Interaction with a hand rehabilitation exoskeleton in EMG-driven bilateral therapy: influence of visual biofeedback on the users' performance

dc.contributor.authorCisnal, Ana
dc.contributor.authorGordaliza Pastor, Paula
dc.contributor.authorPérez Turiel, Javier
dc.contributor.authorFraile, Juan Carlos
dc.contributor.departmentEstadística, Informática y Matemáticases_ES
dc.contributor.departmentEstatistika, Informatika eta Matematikaeu
dc.date.accessioned2024-06-10T15:54:43Z
dc.date.available2024-06-10T15:54:43Z
dc.date.issued2023
dc.date.updated2024-06-10T15:30:51Z
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.en
dc.description.sponsorshipThis research was funded by the Ministry of Science and Innovation through research project RTC2019-007350-1, TICCYL Digital S.L. company, the Regional Ministry of Education for the pre-doctoral recruitment of research staff co-financed by the European Social Fund (ESF), the Basque Government through the BERC 2022-2025 program and Elkartek project 3KIA (KK-2020/00049), and by the Spanish Ministry of Science, Innovation, and Universities (BCAM Severo Ochoa accreditation SEV-2017-0718).en
dc.format.mimetypeapplication/pdfen
dc.identifier.citationCisnal, A., Gordaliza, P., Pérez Turiel, J., Fraile, J. C. (2023) Interaction with a hand rehabilitation exoskeleton in EMG-driven bilateral therapy: Influence of visual biofeedback on the users' performance. Sensors, 23(4), 1-15. https://doi.org/10.3390/s23042048.en
dc.identifier.doi10.3390/s23042048
dc.identifier.issn1424-8220
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/48317
dc.language.isoengen
dc.publisherMDPIen
dc.relation.ispartofSensors 2023, 23(4), 2048en
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI//RTC2019-007350-1/
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI//SEV-2017-0718/
dc.relation.publisherversionhttps://doi.org/10.3390/s23042048
dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectBiofeedbacken
dc.subjectElectromyographyen
dc.subjectHuman–robot interactionen
dc.subjectNeuromotor rehabilitationen
dc.subjectRoboticsen
dc.titleInteraction with a hand rehabilitation exoskeleton in EMG-driven bilateral therapy: influence of visual biofeedback on the users' performanceen
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublication
relation.isAuthorOfPublicationd5bda28d-00d2-4d45-b4db-f7951b9c5b4a
relation.isAuthorOfPublication.latestForDiscoveryd5bda28d-00d2-4d45-b4db-f7951b9c5b4a

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