Visual Search Strategies Predict Throw Accuracy in Elite Wheelchair Curling: An Eye-Tracking and Machine Learning Approach

Visual Search Strategies Predict Throw Accuracy in Elite Wheelchair Curling: An Eye-Tracking and Machine Learning Approach | 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 Visual Search Strategies Predict Throw Accuracy in Elite Wheelchair Curling: An Eye-Tracking and Machine Learning Approach Chao Wang, Wei Du, Hongda Zhao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6868423/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 Visual search plays a critical role in athletic performance, yet its function in adaptive sports such as wheelchair curling remains underexplored. This study investigated how eye movement features predict throw accuracy in elite and novice wheelchair curling athletes. Thirty athletes (15 experts, 15 novices) completed standardized throw accuracy and visual search tasks, during which eye movements were recorded using the EyeLink Portable Duo system. Multiple regression and support vector machine (SVM) models were employed to analyze the relationship between gaze behavior and throw performance. Results showed that expert athletes achieved significantly higher throw accuracy and demonstrated more efficient visual search patterns, including shorter dwell times, faster reaction times, and fewer fixations. Regression analysis identified key eye movement predictors of performance, while the SVM model distinguished between expert and novice groups with 90% classification accuracy and an Area Under the Curve (AUC) of 0.93. These findings confirm a strong link between visual search efficiency and motor performance, suggesting that experienced athletes rely on optimized gaze strategies. The integration of eye-tracking and machine learning offers valuable insights for assessing performance levels and tailoring individualized training approaches in adaptive sports. Health sciences/Diseases Biological sciences/Psychology Wheelchair curling Visual search patterns Para-athletes Machine learning throw accuracy Full Text Additional Declarations No competing interests reported. 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. 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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-6868423","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":474574250,"identity":"caec8b2b-a519-4e7f-ab0b-2b6333fb9335","order_by":0,"name":"Chao Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIie3RMUsDMRTA8YTAueTIekHpZwgETgql91USDjodzoKDKQdxsbjefRHpmCNDl2jXgy6Ci0OH3KQFB+0qmOsomN/4eP/h8QCIor8KKgAIQt2L/JxhQtSJCb3TJRvU4oI25sSEOZfTVtkZUyK8zTZP9u2wnk9AL9h5ut5iBgz0QxVI3NViunIlh40QPHU7fIkUou3j70luqpxDjWSdCVPiZIenyiQoDSXb/TG5lTqTyuLkGTMjRpK+4q9QW3mPLVy22ownRb/P4UpveHamEfCuxLTp6uAt9KHi/qBvJoUl7x/iel4QUnd+CCTfkuzH4PimMOTHNqIoiv65L8RKWQGxbGAEAAAAAElFTkSuQmCC","orcid":"","institution":"Harbin Sport University","correspondingAuthor":true,"prefix":"","firstName":"Chao","middleName":"","lastName":"Wang","suffix":""},{"id":474574251,"identity":"7bca1899-f468-406f-80b2-e6caa2063372","order_by":1,"name":"Wei Du","email":"","orcid":"","institution":"Harbin Sport University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Du","suffix":""},{"id":474574252,"identity":"738ae0a9-0f99-462c-9b7f-55a3fc72768e","order_by":2,"name":"Hongda Zhao","email":"","orcid":"","institution":"Harbin Sport University","correspondingAuthor":false,"prefix":"","firstName":"Hongda","middleName":"","lastName":"Zhao","suffix":""}],"badges":[],"createdAt":"2025-06-11 06:23:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6868423/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6868423/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87315258,"identity":"49deb67a-c7df-4ded-beac-1a9d78a00067","added_by":"auto","created_at":"2025-07-22 15:38:48","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":512620,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptwithauthordetails.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6868423/v1_covered_9410962b-46ae-4a2d-b33f-726a59cd47d2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Visual Search Strategies Predict Throw Accuracy in Elite Wheelchair Curling: An Eye-Tracking and Machine Learning Approach","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Wheelchair curling, Visual search patterns, Para-athletes, Machine learning, throw accuracy","lastPublishedDoi":"10.21203/rs.3.rs-6868423/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6868423/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eVisual search plays a critical role in athletic performance, yet its function in adaptive sports such as wheelchair curling remains underexplored. 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