Evaluating different optimization criteria for estimating spine loads and muscle activity when using back-support exoskeletons

Evaluating different optimization criteria for estimating spine loads and muscle activity when using back-support exoskeletons | 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 Evaluating different optimization criteria for estimating spine loads and muscle activity when using back-support exoskeletons Mohamad Behjati Ashtiani, Sunwook Kim, Maury A. Nussbaum This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8166712/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 Purpose We evaluated how back muscle activity, estimated using different optimization criteria in a commercial musculoskeletal modeling system, corresponds to measured activity. We also examined how the choice of optimization criteria influences estimated intervertebral joint forces (IJFs) during symmetric and asymmetric dynamic lowering/lowering tasks performed with and without two types of back-support exoskeletons (BSEs). Methods We simulated dynamic lowering/lifting tasks in the AnyBody Modeling System™ (AMS) using three available optimization criteria: quadratic, cubic, and min/max, across three intervention conditions, including two BSEs and one control (no BSE) condition. We compared estimated muscle activity with normalized electromyography (nEMG) using maximum normalized cross-correlation and root mean squared error. For each simulation, we estimated peak axial compression and anteroposterior shear IJFs at the lumbar L4/L5 level. Results Quadratic and cubic criteria estimated muscle activity with generally stronger associations and smaller error vs. nEMG. Errors were typically larger during lifting than lowering, and associations were weaker with larger errors in asymmetric compared to symmetric tasks. Estimated IJF magnitudes varied with optimization criteria, with min/max producing the largest forces, followed by cubic and quadratic. Despite these differences in estimated force magnitudes, all criteria indicated a comparable relative reduction in IJFs with BSE use (compared to the control) across all conditions. Conclusion While the selection of an optimization criterion affected the estimated magnitude of spinal loads, it did not change the overall finding of BSE effectiveness. The accuracy of muscle activity estimation using the different criteria was also independent of BSE use. Back-Support Exoskeletons Musculoskeletal Modeling AnyBody Modeling System Optimization Criteria Muscle Activity Electromyography 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. 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exoskeletons\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[{"identity":"c82da8c9-2702-4e65-b768-101dca4ff474","identifier":"10.13039/100000001","name":"National Science Foundation","awardNumber":"2202862","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Back-Support Exoskeletons, Musculoskeletal Modeling, AnyBody Modeling System, Optimization Criteria, Muscle Activity, Electromyography","lastPublishedDoi":"10.21203/rs.3.rs-8166712/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8166712/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003ePurpose\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe evaluated how back muscle activity, estimated using different optimization criteria in a commercial musculoskeletal modeling system, corresponds to measured activity. We also examined how the choice of optimization criteria influences estimated intervertebral joint forces (IJFs) during symmetric and asymmetric dynamic lowering/lowering tasks performed with and without two types of back-support exoskeletons (BSEs).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe simulated dynamic lowering/lifting tasks in the AnyBody Modeling System\u0026trade; (AMS) using three available optimization criteria: quadratic, cubic, and min/max, across three intervention conditions, including two BSEs and one control (no BSE) condition. We compared estimated muscle activity with normalized electromyography (nEMG) using maximum normalized cross-correlation and root mean squared error. For each simulation, we estimated peak axial compression and anteroposterior shear IJFs at the lumbar L4/L5 level.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eQuadratic and cubic criteria estimated muscle activity with generally stronger associations and smaller error vs. nEMG. Errors were typically larger during lifting than lowering, and associations were weaker with larger errors in asymmetric compared to symmetric tasks. Estimated IJF magnitudes varied with optimization criteria, with min/max producing the largest forces, followed by cubic and quadratic. Despite these differences in estimated force magnitudes, all criteria indicated a comparable relative reduction in IJFs with BSE use (compared to the control) across all conditions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWhile the selection of an optimization criterion affected the estimated magnitude of spinal loads, it did not change the overall finding of BSE effectiveness. The accuracy of muscle activity estimation using the different criteria was also independent of BSE use.\u003c/p\u003e","manuscriptTitle":"Evaluating different optimization criteria for estimating spine loads and muscle activity when using back-support exoskeletons","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-21 07:48:29","doi":"10.21203/rs.3.rs-8166712/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":"129e55d0-6289-4307-b36a-7d4daed1c744","owner":[],"postedDate":"November 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-21T07:48:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-21 07:48:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8166712","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8166712","identity":"rs-8166712","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}