Exploring Non-Linear Interactions Between Activity Timing and Sleep: An Explainable Machine Learning Approach

Exploring Non-Linear Interactions Between Activity Timing and Sleep: An Explainable 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 Exploring Non-Linear Interactions Between Activity Timing and Sleep: An Explainable Machine Learning Approach Jihee Choe, Yujin Oh, Chanwoo Park, Young Kim, Changwon Wang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7432580/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Sleep deprivation has a significant impact on health and quality of life, with approximately 30% of adults worldwide suffering from insomnia. Physical activity has been recognized as a promising non-pharmacological intervention method, but the daily association between sleep and physical activity has not been clarified because key factors such as circadian rhythms and activity times have not been considered. Therefore, this study analyzed physical activity by time of day and intensity, and divided participants into circadian rhythm groups to examine the impact of physical activity on sleep on the same day. The results showed that physical activity had a significant influence on sleep efficiency, achieving a high accuracy of 0.8 or higher across all groups. Additionally, through explainable artificial intelligence, the study identified differences in the effects of physical activity by time of day, revealing that low-intensity activity in the evening, 12–15 hours after waking, had the greatest impact across all groups. These findings could serve as an important foundation for developing personalized, non-pharmacological intervention strategies to improve sleep quality. This study demonstrates the potential of explainable machine learning approaches to elucidate the complex relationship between physical activity and sleep, and suggests practical applications for promoting sleep health. Health sciences/Health care Biological sciences/Neuroscience Biological sciences/Physiology Biological sciences/Psychology Social science/Psychology Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 22 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 24 Oct, 2025 Reviews received at journal 20 Oct, 2025 Reviews received at journal 13 Oct, 2025 Reviewers agreed at journal 23 Sep, 2025 Reviewers agreed at journal 16 Sep, 2025 Reviewers agreed at journal 15 Sep, 2025 Reviewers invited by journal 11 Sep, 2025 Editor assigned by journal 11 Sep, 2025 Editor invited by journal 11 Sep, 2025 Submission checks completed at journal 07 Sep, 2025 First submitted to journal 07 Sep, 2025 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-7432580","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":516329654,"identity":"64adf43d-271a-4aa3-8e4a-3cd7799a63a7","order_by":0,"name":"Jihee Choe","email":"","orcid":"","institution":"Soonchunhyang University","correspondingAuthor":false,"prefix":"","firstName":"Jihee","middleName":"","lastName":"Choe","suffix":""},{"id":516329655,"identity":"50ade5aa-d044-4bac-a91a-e047e5a93a24","order_by":1,"name":"Yujin Oh","email":"","orcid":"","institution":"Soonchunhyang University","correspondingAuthor":false,"prefix":"","firstName":"Yujin","middleName":"","lastName":"Oh","suffix":""},{"id":516329656,"identity":"9c659de8-9853-4924-b9fd-05747fc0e266","order_by":2,"name":"Chanwoo Park","email":"","orcid":"","institution":"Soonchunhyang University","correspondingAuthor":false,"prefix":"","firstName":"Chanwoo","middleName":"","lastName":"Park","suffix":""},{"id":516329657,"identity":"a2f8cc84-affb-4811-81a6-6046ef21ae56","order_by":3,"name":"Young Kim","email":"","orcid":"","institution":"Soonchunhyang University","correspondingAuthor":false,"prefix":"","firstName":"Young","middleName":"","lastName":"Kim","suffix":""},{"id":516329658,"identity":"6ebde93e-be8e-414d-8073-c313bdef7e79","order_by":4,"name":"Changwon Wang","email":"","orcid":"","institution":"Soonchunhyang University","correspondingAuthor":false,"prefix":"","firstName":"Changwon","middleName":"","lastName":"Wang","suffix":""},{"id":516329659,"identity":"61516225-80ab-416c-b2f5-6225a445ebb4","order_by":5,"name":"Se Dong Min","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYHACAxDBw8DewMDMAGESq4XnAIlaGBgkEojUIt/evPFxwa9tMuaSzx9+LmCwk2fgOfsAvxVnjhUbz+y7zWM5O8dYegZDsmEDb7sBfi0SOWbSvD23eQxu57Ax8zAwJzDwsxFw2Pw3UC03jz8DaqknrIXhBo+ZNM8PoJYbDGZALYcTGHjb8OswOJNWbMzbANRyBugXHoPjhm08xwg4rP3wxsc8f27bGxw//vAzT0W1PD9PGgGHgQAj3CnAsCLkEyj4Q5yyUTAKRsEoGKEAAMNDO0bUlj2HAAAAAElFTkSuQmCC","orcid":"","institution":"Soonchunhyang University","correspondingAuthor":true,"prefix":"","firstName":"Se","middleName":"Dong","lastName":"Min","suffix":""}],"badges":[],"createdAt":"2025-08-22 08:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7432580/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7432580/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-32036-4","type":"published","date":"2025-12-22T15:58:28+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":99172515,"identity":"26c3aa4f-872c-4ef5-8e5e-78d5c05443a6","added_by":"auto","created_at":"2025-12-29 16:10:46","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1189060,"visible":true,"origin":"","legend":"","description":"","filename":"ExploringNonLinearInteractionsBetweenActivityTimingandSleepAnExplainableMachineLearningApproach.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7432580/v1_covered_6e014925-5f43-44b0-82e4-5fc1d16062d3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring Non-Linear Interactions Between Activity Timing and Sleep: An Explainable Machine Learning Approach","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":"","lastPublishedDoi":"10.21203/rs.3.rs-7432580/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7432580/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Sleep deprivation has a significant impact on health and quality of life, with approximately 30% of adults worldwide suffering from insomnia. 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