Time series data-based classification using combined 1D- CNN-GRU for Seizure detection and prediction

Time series data-based classification using combined 1D- CNN-GRU for Seizure detection and prediction | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Time series data-based classification using combined 1D- CNN-GRU for Seizure detection and prediction CHEKHMANE GHEZALA, Benali Radhwane This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5156295/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Epilepsy is a malfunction of nervous system that it changes the quality of human’s life, and it is caused by many factors. Therefore, the diagnosis of this disease needs the acquisition of the electrical activity of brain which called electroencephalography (EEG) technique. Thus, EEG signals (EEGs) recorded are widely used for epileptic seizure detection and prediction. However, to investigate these process, convolutional neural network (CNN) and deep recurrent network (DRN) are developed to automate the classification of EEGs. In the presented article, a proposed model combined both one-dimensional CNN (1D- CNN) and Gate Recurrent Unit (GRU) is established for EEGs analysis. Furthermore, the performance of this framework is evaluated by using the publicly available CHB-MIT dataset, and the classification between these conditions is examined. Moreover, the obtained results show higher accuracies of the proposed 1D-CNN-GRU and outperforms significantly previous works. Finally, this architecture is accurate and proves their efficacity in the task of epileptic seizure detection and prediction. CHB-MIT Convolutional Neural Network Classification Deep Recurrent Network EEG Signals Epileptic Seizure Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5156295","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":359217971,"identity":"5b373fcd-cc8c-4120-8f24-21d5c67bfd3b","order_by":0,"name":"CHEKHMANE GHEZALA","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0004-4313-2932","institution":"University of Tlemcen","correspondingAuthor":true,"prefix":"","firstName":"CHEKHMANE","middleName":"","lastName":"GHEZALA","suffix":""},{"id":359221961,"identity":"487d48a6-186e-418b-836d-ef93b0e3f057","order_by":1,"name":"Benali Radhwane","email":"","orcid":"https://orcid.org/0000-0002-5648-1718","institution":"University of Tlemcen","correspondingAuthor":false,"prefix":"","firstName":"Benali","middleName":"","lastName":"Radhwane","suffix":""}],"badges":[],"createdAt":"2024-09-26 06:53:45","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5156295/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5156295/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65411793,"identity":"fcaf25b0-6bf1-4655-9ded-9cb32cf20d99","added_by":"auto","created_at":"2024-09-27 06:09:30","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":258980,"visible":true,"origin":"","legend":"","description":"","filename":"researchsquare.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5156295/v1_covered_0812a6f9-4d79-4ae3-9c65-5b26f509b08e.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eTime series data-based classification using combined 1D- CNN-GRU for Seizure detection and prediction\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"CHB-MIT, Convolutional Neural Network, Classification, Deep Recurrent Network, EEG Signals, Epileptic Seizure","lastPublishedDoi":"10.21203/rs.3.rs-5156295/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5156295/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEpilepsy is a malfunction of nervous system that it changes the quality of human\u0026rsquo;s life, and it is caused by many factors. 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