Multiscale Analysis of Heart Sound Signals in the Wavelet Domain for Heart Murmur Detection

preprint OA: closed CC-BY-4.0
📄 Open PDF Full text JSON View at publisher

Abstract

Abstract A heart murmur is an atypical sound produced by the flow of blood through the heart. It can be a sign of a serious heart condition, so detecting heart murmurs is critical for identifying and managing cardiovascular diseases. However, current methods for identifying murmurous heart sounds do not fully utilize the valuable insights that can be gained by exploring different properties of heart sound signals. To address this issue, this study proposes a new discriminatory set of multiscale features based on the scaling and complexity properties of heart sounds, as characterized in the wavelet domain. Scaling properties are characterized by examining fractal behaviors, while complexity is explored by calculating wavelet entropy. We evaluated the diagnostic performance of these proposed features for detecting murmurs using a set of classifiers. When applied to a publicly available heart sound dataset, our proposed wavelet-based multiscale features achieved comparable performance to existing methods with fewer features. This suggests that scaling nature and complexity properties in heart sounds could be potential biomarkers for improving the accuracy of murmur detection.
Full text 13,115 characters · extracted from preprint-html · click to expand
Multiscale Analysis of Heart Sound Signals in the Wavelet Domain for Heart Murmur Detection | 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 Article Multiscale Analysis of Heart Sound Signals in the Wavelet Domain for Heart Murmur Detection Dixon Vimalajeewa, BRANI Vidakovic, Chihoon Lee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4731170/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Mar, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract A heart murmur is an atypical sound produced by the flow of blood through the heart. It can be a sign of a serious heart condition, so detecting heart murmurs is critical for identifying and managing cardiovascular diseases. However, current methods for identifying murmurous heart sounds do not fully utilize the valuable insights that can be gained by exploring different properties of heart sound signals. To address this issue, this study proposes a new discriminatory set of multiscale features based on the scaling and complexity properties of heart sounds, as characterized in the wavelet domain. Scaling properties are characterized by examining fractal behaviors, while complexity is explored by calculating wavelet entropy. We evaluated the diagnostic performance of these proposed features for detecting murmurs using a set of classifiers. When applied to a publicly available heart sound dataset, our proposed wavelet-based multiscale features achieved comparable performance to existing methods with fewer features. This suggests that scaling nature and complexity properties in heart sounds could be potential biomarkers for improving the accuracy of murmur detection. Health sciences/Cardiology Health sciences/Diseases Physical sciences/Mathematics and computing Scaling nature wavelet transform fractality classification cardiovascular diseases heart murmurs phonocardiogram analysis. Full Text Additional Declarations No competing interests reported. Supplementary Files Supplementary.pdf Cite Share Download PDF Status: Published Journal Publication published 25 Mar, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 01 Oct, 2024 Reviews received at journal 27 Sep, 2024 Reviewers agreed at journal 04 Sep, 2024 Reviews received at journal 17 Aug, 2024 Reviewers agreed at journal 09 Aug, 2024 Reviewers invited by journal 07 Aug, 2024 Editor assigned by journal 07 Aug, 2024 Editor invited by journal 27 Jul, 2024 Submission checks completed at journal 24 Jul, 2024 First submitted to journal 12 Jul, 2024 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-4731170","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":341423866,"identity":"a4615df6-6083-4188-910f-15e874afd97c","order_by":0,"name":"Dixon Vimalajeewa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYBACAwbGBgaGAgZmMO9DBQMDH5CWIKzFAKKFccYZBgY2wloQJAMzbxsRWswlkls3/DCwY+dn7zH8wDvvcB4bA/PB2zx4tFjOSGy72WOQzCzZc8ZYQnLb4WI2BrZka3xaDM4cbLvBY8DMbHAjd4OE4bbDiW0MPGbShLTc/GNQz2x//+3mH4lzQFr4v+HXcryx7TaPwWFmAwnebRIHG8C2sBHWImNwnFniTP43y4Zj6YltzGzGlnPwaTnM/uzmm4rqZP72Y8m3/9RYJ/azNz+88QaPFhhIRjCZiVAOAnZEqhsFo2AUjIKRCAAN/UwmdYz6VwAAAABJRU5ErkJggg==","orcid":"","institution":"University of Nebraska Lincoln","correspondingAuthor":true,"prefix":"","firstName":"Dixon","middleName":"","lastName":"Vimalajeewa","suffix":""},{"id":341423867,"identity":"543756dc-ac08-4641-8170-a3c4dc08ada4","order_by":1,"name":"BRANI Vidakovic","email":"","orcid":"","institution":"Texas A\u0026M