Publications citing You Snooze You Win: The PhysioNet/Computing in Cardiology Challenge 2018 v1.0.0

Applications of Self-Supervised Learning to Biomedical Signals: where are we now
Federico Del Pup, Manfredo Atzori. 2023. Cites: paper

U-Sleep’s resilience to AASM guidelines
Luigi Fiorillo, Giuliana Monachino, Julia van der Meer et al. npj Digital Medicine, 2023. Cites: paper

A Review on Detection and Correction of Artifacts from EEG Data
Sagar S. Motdhare, Garima Mathur. International Journal of Recent Technology and Engineering (IJRTE), 2023. Cites: paper

MSED: A Multi-Modal Sleep Event Detection Model for Clinical Sleep Analysis
Alexander Neergaard Zahid, Poul Jennum, Emmanuel Jean-Marie Mignot et al. IEEE Transactions on Biomedical Engineering, 2023. Cites: paper

Signal Processing and Machine Learning for Smart Sensing Applications
Ying‐Ren Chien, Mu Zhou, Ao Peng et al. Sensors, 2023. Cites: paper

Applications of Self-Supervised Learning to Biomedical Signals: A Survey
Federico Del Pup, Manfredo Atzori. IEEE Access, 2023. Cites: paper

A Systematic Review of Electroencephalography Open Datasets and Their Usage With Deep Learning Models
Alberto Nogales, Álvaro José García-Tejedor. IEEE Access, 2023. Cites: paper

Biomedical Signal Processing for Automated Detection of Sleep Arousals Based on Multi-Physiological Signals with Ensemble Learning Methods
Navabeh Sadat Jalili Shani, Mohammad Hassan Moradi. Springer eBooks, 2023. Cites: paper

Machine learning approaches for predicting sleep arousal response based on heart rate variability, oxygen saturation, and body profiles
Chih-Fan Kuo, Cheng-Yu Tsai, Wun-Hao Cheng et al. Digital Health, 2023. Cites: paper

Automatic Sleep Arousal Detection Using Heart Rate From a Single-Lead Electrocardiogram
"Franz Ehrlich, Johannes Bender, Hagen Malberg et al. Computing in cardiology, 2022. Cites: paper

Sleep Quality Evaluation Based on Single-Lead Wearable Cardiac Cycle Acquisition Device
Yang Li, Jianqing Li, Chang Yan et al. Sensors, 2022. Cites: paper

An Automatic Sleep Arousal Detection Method by Enhancing U-Net with Spatial-channel Attention
Yen-Ning Su, Chih‐En Kuo. IEEE International Conference on Big Data (BigData), 2022. Cites: paper

Cross-scenario automatic sleep stage classification using transfer learning and single-channel EEG
Zhengling He, Minfang Tang, Peng Wang et al. Biomedical Signal Processing and Control, 2022. Cites: paper

Time-Frequency Ridge Analysis of Sleep Stage Transitions
Christopher McCausland, Pardis Biglarbeigi, Raymond Bond et al. IEEE Signal Processing in Medicine and Biology Symposium, 2022. Cites: paper

SleepPPG-Net: A Deep Learning Algorithm for Robust Sleep Staging From Continuous Photoplethysmography
Kevin Kotzen, Peter H Charlton, Sharon Salabi et al. IEEE Journal of Biomedical and Health Informatics, 2022. Cites: paper

U-Sleep: resilient to AASM guidelines
Luigi Fiorillo, Giuliana Monachino, Julia van der Meer et al. Research Square, 2022. Cites: paper

Brain and brain-heart Granger causality during wakefulness and sleep
Helmi Abdalbari, Mohammad Durrani, Shivam Pancholi et al. Frontiers in Neuroscience, 2022. Cites: paper

Comparison of deep transfer learning algorithms and transferability measures for wearable sleep staging
Samuel H. Waters, Gari D. Clifford. BioMedical Engineering OnLine, 2022. Cites: paper

ELEKTRA: ELEKTRokardiomatrix application to biometric identification with convolutional neural networks
Caterina Fuster-Barceló, Pedro Peris Lopez, Carmen Cámara. Neurocomputing, 2022. Cites: paper

A systematic review of deep learning methods for modeling electrocardiograms during sleep
Chenxi Sun, Shenda Hong, Jingyu Wang et al. Physiological Measurement, 2022. Cites: paper

State-of-the-Art Deep Learning Methods on Electrocardiogram Data: Systematic Review
Γεώργιος Πετμεζάς, Leandros Stefanopoulos, Vassilis Kilintzis et al. JMIR Medical Informatics, 2022. Cites: paper

Automatic sleep scoring with LSTM networks: impact of time granularity and input signals
Alexandra-Maria Tăuţan, Alessandro C. Rossi, Bogdan Emanuel Ionescu. Biomedizinische Technik/Biomedical Engineering, 2022. Cites: paper

Pediatric Automatic Sleep Staging: A Comparative Study of State-of-the-Art Deep Learning Methods
Huy Phan, Alfred Mertins, Mathias Baumert. IEEE Transactions on Biomedical Engineering, 2022. Cites: paper

Feature Imitating Networks
Sari Saba-Sadiya, Tuka Alhanai, Mohammad M. Ghassemi. IEEE International Conference on Acoustics Speech and Signal Processing, 2022. Cites: paper

How Machine Learning is Powering Neuroimaging to Improve Brain Health
Nalini Singh, Jordan B. Harrod, Sandya Subramanian et al. Neuroinformatics, 2022. Cites: paper

