A Multibody Dynamics Modeling and Optimal Control Framework for Postoperative Gait Prediction in Total Hip Arthroplasty without Kinematic Input

A Multibody Dynamics Modeling and Optimal Control Framework for Postoperative Gait Prediction in Total Hip Arthroplasty without Kinematic Input | 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 A Multibody Dynamics Modeling and Optimal Control Framework for Postoperative Gait Prediction in Total Hip Arthroplasty without Kinematic Input Yanbing Wang, Jianqiao Guo, Hao Tang, Shengxing Fu, Qiang Tian, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9354114/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract To improve the outcomes of total hip arthroplasty (THA), preoperative kinematic measurement of gait motion plays a crucial role in surgical planning. However, the acetabular cup positioning design based on preoperative experimental data cannot account for changes in gait patterns after surgery, while postoperative kinematic data remain unavailable during the preoperative stage. To generate postoperative gait patterns, a predictive framework integrating musculoskeletal multibody dynamics modeling and optimal control theory was proposed in this study. A seven-link biped model, including foot-ground contact constraints, was developed via the approach of discrete mechanics and optimal control for constrained systems (DMOCC). Based on the simulation enforcing asymmetric constraints on the affected and healthy lower limbs, the optimal joint trajectories and ground reaction forces were extracted to estimate the hip joint reaction forces. As a validation, the predicted solution was correlated with the motion tracking data of patients who had undergone THA. The acetabular anteversion was optimized to minimize the possibility of edgeloading. The optimal cup orientation designed in this study fell within the literature-reported safe zone, but the predicted anteversion angle was smaller than the average values estimated from preoperative gait measurements, highlighting the importance of accounting for the alternation of hip movement functions in THA surgical planning. The proposed procedure could improve the compatibility and adaptability of the functional-based surgical plan, thereby enhancing the locomotion outcomes of THA surgery. Gait prediction musculoskeletal multibody dynamics optimal control total hip arthroplasty discrete mechanics and optimal control (DMOCC) Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 11 May, 2026 Reviewers agreed at journal 04 May, 2026 Reviewers invited by journal 29 Apr, 2026 Editor assigned by journal 13 Apr, 2026 Submission checks completed at journal 09 Apr, 2026 First submitted to journal 08 Apr, 2026 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-9354114","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":634882111,"identity":"f0e9a316-cb90-4ca6-82e5-8c45a7d5b355","order_by":0,"name":"Yanbing Wang","email":"","orcid":"","institution":"Beijing Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Yanbing","middleName":"","lastName":"Wang","suffix":""},{"id":634882112,"identity":"6e2d7f26-8882-4463-9370-83d99a0c0ce5","order_by":1,"name":"Jianqiao 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