University","correspondingAuthor":false,"prefix":"","firstName":"BRANI","middleName":"","lastName":"Vidakovic","suffix":""},{"id":341423868,"identity":"54fb0972-813f-4aff-a4a8-b53eae28fd94","order_by":2,"name":"Chihoon Lee","email":"","orcid":"","institution":"Texas A\u0026M University","correspondingAuthor":false,"prefix":"","firstName":"Chihoon","middleName":"","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2024-07-12 15:06:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4731170/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4731170/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-93989-0","type":"published","date":"2025-03-25T15:57:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79604968,"identity":"d81ec0f7-bc01-4d39-8395-10f3355ae4d0","added_by":"auto","created_at":"2025-03-31 16:09:44","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1029216,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4731170/v1_covered_edb954c7-8410-4cf6-af2d-47119f842c67.pdf"},{"id":62928930,"identity":"b5744b0d-0277-4a04-ad41-2068611a0307","added_by":"auto","created_at":"2024-08-21 07:26:15","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":268459,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4731170/v1/7027dbc55e4e3ecf885a6ce6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multiscale Analysis of Heart Sound Signals in the Wavelet Domain for Heart Murmur Detection","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Scaling nature, wavelet transform, fractality, classification, cardiovascular diseases, heart murmurs, phonocardiogram analysis.","lastPublishedDoi":"10.21203/rs.3.rs-4731170/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4731170/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"A heart murmur is an atypical sound produced by the flow of blood through the heart. It can be a sign of a serious heart condition, so detecting heart murmurs is critical for identifying and managing cardiovascular diseases. However, current methods for identifying murmurous heart sounds do not fully utilize the valuable insights that can be gained by exploring different properties of heart sound signals. To address this issue, this study proposes a new discriminatory set of multiscale features based on the scaling and complexity properties of heart sounds, as characterized in the wavelet domain. Scaling properties are characterized by examining fractal behaviors, while complexity is explored by calculating wavelet entropy. We evaluated the diagnostic performance of these proposed features for detecting murmurs using a set of classifiers. When applied to a publicly available heart sound dataset, our proposed wavelet-based multiscale features achieved comparable performance to existing methods with fewer features. This suggests that scaling nature and complexity properties in heart sounds could be potential biomarkers for improving the accuracy of murmur detection.","manuscriptTitle":"Multiscale Analysis of Heart Sound Signals in the Wavelet Domain for Heart Murmur Detection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-21 07:26:10","doi":"10.21203/rs.3.rs-4731170/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-01T08:20:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-28T00:41:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"244326052120057494159518864416432436265","date":"2024-09-04T06:15:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-17T09:43:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"231730345390984760657616438679954313853","date":"2024-08-09T14:21:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-07T07:18:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-07T07:15:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-27T17:34:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-24T14:16:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-07-12T15:05:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6634734e-a5b4-473f-8cdd-6ef119fcd58b","owner":[],"postedDate":"August 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":36178374,"name":"Health sciences/Cardiology"},{"id":36178375,"name":"Health sciences/Diseases"},{"id":36178376,"name":"Physical sciences/Mathematics and computing"}],"tags":[],"updatedAt":"2025-03-31T16:04:21+00:00","versionOfRecord":{"articleIdentity":"rs-4731170","link":"https://doi.org/10.1038/s41598-025-93989-0","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-03-25 15:57:18","publishedOnDateReadable":"March 25th, 2025"},"versionCreatedAt":"2024-08-21 07:26:10","video":"","vorDoi":"10.1038/s41598-025-93989-0","vorDoiUrl":"https://doi.org/10.1038/s41598-025-93989-0","workflowStages":[]},"version":"v1","identity":"rs-4731170","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4731170","identity":"rs-4731170","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2024) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
unpaywall
last seen: 2026-05-26T02:00:01.498150+00:00
License: CC-BY-4.0