ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2111.08446
  4. Cited By
Automatic Sleep Staging of EEG Signals: Recent Development, Challenges,
  and Future Directions
v1v2v3 (latest)

Automatic Sleep Staging of EEG Signals: Recent Development, Challenges, and Future Directions

Physiological Measurement (Physiol. Meas.), 2021
3 November 2021
Huy P Phan
Kaare B. Mikkelsen
ArXiv (abs)PDFHTML

Papers citing "Automatic Sleep Staging of EEG Signals: Recent Development, Challenges, and Future Directions"

21 / 21 papers shown
Estimating the Event-Related Potential from Few EEG Trials
Estimating the Event-Related Potential from Few EEG Trials
Anders Vestergaard Nørskov
Kasper Jørgensen
Alexander Neergaard Zahid
Morten Mørup
100
0
0
28 Nov 2025
NAP: Attention-Based Late Fusion for Automatic Sleep Staging
NAP: Attention-Based Late Fusion for Automatic Sleep Staging
Alvise Dei Rossi
J. van der Meer
Markus H. Schmidt
C. Bassetti
Luigi Fiorillo
F. Faraci
MLAU
257
1
0
05 Nov 2025
A Systematic Evaluation of Self-Supervised Learning for Label-Efficient Sleep Staging with Wearable EEG
A Systematic Evaluation of Self-Supervised Learning for Label-Efficient Sleep Staging with Wearable EEG
Emilio Estevan
María Sierra-Torralba
Eduardo López-Larraz
Luis Montesano
164
0
0
09 Oct 2025
SPICED: A Synaptic Homeostasis-Inspired Framework for Unsupervised Continual EEG Decoding
SPICED: A Synaptic Homeostasis-Inspired Framework for Unsupervised Continual EEG Decoding
Yangxuan Zhou
Sha Zhao
Jiquan Wang
Haiteng Jiang
Shijian Li
Tao Li
Gang Pan
126
0
0
22 Sep 2025
EEG Artifact Detection and Correction with Deep Autoencoders
EEG Artifact Detection and Correction with Deep Autoencoders
David Aquilué-Llorens
Aureli Soria-Frisch
242
1
0
12 Feb 2025
MSA-CNN: A Lightweight Multi-Scale CNN with Attention for Sleep Stage Classification
S. Goerttler
Yucheng Wang
Emadeldeen Eldele
Min Wu
F. He
188
4
0
06 Jan 2025
wav2sleep: A Unified Multi-Modal Approach to Sleep Stage Classification
  from Physiological Signals
wav2sleep: A Unified Multi-Modal Approach to Sleep Stage Classification from Physiological Signals
Jonathan Carter
Lionel Tarassenko
MLAU
288
3
0
07 Nov 2024
Evaluating the Influence of Temporal Context on Automatic Mouse Sleep
  Staging through the Application of Human Models
Evaluating the Influence of Temporal Context on Automatic Mouse Sleep Staging through the Application of Human Models
Javier García Ciudad
Morten Mørup
B. R. Kornum
Alexander Neergaard Zahid
159
0
0
06 Jun 2024
Permutation time irreversibility in sleep electroencephalograms:
  Dependence on sleep stage and the effect of equal values
Permutation time irreversibility in sleep electroencephalograms: Dependence on sleep stage and the effect of equal valuesPhysical Review E (Phys. Rev. E), 2024
Wenpo Yao
133
3
0
05 May 2024
Data-Efficient Sleep Staging with Synthetic Time Series Pretraining
Data-Efficient Sleep Staging with Synthetic Time Series Pretraining
Niklas Grieger
S. Mehrkanoon
Stephan Bialonski
213
0
0
13 Mar 2024
A novel dual-stream time-frequency contrastive pretext tasks framework
  for sleep stage classification
A novel dual-stream time-frequency contrastive pretext tasks framework for sleep stage classificationIEEE International Joint Conference on Neural Network (IJCNN), 2023
Sergio Kazatzidis
S. Mehrkanoon
AI4TS
274
2
0
15 Dec 2023
SleepEGAN: A GAN-enhanced Ensemble Deep Learning Model for Imbalanced
  Classification of Sleep Stages
SleepEGAN: A GAN-enhanced Ensemble Deep Learning Model for Imbalanced Classification of Sleep StagesBiomedical Signal Processing and Control (BSPC), 2023
Xuewei Cheng
Kevin Huang
Yishan Zou
Shujie Ma
GANAI4TS
189
17
0
04 Jul 2023
Deep Learning-Enabled Sleep Staging From Vital Signs and Activity
  Measured Using a Near-Infrared Video Camera
Deep Learning-Enabled Sleep Staging From Vital Signs and Activity Measured Using a Near-Infrared Video Camera
Jonathan Carter
João Jorge
B. Venugopal
O. Gibson
Lionel Tarassenko
171
7
0
06 Jun 2023
BIOT: Cross-data Biosignal Learning in the Wild
BIOT: Cross-data Biosignal Learning in the Wild
Chaoqi Yang
M. P. M. Brandon Westover
Jimeng Sun
193
19
0
10 May 2023
L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep
  Staging
L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep StagingIEEE journal of biomedical and health informatics (IEEE JBHI), 2023
Huy P Phan
Kristian P. Lorenzen
E. Heremans
Oliver Y. Chén
Minh C. Tran
P. Koch
Alfred Mertins
M. Baumert
Kaare B. Mikkelsen
Marina De Vos
231
61
0
09 Jan 2023
Modeling Multivariate Biosignals With Graph Neural Networks and
  Structured State Space Models
Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space ModelsACM Conference on Health, Inference, and Learning (ACM CHIL), 2022
Siyi Tang
Jared A. Dunnmon
Liangqiong Qu
Khaled Kamal Saab
T. Baykaner
Christopher Lee-Messer
D. Rubin
313
38
0
21 Nov 2022
Automatic Sleep Scoring from Large-scale Multi-channel Pediatric EEG
Automatic Sleep Scoring from Large-scale Multi-channel Pediatric EEG
Harlin Lee
Aaqib Saeed
148
3
0
30 Jun 2022
SleepPPG-Net: a deep learning algorithm for robust sleep staging from
  continuous photoplethysmography
SleepPPG-Net: a deep learning algorithm for robust sleep staging from continuous photoplethysmographyIEEE journal of biomedical and health informatics (IEEE JBHI), 2022
Kevin Kotzen
Peter H. Charlton
Sharon Salabi
Lea Amar
A. Landesberg
Joachim A. Behar
202
48
0
11 Feb 2022
Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and
  Automated sleep staging
Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep stagingIEEE transactions on neural systems and rehabilitation engineering (TNSRE), 2019
Antoine Guillot
F. Sauvet
E. During
Valentin Thorey
534
125
0
31 Oct 2019
U-Time: A Fully Convolutional Network for Time Series Segmentation
  Applied to Sleep Staging
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep StagingNeural Information Processing Systems (NeurIPS), 2019
Mathias Perslev
M. Jensen
Kenny Erleben
P. Jennum
Christian Igel
AI4TS
290
294
0
24 Oct 2019
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
2.5K
19,805
0
16 Feb 2016
1