Optimizing Ground Reaction Force Estimation in Gait Analysis Using an IMU Sensor and Kalman Filtering

Optimizing Ground Reaction Force Estimation in Gait Analysis Using an IMU Sensor and Kalman Filtering | 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 Research Article Optimizing Ground Reaction Force Estimation in Gait Analysis Using an IMU Sensor and Kalman Filtering Abu Hena MD Maruf Morshed This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7486023/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 Walking and running may seem simple, but mechanically they place significant stress on the body. Each heel strike generates high-frequency impulse loads, producing sudden and substantial contact forces that travel through the tibiofemoral joint. Understanding these ground reaction forces (GRFs) is vital for studying the development and progression of conditions such as osteoarthritis. Since direct in-vivo measurement of joint contact forces is not possible, computational modeling becomes indispensable. Developing a realistic multiphysics model of the tibiofemoral joint-encompassing bones, cartilage, and synovial fluid-requires accurate GRF data as external boundary conditions to capture joint loading behavior. However, existing methods for obtaining GRFs are largely confined to laboratory settings or demand expensive equipment, underscoring the need for affordable, wearable alternatives. In this work, we propose an IMU-based technique for estimating vertical GRF during gait. A single body-mounted accelerometer is used to capture vertical acceleration data, from which GRF is recovered using a discrete-time Kalman filter with Zero-Velocity Updates (ZUPT) for drift correction. Our simulation demonstrates that, even under strong sensor bias, the Kalman filter reliably reconstructs GRF by dynamically adjusting the estimated accelerometer bias. This allows for accurate force estimation across gait cycles, enabling the integration of wearable sensing into musculoskeletal modeling pipelines. Mechanical Engineering GRF Kalman Filter osteoarthritis musculoskeletal Optimal Estimation Full Text Additional Declarations The authors declare no competing interests. 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. 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-7486023","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":507298732,"identity":"43f499b9-b696-4d48-9fdc-70a0f2569393","order_by":0,"name":"Abu Hena MD Maruf Morshed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYHAC9s9/fvyXQxYxIKSFjYG3h9kYWTURWnjYmBMbiNbCPyM77YEED1v62vYzxh8Y2/7IM7A3b5PAp0XizNntBgYWPLnbzuSYSTC2GRg28Bwrw6uF4XjvBokEHoncbQfS0hiAWhgbJIB68emQP8y7QeIAm0G62flnyUCHGdg3yL/Br8XgeO82yQa2hASzG8kHQA5LbJDgwa/F8MzZzcaMPQcMt914fEwi4ZxxchtPWrEFPi1yN3I3Pmb4cUDe7Hxi84cPZXK2/eyHN97ApwUVJDCAomkUjIJRMApGAcUAACHsSEqdT2TKAAAAAElFTkSuQmCC","orcid":"","institution":"The University of Texas at Arlington","correspondingAuthor":true,"prefix":"","firstName":"Abu","middleName":"Hena MD Maruf","lastName":"Mors","suffix":"MD"}],"badges":[],"createdAt":"2025-08-29 07:32:23","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7486023/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7486023/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90277109,"identity":"a79e8ee3-8c27-41b4-81b3-f4653e2e4cf1","added_by":"auto","created_at":"2025-09-01 03:11:30","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":968397,"visible":true,"origin":"","legend":"","description":"","filename":"OptimizingGroundReactionForceEstimationinGaitAnalysisUsinganIMUSensorandKalmanFiltering.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7486023/v1_covered_846e6b63-ef59-42c8-9afe-118db62ec4f1.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eOptimizing Ground Reaction Force Estimation in Gait Analysis Using an IMU Sensor and Kalman Filtering\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"The University of Texas at Arlington","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":"GRF, Kalman Filter, osteoarthritis, musculoskeletal, Optimal Estimation","lastPublishedDoi":"10.21203/rs.3.rs-7486023/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7486023/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWalking and running may seem simple, but mechanically they place significant stress on the body. Each heel strike generates high-frequency impulse loads, producing sudden and substantial contact forces that travel through the tibiofemoral joint. Understanding these ground reaction forces (GRFs) is vital for studying the development and progression of conditions such as osteoarthritis. Since direct in-vivo measurement of joint contact forces is not possible, computational modeling becomes indispensable.\u003c/p\u003e\n\u003cp\u003eDeveloping a realistic multiphysics model of the tibiofemoral joint-encompassing bones, cartilage, and synovial fluid-requires accurate GRF data as external boundary conditions to capture joint loading behavior. However, existing methods for obtaining GRFs are largely confined to laboratory settings or demand expensive equipment, underscoring the need for affordable, wearable alternatives.\u003c/p\u003e\n\u003cp\u003eIn this work, we propose an IMU-based technique for estimating vertical GRF during gait. A single body-mounted accelerometer is used to capture vertical acceleration data, from which GRF is recovered using a discrete-time Kalman filter with Zero-Velocity Updates (ZUPT) for drift correction. Our simulation demonstrates that, even under strong sensor bias, the Kalman filter reliably reconstructs GRF by dynamically adjusting the estimated accelerometer bias. This allows for accurate force estimation across gait cycles, enabling the integration of wearable sensing into musculoskeletal modeling pipelines.\u003c/p\u003e","manuscriptTitle":"Optimizing Ground Reaction Force Estimation in Gait Analysis Using an IMU Sensor and Kalman Filtering","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-01 03:03:22","doi":"10.21203/rs.3.rs-7486023/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"10b5e70b-76cd-4c06-8632-711363283e0c","owner":[],"postedDate":"September 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53884619,"name":"Mechanical Engineering"}],"tags":[],"updatedAt":"2025-09-01T03:03:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-01 03:03:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7486023","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7486023","identity":"rs-7486023","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}