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dc.contributor.authorRosa Steinz, Ramón de la 
dc.contributor.authorAlonso Alonso, Alonso 
dc.contributor.authorCarrera González, Albano
dc.contributor.authorDurán Barroso, Ramón José 
dc.contributor.authorFernández Reguero, Patricia 
dc.date.accessioned2022-11-30T11:12:49Z
dc.date.available2022-11-30T11:12:49Z
dc.date.issued2010
dc.identifier.citationSensors, 2010, vol. 10, n. 12, p. 11100-11125es
dc.identifier.issn1424-8220es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/57541
dc.descriptionProducción Científicaes
dc.description.abstractThis paper presents the UVa-NTS (University of Valladolid Neuromuscular Training System), a multifunction and portable Neuromuscular Training System. The UVa-NTS is designed to analyze the voluntary control of severe neuromotor handicapped patients, their interactive response, and their adaptation to neuromuscular interface systems, such as neural prostheses or domotic applications. Thus, it is an excellent tool to evaluate the residual muscle capabilities in the handicapped. The UVa-NTS is composed of a custom signal conditioning front-end and a computer. The front-end electronics is described thoroughly as well as the overall features of the custom software implementation. The software system is composed of a set of graphical training tools and a processing core. The UVa-NTS works with two classes of neuromuscular signals: the classic myoelectric signals (MES) and, as a novelty, the myomechanic signals (MMS). In order to evaluate the performance of the processing core, a complete analysis has been done to classify its efficiency and to check that it fulfils with the real-time constraints. Tests were performed both with healthy and selected impaired subjects. The adaptation was achieved rapidly, applying a predefined protocol for the UVa-NTS set of training tools. Fine voluntary control was demonstrated to be reached with the myoelectric signals. And the UVa-NTS demonstrated to provide a satisfactory voluntary control when applying the myomechanic signals.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherMDPIes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/*
dc.subject.classificationBiological control systemses
dc.subject.classificationTraininges
dc.subject.classificationElectromyographyes
dc.titleMan-machine interface system for neuromuscular training and evaluation based on EMG and MMG signalses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2010 The Author(s)es
dc.identifier.doi10.3390/s101211100es
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/10/12/11100es
dc.identifier.publicationfirstpage11100es
dc.identifier.publicationissue12es
dc.identifier.publicationlastpage11125es
dc.identifier.publicationtitleSensorses
dc.identifier.publicationvolume10es
dc.peerreviewedSIes
dc.identifier.essn1424-8220es
dc.rightsAttribution 3.0 Unported*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco33 Ciencias Tecnológicases
dc.subject.unesco3314 Tecnología Médicaes


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