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Wavelet Domain for Heart Murmur Detection Dixon Vimalajeewa, BRANI Vidakovic, Chihoon Lee This is a preprint; it has not been peer reviewed by a journal.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. 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