Individualized Physiology-Based Digital Twin Model for Sports Performance Prediction : A Reinterpretation of the Margaria-Morton Model

Individualized Physiology-Based Digital Twin Model for Sports Performance Prediction : A Reinterpretation of the Margaria-Morton Model | 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 Individualized Physiology-Based Digital Twin Model for Sports Performance Prediction : A Reinterpretation of the Margaria-Morton Model Alice Boillet, Laurent A. Messonnier, Caroline Cohen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3854200/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Mar, 2024 Read the published version in Scientific Reports → Version 1 posted 8 You are reading this latest preprint version Abstract Performance in many racing sports depends on the ability of the athletes to produce and maintain the highest possible worki.e., the highest power for the duration of the race. To model this energy production in an individualized way, an adaptation anda reinterpretation (including a physiological meaning of parameters) of the three-component Margaria-Morton model wereperformed. The model is applied to the muscles involved in a given task. The introduction of physiological meanings waspossible thanks to the measurement of physiological characteristics for a given athlete. A method for creating a digital twin wastherefore proposed. The twins thus created were validated by comparison with field performance, experimental observations,and literature data. Simulations of record times and 3-minute all-out tests were consistent with experimental data. Consideringthe literature, the model provided good estimates of the time course of muscle metabolite concentrations (e.g., lactate andphosphocreatine). It also simulated the behavior of oxygen kinetics at exercise onset and during recovery. This methodologyhas a wide range of applications, including prediction and optimization of the performance of individually modeled athletes. Biological sciences/Physiology/Metabolism Biological sciences/Biophysics/Bioenergetics Biological sciences/Computational biology and bioinformatics/Computational models Biological sciences/Systems biology/Computer modelling Full Text Additional Declarations No competing interests reported. Supplementary Files MMBoillet20231221Suppl.pdf sample.bbl Cite Share Download PDF Status: Published Journal Publication published 05 Mar, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 14 Feb, 2024 Reviews received at journal 09 Feb, 2024 Reviewers agreed at journal 01 Feb, 2024 Reviewers invited by journal 22 Jan, 2024 Editor assigned by journal 22 Jan, 2024 Editor invited by journal 21 Jan, 2024 Submission checks completed at journal 21 Jan, 2024 First submitted to journal 11 Jan, 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. 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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-3854200","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":268590612,"identity":"9ccfd09b-ff1a-4895-913b-a7482cbbada8","order_by":0,"name":"Alice Boillet","email":"data:image/png;base64,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","orcid":"","institution":"École Polytechnique","correspondingAuthor":true,"prefix":"","firstName":"Alice","middleName":"","lastName":"Boillet","suffix":""},{"id":268590613,"identity":"2de66824-2434-48fa-9659-c7b37c0315d6","order_by":1,"name":"Laurent A. 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