PSG (Training)

    Mohammad M. Ghassemi, Benjamin E. Moody, Li-wei H. Lehman, Christopher Song, Qiao Li, Haoqi Sun, Roger G. Mark, M. Brandon Westover, Gari D. Clifford · 2026 · UC San Diego

    Cites data paper

92. PhysioNet 2018 Challenge: Sleep Arousal Detection PSG (Training)

    Mohammad M. Ghassemi, Benjamin E. Moody, Li-wei H. Lehman, Christopher Song, Qiao Li, Haoqi Sun, Roger G. Mark, M. Brandon Westover, Gari D. Clifford · 2026 · Open MIND

    Cites data paper

No citations of that kind for this dataset.