{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T21:22:56Z","timestamp":1778534576604,"version":"3.51.4"},"reference-count":53,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,11,21]],"date-time":"2020-11-21T00:00:00Z","timestamp":1605916800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61962034, 61941109"],"award-info":[{"award-number":["61962034, 61941109"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Opening Fundation of Key Laboratory of Opto-technology and Intelligent Control (Lanzhou Jiaotong University), Ministry of Education","award":["KFKT2020-13"],"award-info":[{"award-number":["KFKT2020-13"]}]},{"name":"Tianyou Youth Talent Lift Program of Lanzhou Jiaotong Univesity","award":["01"],"award-info":[{"award-number":["01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Sleep staging has attracted significant attention as a critical step in auxiliary diagnosis of sleep disease. To avoid subjectivity of doctor\u2019s manual sleep staging, and to realize scientific management of massive physiological data, an ontology-based decision support tool is proposed. The tool implements an automated procedure for sleep staging using dual-channel electroencephalogram (EEG) signals. First of all, it encodes EEG features, sleep-related concepts and other contextual information to \u201cEEG-Sleep ontology\u201d. Secondly, a rule-set is constructed based on a data mining technique. Finally, the first two steps are processed in a reasoning engine which is automatically assign each 30 s epoch (segment) sleep stage to one of five possible sleep stages: WA, NREM1, NREM2, SWS and REM. The rule set is obtained using EEG data taken from the Sleep-EDF database [EXPANDED] according to the random forest algorithm (RF), we prove that the performance of the proposed method with 89.12% accuracy, and 0.81 Kappa statistics is superior to other algorithms such as Bayesian network, C4.5, support vector machine, and multilayer perceptron. Additionally, our proposed approach improved performance when compared to other studies using a small subset of the Sleep-EDF database [EXPANDED].<\/jats:p>","DOI":"10.3390\/sym12111921","type":"journal-article","created":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T11:50:34Z","timestamp":1606132234000},"page":"1921","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Ontology-Based Decision Support Tool for Automatic Sleep Staging Using Dual-Channel EEG Data"],"prefix":"10.3390","volume":"12","author":[{"given":"Bingtao","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China"},{"name":"Key Laboratory of Opto-Technology and Intelligent Control, Ministry of Education, Lanzhou Jiaotong University, Lanzhou 730070, China"},{"name":"School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhifei","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hanshu","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Lian","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenwen","family":"Chang","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhonglin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,21]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"A manual of standardized terminology, techniques and scoring systems for sleep stages of human subjects","volume":"50","author":"Rechtschaffen","year":"1968","journal-title":"Health Inst."},{"key":"ref_2","unstructured":"Iber, C., Ancoli-Israel, S., Chesson, A., and Quan, S.F. (2007). The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications, American Academy of Sleep Medicine."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.compbiomed.2011.04.001","article-title":"Self-evaluated automatic classifier as a decision-support tool for sleep\/wake staging","volume":"41","author":"Charbonnier","year":"2011","journal-title":"Comput. Biol. Med."},{"key":"ref_4","first-page":"1279","article-title":"Insights from studying human sleep disorders","volume":"437","author":"Mahowald","year":"2005","journal-title":"Nat. Cell Biol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1053\/smrv.2002.0186","article-title":"Epidemiology of insomnia: What we know and what we still need to learn","volume":"6","author":"Ohayon","year":"2002","journal-title":"Sleep Med. Rev."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.specom.2017.04.001","article-title":"Investigation of different speech types and emotions for detecting depression using different classifiers","volume":"90","author":"Jiang","year":"2017","journal-title":"Speech Commun."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.cmpb.2016.08.010","article-title":"EEG-based mild depressive detection using feature selection methods and classifiers","volume":"136","author":"Li","year":"2016","journal-title":"Comput. Methods Progr. Biomed."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/B0-72-160797-7\/50009-4","article-title":"Normal human sleep: An overview","volume":"12","author":"Carskadon","year":"2005","journal-title":"Princ. Pract. Sleep Med."