276
Views
38
CrossRef citations to date
0
Altmetric
Original Articles

An automatic, continuous and probabilistic sleep stager based on a hidden markov model

Pages 199-207 | Published online: 30 Nov 2010

Keep up to date with the latest research on this topic with citation updates for this article.

Read on this site (1)

Natheer Khasawneh, Mohammad Abdel Kareem Jaradat, Luay Fraiwan & Mohamed Al-Fandi. (2011) ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR AUTOMATIC SLEEP MULTISTAGE LEVEL SCORING EMPLOYING EEG, EOG, AND EMG EXTRACTED FEATURES. Applied Artificial Intelligence 25:2, pages 163-179.
Read now

Articles from other publishers (37)

Kyle Q. Lepage, Sparsh Jain, Andrew Kvavilashvili, Mark Witcher & Sujith Vijayan. (2023) Unsupervised Multitaper Spectral Method for Identifying REM Sleep in Intracranial EEG Recordings Lacking EOG/EMG Data. Bioengineering 10:9, pages 1009.
Crossref
Lieke WA. Hermans, Iris AM. Huijben, Hans van Gorp, Tim RM. Leufkens, Pedro Fonseca, Sebastiaan Overeem & Merel M. van Gilst. (2022) Representations of temporal sleep dynamics: Review and synthesis of the literature. Sleep Medicine Reviews 63, pages 101611.
Crossref
Hadeel Alsolai, Shahnawaz Qureshi, Syed Muhammad Zeeshan Iqbal, Sirirut Vanichayobon, Lawrence Edward Henesey, Craig Lindley & Seppo Karrila. (2022) A Systematic Review of Literature on Automated Sleep Scoring. IEEE Access 10, pages 79419-79443.
Crossref
Ingmar Visser & Maarten SpeekenbrinkIngmar Visser & Maarten Speekenbrink. 2022. Mixture and Hidden Markov Models with R. Mixture and Hidden Markov Models with R 1 43 .
Indie C. Garwood, Sourish Chakravarty, Jacob Donoghue, Meredith Mahnke, Pegah Kahali, Shubham Chamadia, Oluwaseun Akeju, Earl K. Miller & Emery N. Brown. (2021) A hidden Markov model reliably characterizes ketamine-induced spectral dynamics in macaque local field potentials and human electroencephalograms. PLOS Computational Biology 17:8, pages e1009280.
Crossref
Xichen She, Yaya Zhai, Ricardo Henao, Christopher W. Woods, Christopher Chiu, Geoffrey S. Ginsburg, Peter X. K. Song & Alfred O. Hero. (2021) Adaptive Multi-Channel Event Segmentation and Feature Extraction for Monitoring Health Outcomes. IEEE Transactions on Biomedical Engineering 68:8, pages 2377-2388.
Crossref
Yassin Khalifa, Danilo Mandic & Ervin Sejdić. (2021) A review of Hidden Markov models and Recurrent Neural Networks for event detection and localization in biomedical signals. Information Fusion 69, pages 52-72.
Crossref
Susanne M.M. de Mooij, Tessa F. Blanken, Raoul P.P.P. Grasman, Jennifer R. Ramautar, Eus J.W. Van Someren & Han L.J. van der Maas. (2020) Dynamics of sleep: Exploring critical transitions and early warning signals. Computer Methods and Programs in Biomedicine 193, pages 105448.
Crossref
Saeid Sanei, Delaram Jarchi & Anthony G. Constantinides. 2020. Body Sensor Networking, Design and Algorithms. Body Sensor Networking, Design and Algorithms 83 105 .
Michelle L. Trevenen, Berwin A. Turlach, Peter R. Eastwood, Leon M. Straker & Kevin Murray. (2019) Using hidden Markov models with raw, triaxial wrist accelerometry data to determine sleep stages. Australian & New Zealand Journal of Statistics 61:3, pages 273-298.
Crossref
Hojat Ghimatgar, Kamran Kazemi, Mohammad Sadegh Helfroush & Ardalan Aarabi. (2019) An automatic single-channel EEG-based sleep stage scoring method based on hidden Markov Model. Journal of Neuroscience Methods 324, pages 108320.
Crossref
Shing-Tai Pan, Chih-Hung Wu, Chia-Ho Wu, Yung-Ran Lin & Shie-Jue Lee. 2019. Advances in Smart Vehicular Technology, Transportation, Communication and Applications. Advances in Smart Vehicular Technology, Transportation, Communication and Applications 284 291 .
Somayeh Raiesdana. (2018) Automated sleep staging of OSAs based on ICA preprocessing and consolidation of temporal correlations. Australasian Physical & Engineering Sciences in Medicine 41:1, pages 161-176.
Crossref
Sirinthip Roomkham, David Lovell, Joseph Cheung & Dimitri Perrin. (2018) Promises and Challenges in the Use of Consumer-Grade Devices for Sleep Monitoring. IEEE Reviews in Biomedical Engineering 11, pages 53-67.
Crossref
Julie A. Onton, Dae Y. Kang & Todd P. Coleman. (2016) Visualization of Whole-Night Sleep EEG From 2-Channel Mobile Recording Device Reveals Distinct Deep Sleep Stages with Differential Electrodermal Activity. Frontiers in Human Neuroscience 10.
Crossref
Álvaro Gómez-Losada, José Carlos M. Pires & Rafael Pino-Mejías. (2015) Time series clustering for estimating particulate matter contributions and its use in quantifying impacts from deserts. Atmospheric Environment 117, pages 271-281.
Crossref
Bin Xia, Qianyun Li, Jie Jia, Jingyi Wang, Ujwal Chaudhary, Ander Ramos-Murguialday & Niels Birbaumer. (2015) Electrooculogram based sleep stage classification using deep belief network. Electrooculogram based sleep stage classification using deep belief network.
