Validated Multi-Camera Markerless Motion Capture with Real-Time Data Analytics for Gait Stability Assessment

Validated Multi-Camera Markerless Motion Capture with Real-Time Data Analytics for Gait Stability Assessment | 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 Validated Multi-Camera Markerless Motion Capture with Real-Time Data Analytics for Gait Stability Assessment Sajeda Al-Hammouri, Ziao Chen, Nima Toosizadeh, Christopher Arellano, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9347103/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Marker-based motion capture systems provide highly accurate biomechanical measurements, but they are expensive, require reflective marker placement, and are typically limited to controlled laboratory environments. Their reliance on extensive post-processing also restricts real-time clinical applicability. Markerless pose estimation systems offer a more accessible alternative; however, their ability to reliably quantify clinically relevant dynamic gait stability metrics, such as anterior–posterior (AP) and mediolateral (ML) margin of stability (MoS), remains insufficiently validated. This study evaluated a cost-effective, multi-camera, three-dimensional, markerless motion-capture system based on MediaPipe to estimate gait stability. Ten participants walked on a treadmill at a constant speed of 1.1 m/s while data were collected simultaneously using a three-camera synchronized RGB setup and a gold-standard Vicon capture system. Because MoS relies heavily on accurate estimates of center of mass (CoM) motion and joint kinematics, the temporal trajectories of 14 anatomical landmarks were first compared across systems. The markerless system achieved a mean 3D Euclidean RMSE of 2.48 ± 0.69 cm, with median and 95th-percentile errors of 1.98 ± 0.51 cm and 4.09 ± 1.40 cm, respectively. Using a segmental CoM model, AP MoS values were − 19.6 ± 0.46 cm (marker-based) and − 18.6 ± 0.30 cm (markerless), while ML MoS values were 4.2 ± 0.1 cm and 3.9 ± 0.12 cm, respectively. Errors were larger in the AP direction (RMSE = 3.8 cm) than in the ML direction (RMSE = 0.83 cm). Similar trends were observed using pelvic CoM approximation. Paired t -tests showed no statistically significant differences between the two systems ( p > 0.05). These findings suggest that the proposed multi-camera markerless system can reliably estimate whole-body kinematics and gait stability metrics, support scalable clinical assessment of walking stability and fall risk beyond specialized laboratory environments. Health sciences/Anatomy Health sciences/Biomarkers Physical sciences/Engineering Health sciences/Health care Health sciences/Medical research Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 06 May, 2026 Reviewers agreed at journal 05 May, 2026 Reviewers agreed at journal 05 May, 2026 Reviewers invited by journal 04 May, 2026 Editor assigned by journal 24 Apr, 2026 Editor invited by journal 20 Apr, 2026 Submission checks completed at journal 16 Apr, 2026 First submitted to journal 16 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. 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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-9347103","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":637512535,"identity":"c2ce5643-3767-4d15-9e21-4413ab1218d7","order_by":0,"name":"Sajeda Al-Hammouri","email":"","orcid":"","institution":"The University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Sajeda","middleName":"","lastName":"Al-Hammouri","suffix":""},{"id":637512536,"identity":"cfa8ca99-1cbf-461e-9692-e18f5432f1c3","order_by":1,"name":"Ziao Chen","email":"","orcid":"","institution":"The University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Ziao","middleName":"","lastName":"Chen","suffix":""},{"id":637512537,"identity":"c44e23d8-9209-409d-b810-465d69d94bc7","order_by":2,"name":"Nima Toosizadeh","email":"","orcid":"","institution":"Rutgers University","correspondingAuthor":false,"prefix":"","firstName":"Nima","middleName":"","lastName":"Toosizadeh","suffix":""},{"id":637512538,"identity":"e9360f10-e2c2-4ccc-a0ba-5634848a237d","order_by":3,"name":"Christopher Arellano","email":"","orcid":"","institution":"The University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"","lastName":"Arellano","suffix":""},{"id":637512539,"identity":"b142db6b-b50b-47fe-8a3c-903628f5bcef","order_by":4,"name":"Kavan Hazeli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBACCQh1AIiZGw58gPAMiNXC2HBwBslamHmI0SLZfsbwcwHDHXn59sbGw7ZtdvkM7M3bJPBpkebJMZaewfDMsLHnYMPh3LZkywaeY2V4tcgxpCVI8zAcZmyWSARpOWDAIJFjhl8L/7Pk30At9m3yDxsOW4K0yL/Br0VaIvkYyJbEHgnGhsOMYFt48GuRnPH4mDWPweHkGTyJDQd7ziUbsPGkFVvg0yJxPrH5Nk/FYdv57YcPf/hRZmfAz3544w18WiAAOSLYCCsfBaNgFIyCUUAIAAAinEYGAW8ozgAAAABJRU5ErkJggg==","orcid":"","institution":"University of California","correspondingAuthor":true,"prefix":"","firstName":"Kavan","middleName":"","lastName":"Hazeli","suffix":""}],"badges":[],"createdAt":"2026-04-07 15:24:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9347103/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9347103/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109205106,"identity":"3c5eb406-3d9e-4023-8937-9b9e3e212e98","added_by":"auto","created_at":"2026-05-13 15:03:23","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":452121,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptfinal.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9347103/v1_covered_128150ee-c008-4bf5-91f7-f7bde691a880.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Validated Multi-Camera Markerless Motion Capture with Real-Time Data Analytics for Gait Stability Assessment","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"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-9347103/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9347103/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMarker-based motion capture systems provide highly accurate biomechanical measurements, but they are expensive, require reflective marker placement, and are typically limited to controlled laboratory environments. Their reliance on extensive post-processing also restricts real-time clinical applicability. Markerless pose estimation systems offer a more accessible alternative; however, their ability to reliably quantify clinically relevant dynamic gait stability metrics, such as anterior\u0026ndash;posterior (AP) and mediolateral (ML) margin of stability (MoS), remains insufficiently validated. This study evaluated a cost-effective, multi-camera, three-dimensional, markerless motion-capture system based on MediaPipe to estimate gait stability. Ten participants walked on a treadmill at a constant speed of 1.1 m/s while data were collected simultaneously using a three-camera synchronized RGB setup and a gold-standard Vicon capture system. Because MoS relies heavily on accurate estimates of center of mass (CoM) motion and joint kinematics, the temporal trajectories of 14 anatomical landmarks were first compared across systems. The markerless system achieved a mean 3D Euclidean RMSE of 2.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69 cm, with median and 95th-percentile errors of 1.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51 cm and 4.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40 cm, respectively. Using a segmental CoM model, AP MoS values were \u0026minus;\u0026thinsp;19.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46 cm (marker-based) and \u0026minus;\u0026thinsp;18.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30 cm (markerless), while ML MoS values were 4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 cm and 3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12 cm, respectively. Errors were larger in the AP direction (RMSE\u0026thinsp;=\u0026thinsp;3.8 cm) than in the ML direction (RMSE\u0026thinsp;=\u0026thinsp;0.83 cm). Similar trends were observed using pelvic CoM approximation. Paired \u003cem\u003et\u003c/em\u003e-tests showed no statistically significant differences between the two systems (\u003cem\u003ep\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05). These findings suggest that the proposed multi-camera markerless system can reliably estimate whole-body kinematics and gait stability metrics, support scalable clinical assessment of walking stability and fall risk beyond specialized laboratory environments.\u003c/p\u003e","manuscriptTitle":"Validated Multi-Camera Markerless Motion Capture with Real-Time Data Analytics for Gait Stability Assessment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-12 17:22:20","doi":"10.21203/rs.3.rs-9347103/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"80229560001313790934400694304452020517","date":"2026-05-06T07:46:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"288429973204018484302417610550208007805","date":"2026-05-05T17:25:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"288633878966491084752521989038549326279","date":"2026-05-05T07:31:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-04T17:54:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-24T15:54:33+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-20T05:01:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-16T11:50:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-04-16T10:26:29+00:00","index":"","fulltext":""}],"status":"published","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}}],"origin":"","ownerIdentity":"a2b2b898-a823-4724-97bc-c17c3c183908","owner":[],"postedDate":"May 12th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"80229560001313790934400694304452020517","date":"2026-05-06T07:46:14+00:00","index":58,"fulltext":""},{"type":"reviewerAgreed","content":"288429973204018484302417610550208007805","date":"2026-05-05T17:25:58+00:00","index":57,"fulltext":""},{"type":"reviewerAgreed","content":"288633878966491084752521989038549326279","date":"2026-05-05T07:31:30+00:00","index":55,"fulltext":""},{"type":"reviewersInvited","content":"15","date":"2026-05-04T17:54:48+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":67855635,"name":"Health sciences/Anatomy"},{"id":67855636,"name":"Health sciences/Biomarkers"},{"id":67855637,"name":"Physical sciences/Engineering"},{"id":67855638,"name":"Health sciences/Health care"},{"id":67855639,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-05-12T17:22:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-12 17:22:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9347103","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9347103","identity":"rs-9347103","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}