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/sleep\/23.7.1e","article-title":"Interobserver Agreement Among Sleep Scorers from Different Centers in a Large Dataset","volume":"23","author":"Norman","year":"2000","journal-title":"Sleep"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1159\/000085205","article-title":"An E-Health Solution for Automatic Sleep Classification according to Rechtschaffen and Kales: Validation Study of the Somnolyzer 24 \u00d7 7 Utilizing the Siesta Database","volume":"51","author":"Anderer","year":"2005","journal-title":"Neuropsychobiology"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1093\/sleep\/30.11.1587","article-title":"Automatic Analysis of Single-Channel Sleep EEG: Validation in Healthy Individuals","volume":"30","author":"Berthomier","year":"2007","journal-title":"Sleep"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zhang, X., Hu, B., Moore, P., Chen, J., and Zhou, L. (2011, January 13\u201317). Emotiono: An Ontology with Rule-Based Reasoning for Emotion Recognition. Proceedings of the 18th International Conference on Neural Information Processing, Shanghai, China.","DOI":"10.1007\/978-3-642-24958-7_11"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1007\/s11280-012-0181-5","article-title":"Ontology-based context modeling for emotion recognition in an intelligent web","volume":"16","author":"Zhang","year":"2013","journal-title":"World Wide Web"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1016\/j.cmpb.2013.12.023","article-title":"Ontology driven decision support for the diagnosis of mild cognitive impairment","volume":"113","author":"Zhang","year":"2014","journal-title":"Comput. Methods Progr. Biomed."},{"key":"ref_15","first-page":"13","article-title":"An automatic sleep-stage classifier using electroencephalographic signals","volume":"1","author":"Correa","year":"2008","journal-title":"Int. J. Med. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.neucom.2012.11.003","article-title":"Automatic sleep stage recurrent neural classifier using energy features of EEG signals","volume":"104","author":"Hsu","year":"2013","journal-title":"Neurocomputing"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1007\/s10916-009-9286-5","article-title":"Estimation of Sleep Stages by an Artificial Neural Network Employing EEG, EMG and EOG","volume":"34","author":"Tagluk","year":"2010","journal-title":"J. Med. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1186\/1475-925X-11-52","article-title":"A transition-constrained discrete hidden Markov model for automatic sleep staging","volume":"11","author":"Pan","year":"2012","journal-title":"Biomed. Eng. Online"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/scj.10248","article-title":"Automatic sleep stage scoring based on waveform recognition method and decision-tree learning","volume":"33","author":"Hanaoka","year":"2002","journal-title":"Syst. Comput. Jpn."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1813","DOI":"10.1109\/JBHI.2014.2303991","article-title":"Analysis and Classification of Sleep Stages Based on Difference Visibility Graphs from a Single-Channel EEG Signal","volume":"18","author":"Zhu","year":"2014","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1109\/10.24251","article-title":"Sleep staging automaton based on the theory of evidence","volume":"36","author":"Principe","year":"1989","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1016\/j.neucom.2004.01.178","article-title":"Sleep stage classification using fuzzy sets and machine learning techniques","volume":"58","author":"Pinero","year":"2004","journal-title":"Neurocomputing"},{"key":"ref_23","first-page":"1","article-title":"EEG-based automatic sleep staging usingontology and weighting feature analysis","volume":"6534041","author":"Bingtao","year":"2018","journal-title":"Comput. Math. Methods Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1649","DOI":"10.1109\/TIM.2012.2187242","article-title":"Automatic Stage Scoring of Single-Channel Sleep EEG by Using Multiscale Entropy and Autoregressive Models","volume":"61","author":"Liang","year":"2012","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.artmed.2011.06.004","article-title":"Automatic sleep scoring: A search for an optimal combination of measures","volume":"53","year":"2011","journal-title":"Artif. Intell. Med."},{"key":"ref_26","first-page":"696","article-title":"Modeling and detection of ontology-based Byzantine attacks","volume":"28","author":"Feng","year":"2011","journal-title":"J. Univ. Chin. Acad. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"817","DOI":"10.1016\/j.compbiomed.2005.04.010","article-title":"HL7 ontology and mobile agents for interoperability in heterogeneous medical information systems","volume":"36","author":"Orgun","year":"2006","journal-title":"Comput. Biol. Med."},{"key":"ref_28","first-page":"1","article-title":"Reengineering thesauri for new applications: The AGROVOC Example","volume":"4","author":"Soergel","year":"2004","journal-title":"J. Digit. Inf."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1146\/annurev.bioeng.5.040202.121601","article-title":"Advances in Quantitative Electroencephalogram Analysis Methods","volume":"6","author":"Thakor","year":"2004","journal-title":"Annu. Rev. Biomed. Eng."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1007\/11837787_9","article-title":"Ontological and Practical Issues in Using a Description Logic to Represent Medical Concept Systems: Experience from GALEN","volume":"4126","author":"Rector","year":"2006","journal-title":"Reason. Web"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.cmpb.2007.06.005","article-title":"KnowBaSICS-M: An ontology-based system for semantic management of medical problems and computerised algorithmic solutions","volume":"88","author":"Bratsas","year":"2007","journal-title":"Comput. Methods Progr. Biomed."