Automatic sleep staging of EEG signals: recent development, challenges, and future directions
Huy Phan, Kaare B. Mikkelsen. Physiological Measurement, 2022. Cites: paper

Non-invasive Techniques for Monitoring Different Aspects of Sleep: A Comprehensive Review
Zawar Hussain, Quan Z. Sheng, Wei Emma Zhang et al. ACM Transactions on Computing for Healthcare, 2022. Cites: paper

DeepSleep 2.0: Automated Sleep Arousal Segmentation via Deep Learning
Róbert Fónod. AI, 2022. Cites: paper

Fractal nature of arterial blood oxygen saturation data
Gennady P. Chuiko, Yevhen S. Darnapuk. RADIOELECTRONIC AND COMPUTER SYSTEMS, 2022. Cites: paper

Robust learning from corrupted EEG with dynamic spatial filtering
Hubert J. Banville, Sean U. N. Wood, Chris Aimone et al. NeuroImage, 2022. Cites: paper

Enabling real-world EEG applications with deep learning
Hubert J. Banville. theses.fr (ABES), 2022. Cites: paper

Practical Lessons on 12-Lead ECG Classification: Meta-Analysis of Methods From PhysioNet/Computing in Cardiology Challenge 2020
Shenda Hong, Wenrui Zhang, Chenxi Sun et al. Frontiers in Physiology, 2022. Cites: paper

Abdominal Electromyograms Mining: Breathing Patterns of Asleep Adults
Gennady P. Chuiko, Yevhen S. Darnapuk, Olga V. Dvornik et al. SSRN Electronic Journal, 2022. Cites: paper

Correlated diseases
Anirban Dutta Choudhury, Rohan Banerjee, Sanjay Kimbahune et al. Elsevier eBooks, 2022. Cites: paper

Recent Advancement in Sleep Technologies: A Literature Review on Clinical Standards, Sensors, Apps, and AI Methods
Gozde Cay, Vignesh Ravichandran, Shehjar Sadhu et al. IEEE Access, 2022. Cites: paper

Automatic detection of respiratory events during sleep from Polysomnography data using Layered Hidden Markov Model
Azadeh Sadoughi, Mohammad Bagher Shamsollahi, Emad Fatemizadeh. Physiological Measurement, 2021. Cites: paper

Development of a method for differential analysis of data on the arterial blood oxygenation in healthy adults
Gennady P. Chuiko, Yevhen S. Darnapuk. Eastern-European Journal of Enterprise Technologies, 2021. Cites: paper

Design and Implementation of Automatic Sleep Staging based on ECG Signals
Weilun Yu, Dazhi Jiang, Wenxin Zeng et al. International Conference on Computational Intelligence and Security (CIS), 2021. Cites: paper

EEG Signal Multichannel Frequency-Domain Ratio Indices for Drowsiness Detection Based on Multicriteria Optimization
Igor Stančin, Nikolina Frid, Mario Cifrek et al. Sensors, 2021. Cites: paper

A Review of Methods for Sleep Arousal Detection Using Polysomnographic Signals
Xiangyu Qian, Ye Qiu, Qingzu He et al. Brain Sciences, 2021. Cites: paper

Automatic Sleep-Arousal Detection with Single-Lead EEG Using Stacking Ensemble Learning
Ying‐Ren Chien, Cheng-Hsuan Wu, Hen‐Wai Tsao. Sensors, 2021. Cites: paper

Sleep Arousal Detection Using One Dimensional Local Binary Pattern-Based Convolutional Neural Network
Hasan Zan, Abdulnasır Yildiz. International Conference on Innovations in Intelligent Systems and Applications (INISTA), 2021. Cites: paper

“Devil’s stairs”, Poisson’s Statistics, and Patient Sorting via Variabilities for Oxygenation: All from Arterial Blood Gas Data
Gennady P. Chuiko, Yevhen S. Darnapuk, Olga V. Dvornik et al. bioRxiv (Cold Spring Harbor Laboratory), 2021. Cites: paper

Sleep Apnea Detection Using ResNet
Aditya Shanmugham, Bhamidipati V S Ananda Srivatsa, K Gopikrishnan et al. International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2021. Cites: paper

Assessment of Cardiorespiratory Interactions during Apneic Events in Sleep via Fuzzy Kernel Measures of Information Dynamics
Ivan Lazić, Riccardo Pernice, Tatjana Lončar-Turukalo et al. Entropy, 2021. Cites: paper

Boosting automated sleep staging performance in big datasets using population subgrouping
Samaneh Nasiri, Gari D. Clifford. SLEEP, 2021. Cites: paper

Artifact Detection and Correction in EEG data: A Review
Sari Saba-Sadiya, Tuka Alhanai, Mohammad M. Ghassemi. International IEEE/EMBS Conference on Neural Engineering, 2021. Cites: paper

U-Sleep: resilient high-frequency sleep staging
Mathias Perslev, Sune Darkner, Lykke Kempfner et al. npj Digital Medicine, 2021. Cites: paper

Reproducibility in machine learning for health research: Still a ways to go
Matthew B. A. McDermott, Shirly Wang, Nikki Marinsek et al. Science Translational Medicine, 2021. Cites: paper

Transfer learning from ECG to PPG for improved sleep staging from wrist-worn wearables
Qiao Li, Qichen Li, Ayse Selin Cakmak et al. Physiological Measurement, 2021. Cites: paper

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