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dc.contributor.authorMartínez-Zarzuela, Mario
dc.contributor.authorGonzález Alonso, Javier 
dc.contributor.authorMartín Tapia, Paula
dc.contributor.authorGonzález Ortega, David 
dc.contributor.authorAntón Rodríguez, Miriam 
dc.contributor.authorDíaz Pernas, Francisco Javier 
dc.date.accessioned2025-07-15T09:08:06Z
dc.date.available2025-07-15T09:08:06Z
dc.date.issued2025
dc.identifier.citationExpert Systems with Applications, 2025, vol. 278, p. 127212es
dc.identifier.issn0957-4174es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/76348
dc.descriptionProducción Científicaes
dc.description.abstractThis study presents ME-WARD (Multimodal Ergonomic Workplace Assessment and Risk from Data), a novel system for ergonomic assessment and musculoskeletal risk evaluation that implements the Rapid Upper Limb Assess- ment (RULA) method. ME-WARD is designed to process joint angle data from motion capture systems, including inertial measurement unit (IMU)-based setups, and deep learning human body pose tracking models. The tool’s flexibility enables ergonomic risk assessment using any system capable of reliably measuring joint angles, extending the applicability of RULA beyond proprietary setups. To validate its performance, the tool was tested in an industrial setting during the assembly of conveyor belts, which involved high-risk tasks such as inserting rods and pushing conveyor belt components. The experiments leveraged gold standard IMU systems alongside a state-of-the-art monocular 3D pose estimation system. The results confirmed that ME-WARD produces reliable RULA scores that closely align with IMU-derived metrics for flexion-dominated movements and comparable performance with the monocular system, despite limitations in tracking lateral and rotational motions. This work highlights the potential of integrating multiple motion capture technologies into a unified and accessible ergo- nomic assessment pipeline. By supporting diverse input sources, including low-cost video-based systems, the proposed multimodal approach offers a scalable, cost-effective solution for ergonomic assessments, paving the way for broader adoption in resource-constrained industrial environments.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.classificationBiomechanicses
dc.subject.classificationErgonomicses
dc.subject.classificationIMUes
dc.subject.classificationIndustry 4.0es
dc.subject.classificationComputer visiones
dc.subject.classificationRULAes
dc.titleME-WARD: A multimodal ergonomic analysis tool for musculoskeletal risk assessment from inertial and video data in working placeses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2025 The Author(s)es
dc.identifier.doi10.1016/j.eswa.2025.127212es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0957417425008346es
dc.identifier.publicationfirstpage127212es
dc.identifier.publicationtitleExpert Systems with Applicationses
dc.identifier.publicationvolume278es
dc.peerreviewedSIes
dc.description.projectMinisterio de Ciencia e Innovación [PID2021-124515OA-I00]es
dc.description.projectJunta de Castilla y León - Consejería de Empleo e Industria de Castilla y León (under research project ErgoTwyn [INVESTUN/21/VA/0003])es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco33 Ciencias Tecnológicases


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