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dc.contributor.authorCisnal de la Rica, Ana
dc.contributor.authorGordaliza Pastor, Paula
dc.contributor.authorPérez Turiel, Javier 
dc.contributor.authorFraile Marinero, Juan Carlos 
dc.date.accessioned2023-12-13T08:52:45Z
dc.date.available2023-12-13T08:52:45Z
dc.date.issued2023
dc.identifier.citationSensors, 2023, Vol. 23, Nº. 4, 2048es
dc.identifier.issn1424-8220es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/63594
dc.descriptionProducción Científicaes
dc.description.abstractThe effectiveness of EMG biofeedback with neurorehabilitation robotic platforms has not been previously addressed. The present work evaluates the influence of an EMG-based visual biofeedback on the user performance when performing EMG-driven bilateral exercises with a robotic hand exoskeleton. Eighteen healthy subjects were asked to perform 1-min randomly generated sequences of hand gestures (rest, open and close) in four different conditions resulting from the combination of using or not (1) EMG-based visual biofeedback and (2) kinesthetic feedback from the exoskeleton movement. The user performance in each test was measured by computing similarity between the target gestures and the recognized user gestures using the L2 distance. Statistically significant differences in the subject performance were found in the type of provided feedback (p-value 0.0124). Pairwise comparisons showed that the L2 distance was statistically significantly lower when only EMG-based visual feedback was present (2.89 ± 0.71) than with the presence of the kinesthetic feedback alone (3.43 ± 0.75, p-value = 0.0412) or the combination of both (3.39 ± 0.70, p-value = 0.0497). Hence, EMG-based visual feedback enables subjects to increase their control over the movement of the robotic platform by assessing their muscle activation in real time. This type of feedback could benefit patients in learning more quickly how to activate robot functions, increasing their motivation towards rehabilitation.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherMDPIes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectBiofeedbackes
dc.subjectBiorretroalimentaciónes
dc.subjectBiological control systemses
dc.subjectSistemas de control biológicoes
dc.subjectBiomedicinees
dc.subjectElectromyographyes
dc.subjectElectromiografíaes
dc.subjectHuman robot interactiones
dc.subjectRehabilitation technologyes
dc.subjectRoboticses
dc.subjectRobotics in medicinees
dc.subjectRobóticaes
dc.subjectRobotic exoskeletonses
dc.subjectNeuromuscular diseases - Treatmentes
dc.subjectEnfermedades neuromusculares - Tratamientoes
dc.titleInteraction with a hand rehabilitation exoskeleton in EMG-driven bilateral therapy: Influence of visual biofeedback on the users’ performancees
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2023 The authorses
dc.identifier.doi10.3390/s23042048es
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/23/4/2048es
dc.identifier.publicationfirstpage2048es
dc.identifier.publicationissue4es
dc.identifier.publicationtitleSensorses
dc.identifier.publicationvolume23es
dc.peerreviewedSIes
dc.description.projectMinisterio de Ciencia e Innovación - (project RTC2019-007350-1)es
dc.description.projectConsejería de Educación, Fondo Social Europeo, Gobierno Vasco - (BERC 2022-2025) y (project 3KIA (KK-2020/00049)es
dc.description.projectMinisterio de Ciencia, Innovación y Universidades - (BCAM Severo Ochoa: SEV-2017-0718)es
dc.identifier.essn1424-8220es
dc.rightsAtribución 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco32 Ciencias Médicases
dc.subject.unesco6103.08 Rehabilitaciónes
dc.subject.unesco3314 Tecnología Médica


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