An adaptive iterative refinement model usingmulti-scale soft-braid for ECG arrhythmia recognition

An adaptive iterative refinement model usingmulti-scale soft-braid for ECG arrhythmia recognition | 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 An adaptive iterative refinement model usingmulti-scale soft-braid for ECG arrhythmia recognition Jibin Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9274833/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Cardiac arrhythmias represent a major global health challenge, accounting formore than 32% of deaths worldwide. Premature atrial contraction, prematureventricular contraction and atrial fibrillation are clinically significant types, theyare usually asymptomatic and can increase the risk of various complications suchas stroke and heart failure. The existing approaches still effectively struggle tocapture multi-scale spatio-temporal relationships in electrocardiograms (ECGs).To address this issue, this research put forward a multi-scale soft-braid iterativerefiner (MSIRefiner), which integrates multi-scale soft-braid topology to modelinteractions among ECG leads and waveform episodes across different temporalresolutions. This model includes four critical components:multi-scale soft-braid topology for capturing spatio-temporal relationships, topology-aware efficientattention to alleviate computational cost, iterative refinement of both topologyand diagnostic recognitions and an adaptive stopping mechanism to balance accuracy and efficiency. Experiments across the two public databases demonstratethat MSIRefiner achieves better performance than several baseline models ondiverse arrhythmias recognition, further providing improved interpretability viavisualization analysis and thus highlighting its potential for real-world clinicaldeployment in automated ECG analysis. Electrocardiogram Soft-braid topology Attention mechanism Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 12 May, 2026 Reviews received at journal 29 Apr, 2026 Reviews received at journal 21 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviewers invited by journal 19 Apr, 2026 Editor assigned by journal 06 Apr, 2026 Submission checks completed at journal 31 Mar, 2026 First submitted to journal 31 Mar, 2026 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. 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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-9274833","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626738494,"identity":"ed807651-5c6f-49f0-b70d-195ac34fec88","order_by":0,"name":"Jibin Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYLACCYMDPAzM/A8OfqiQkOMnXgt7D+NjiTMWxpINxNlzgIGB5wyzAW9bReIGQloMjp89/MKi4I6MuUTuMQnJeRKMGxiYHz66gU/Lmbw0CwmDZzyWM/LSJAq3STCbM7AZG+fg0WJ2IMfMQMLgMI/BjQQzCcltEmyWDTxs0ni1nH+DpIV3jgQPMCgIaLmRY/wArOXMGWMD3gYJCYJa7G+8MWMA+cXgeFviY4ljEgaSzQT8ItmfY/xZ4s8de4PDzAcOfqipq+9nb374GJ8WIGCTlkDhM+NXDlby8QNhRaNgFIyCUTCSAQDUDE1JzBTAfwAAAABJRU5ErkJggg==","orcid":"","institution":"Bengbu Medical University","correspondingAuthor":true,"prefix":"","firstName":"Jibin","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2026-03-31 05:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9274833/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9274833/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107870694,"identity":"823f2e0b-f22b-4ae5-b019-5fb28114900a","added_by":"auto","created_at":"2026-04-27 07:40:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5369581,"visible":true,"origin":"","legend":"","description":"","filename":"Latex.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9274833/v1_covered_02af882e-a89b-4d3c-897b-09d2ae8915a0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An adaptive iterative refinement model usingmulti-scale soft-braid for ECG arrhythmia recognition","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"international-journal-of-machine-learning-and-cybernetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jmlc","sideBox":"Learn more about [International Journal of Machine Learning and Cybernetics](http://actavetscand.biomedcentral.com/)","snPcode":"13042","submissionUrl":"https://submission.nature.com/new-submission/13042/3","title":"International Journal of Machine Learning and Cybernetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Electrocardiogram, Soft-braid topology, Attention mechanism","lastPublishedDoi":"10.21203/rs.3.rs-9274833/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9274833/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Cardiac arrhythmias represent a major global health challenge, accounting formore than 32% of deaths worldwide. Premature atrial contraction, prematureventricular contraction and atrial fibrillation are clinically significant types, theyare usually asymptomatic and can increase the risk of various complications suchas stroke and heart failure. The existing approaches still effectively struggle tocapture multi-scale spatio-temporal relationships in electrocardiograms (ECGs).To address this issue, this research put forward a multi-scale soft-braid iterativerefiner (MSIRefiner), which integrates multi-scale soft-braid topology to modelinteractions among ECG leads and waveform episodes across different temporalresolutions. This model includes four critical components:multi-scale\nsoft-braid topology for capturing spatio-temporal relationships, topology-aware efficientattention to alleviate computational cost, iterative refinement of both topologyand diagnostic recognitions and an adaptive stopping mechanism to balance accuracy and efficiency. 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