Tarek Lajnef, Sahbi Chaibi, Perrine Ruby, Pierre-Emmanuel Aguera, Jean-Baptiste Eichenlaub, Mounir Samet, Abdennaceur Kachouri & Karim Jerbi. (2015) Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines. Journal of Neuroscience Methods 250, pages 94-105.
Crossref
Wasifa Jamal, Saptarshi Das, Ioana-Anastasia Oprescu & Koushik Maharatna. (2015) Prediction of Synchrostate Transitions in EEG Signals Using Markov Chain Models. IEEE Signal Processing Letters 22:2, pages 149-152.
Crossref
Yanjun Zhang, Xiangmin Zhang, Wenhui Liu, Yuxi Luo, Enjia Yu, Keju Zou & Xiaoliang Liu. (2014) Automatic Sleep Staging using Multi-dimensional Feature Extraction and Multi-kernel Fuzzy Support Vector Machine. Journal of Healthcare Engineering 5:4, pages 505-520.
Crossref
Sheng-Fu Liang, Ching-Fa Chen, Jian-Hong Zeng & Shing-Tai Pan. (2014) Application of Genetic Algorithm and Fuzzy Vector Quantization on EEG-based automatic sleep staging by using Hidden Markov Model. Application of Genetic Algorithm and Fuzzy Vector Quantization on EEG-based automatic sleep staging by using Hidden Markov Model.
Shayan Motamedi-Fakhr, Mohamed Moshrefi-Torbati, Martyn Hill, Catherine M. Hill & Paul R. White. (2014) Signal processing techniques applied to human sleep EEG signals—A review. Biomedical Signal Processing and Control 10, pages 21-33.
Crossref
Sheng-Fu Liang, Ching-Fa Chen, Jian-Hong Zeng & Shing-Tai Pan. 2014. Proceedings of the 2nd International Conference on Intelligent Technologies and Engineering Systems (ICITES2013). Proceedings of the 2nd International Conference on Intelligent Technologies and Engineering Systems (ICITES2013) 891 898 .
Sana Tmar-Ben Hamida & Beena Ahmed. (2013) Computer based sleep staging: Challenges for the future. Computer based sleep staging: Challenges for the future.
Shing-Tai Pan, Chih-En Kuo, Jian-Hong Zeng & Sheng-Fu Liang. (2012) A transition-constrained discrete hidden Markov model for automatic sleep staging. BioMedical Engineering OnLine 11:1.
Crossref
Ingmar Visser. (2011) Seven things to remember about hidden Markov models: A tutorial on Markovian models for time series. Journal of Mathematical Psychology 55:6, pages 403-415.
Crossref
Wen Zhao, Jingzhi Yan, Bin Hu, Haoyu Ma & Li Liu. (2010) Advanced measure selection in automatic NREM discrimination based on EEG. Advanced measure selection in automatic NREM discrimination based on EEG.
A. G. Ravelo-García, F.D. Lorenzo-García & J.L. Navarro-Mesa. 2009. Proceedings of the European Computing Conference. Proceedings of the European Computing Conference 133 141 .
Peter Anderer, Georg Gruber, Silvia Parapatics & Georg Dorffner. (2007) Automatic sleep classification according to Rechtschaffen and Kales. Automatic sleep classification according to Rechtschaffen and Kales.
Peter Anderer, Georg Gruber, Silvia Parapatics, Michael Woertz, Tatiana Miazhynskaia, Gerhard Klösch, Bernd Saletu, Josef Zeitlhofer, Manuel J. Barbanoj, Heidi Danker-Hopfe, Sari-Leena Himanen, Bob Kemp, Thomas Penzel, Michael Grözinger, Dieter Kunz, Peter Rappelsberger, Alois Schlögl & Georg Dorffner. (2005) An E-Health Solution for Automatic Sleep Classification according to Rechtschaffen and Kales: Validation Study of the Somnolyzer 24 × 7 Utilizing the Siesta Database. Neuropsychobiology 51:3, pages 115-133.
Crossref
Arthur Flexer, Georg Gruber & Georg Dorffner. (2005) A reliable probabilistic sleep stager based on a single EEG signal. Artificial Intelligence in Medicine 33:3, pages 199-207.
Crossref
Iead Rezek & Stephen Roberts. 2005. Probabilistic Modeling in Bioinformatics and Medical Informatics. Probabilistic Modeling in Bioinformatics and Medical Informatics 419 450 .
D. Novak, D. Cuesta-Frau, T. Al ani, M. Aboy, R. Mico & L. Lhotska. (2004) Speech recognition methods applied to biomedical signals processing. Speech recognition methods applied to biomedical signals processing.
Karl Pauwels, Temujin Gautama, Danilo P. Mandic & Marc M. Hulle. 2004. Applications and Science in Soft Computing. Applications and Science in Soft Computing 213 218 .
Matthias Schwaibold, Reinhard Harms, Bernd Scholler, Iris Pinnow, Werner Cassel, Thomas Penzel, Heinrich F. Becker & Armin Bolz. (2003) Knowledge-Based Automatic Sleep-Stage Recognition - Reduction in the Interpretation Variability. Wissensbasierte automatische Schlafstadienanalyse - Reduktion der Auswertevariabilitat. Somnologie 7:2, pages 59-65.
Crossref
A. Flexer, G. Gruber & G. Dorffner. (2002) Improvements on continuous unsupervised sleep staging. Improvements on continuous unsupervised sleep staging.
Arthur Flexer, Georg Gruber & Georg Dorffner. 2002. Artificial Neural Networks — ICANN 2002. Artificial Neural Networks — ICANN 2002 1013 1018 .

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.