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.cmpb.2011.06.006","article-title":"Ontology-driven execution of clinical guidelines","volume":"107","author":"Isern","year":"2012","journal-title":"Comput. Methods Progr. Biomed."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1007\/11527770_31","article-title":"Ontology-Mediated Distributed Decision Support for Breast Cancer","volume":"3581","author":"Dasmahapatra","year":"2005","journal-title":"Artif. Intell. Med."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Su, Y., Hu, B., Xu, L., Cai, H., Moore, P., Zhang, X., and Chen, J. (2014, January 2\u20135). EmotionO+: Physiological signals knowledge representation and emotion reasoning model for mental health monitoring. Proceedings of the 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Belfast, UK.","DOI":"10.1109\/BIBM.2014.6999215"},{"key":"ref_35","unstructured":"(2020, November 20). The Sleep-EDF Database [Expanded]. Available online: http:\/\/physionet.org\/pn4\/sleep-edfx\/#sleep-recordings-and-hypnograms-in-european-data-f."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1185","DOI":"10.1109\/10.867928","article-title":"Analysis of a sleep-dependent neuronal feedback loop: The slow-wave microcontinuity of the EEG","volume":"47","author":"Kemp","year":"2000","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"e215","DOI":"10.1161\/01.CIR.101.23.e215","article-title":"PhysioBank, PhysioToolkit, and PhysioNet","volume":"101","author":"Goldberger","year":"2000","journal-title":"Circulation"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1093\/sleep\/13.3.279","article-title":"Alternative electrode placement in (automatic) sleep scoring (Fpz-Cz\/Pz-Oz versus C4-A1\/C3-A2)","volume":"13","author":"Sweden","year":"1990","journal-title":"Sleep"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/0924-980X(96)00316-5","article-title":"Evaluation of Hjorth parameters in forearm surface EMG analysis during an occupational repetitive task","volume":"101","author":"Horwat","year":"1996","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.bspc.2007.05.005","article-title":"Feature selection for sleep\/wake stages classification using data driven methods","volume":"2","author":"Zoubek","year":"2007","journal-title":"Biomed. Signal Process."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1340","DOI":"10.1016\/j.engappai.2011.02.002","article-title":"An ontology-based fuzzy decision support system for multiple sclerosis","volume":"24","author":"Esposito","year":"2011","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1006\/ijhc.1995.1068","article-title":"Top-level ontological categories","volume":"43","author":"Sowa","year":"1995","journal-title":"Int. J. Hum. Comput. Stud."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.1093\/bioinformatics\/bti171","article-title":"Optimal number of features as a function of sample size for various classification rules","volume":"21","author":"Hua","year":"2005","journal-title":"Bioinformatics"},{"key":"ref_45","unstructured":"Garner, S. (1995, January 18\u201321). WEKA: The Waikato environment for knowledge analysis. Proceedings of the New Zealand Computer Science Research Students Conference, Hamilton, New Zealand."},{"key":"ref_46","unstructured":"Jena, A.P.I. (2020, November 20). Available online: http:\/\/jena.apache.org\/."},{"key":"ref_47","first-page":"336","article-title":"An Introduction to Bayesian Network","volume":"39","author":"Jensen","year":"1966","journal-title":"Technometrics"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2017\/9878369","article-title":"A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering","volume":"2017","author":"Li","year":"2017","journal-title":"Complexity"},{"key":"ref_49","first-page":"71","article-title":"Neural Networks: A Comprehensive Foundation","volume":"31","author":"Haykin","year":"1995","journal-title":"Inf. Process. Manag."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1765","DOI":"10.1109\/TCBB.2016.2602263","article-title":"Feature Selection for Optimized High-Dimensional Biomedical Data Using an Improved Shuffled Frog Leaping Algorithm","volume":"15","author":"Hu","year":"2016","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.cmpb.2011.11.005","article-title":"Automated sleep stage identification system based on time\u2013frequency analysis of a single EEG channel and random forest classifier","volume":"108","author":"Fraiwan","year":"2012","journal-title":"Comput. Methods Progr. Biomed."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1053\/smrv.1999.0086","article-title":"Limitations of Rechtschaffen and Kales","volume":"4","author":"Himanen","year":"2000","journal-title":"Sleep Med. Rev."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.ijpsycho.2005.05.004","article-title":"Power and coherent oscillations distinguish REM sleep, stage 1 and wakefulness","volume":"60","author":"Guevara","year":"2006","journal-title":"Int. J. Psychophysiol."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/12\/11\/1921\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:35:26Z","timestamp":1760178926000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/12\/11\/1921"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,21]]},"references-count":53,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2020,11]]}},"alternative-id":["sym12111921"],"URL":"https:\/\/doi.org\/10.3390\/sym12111921","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,21]]}}}