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dc.contributor.authorJarque-Bou, Néstor J
dc.contributor.authorVergara, Margarita
dc.contributor.authorSancho-Bru, Joaquin L.
dc.date.accessioned2024-04-19T11:57:23Z
dc.date.available2024-04-19T11:57:23Z
dc.date.issued2024-04-10
dc.identifier.citationJarque-Bou, N.J.; Vergara, M.; Sancho-Bru, J.L. Understanding Forearm Muscle Activity during Everyday Common Grasps: Insights for Rehabilitation, Prosthetic Control, and Human–Machine Interaction. Appl. Sci. 2024, 14, 3190. https://doi.org/10.3390/app14083190ca_CA
dc.identifier.issn2076-3417
dc.identifier.urihttp://hdl.handle.net/10234/206486
dc.description.abstractThe specific role of forearm muscles in the development of activities of daily living (ADL) remains unknown. Consequently, studying forearm muscle activity during the most commonly used grasps in ADL would yield valuable insights for hand function evaluation, rehabilitation, and advancements in prosthetic control. In this study, forearm muscle activity was analyzed in 22 healthy subjects, examining seven representative forearm areas during the performance of seven types of grasps at 50% of maximum effort. A Scheirer–Ray–Hare test revealed significant differences for grasp, spot, and their interaction (α < 0.05), but not for repetition (and its interactions). Specific significant differences between grasps were found in specific spots by means of Bonferroni post hoc analyses, ensuring the possibility to discriminate between grasps, which is key to identifying the person’s intention to perform a particular grasp. The median values ranged from 4.4% to 32.8%, depending on the spot and grasp, with small 95% confidence intervals (0.5% to 5.5%). Cylindrical grasp requires the highest muscle activity among all spots, while lateral pinch demands the least. The findings elucidate the contribution, coordination, and function of each muscle in relation to each grasp, with implications for rehabilitation, prosthetics, and telerobotic and teleoperation systems.ca_CA
dc.format.extent12 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherMDPIca_CA
dc.relation.isPartOfApplied Sciences, 2024, vol. 14, no 8ca_CA
dc.rightsCopyright: © 2024 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 (https://creativecommons.org/licenses/by/4.0/ca_CA
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/ca_CA
dc.subjectelectromyographyca_CA
dc.subjectelectrode placementca_CA
dc.subjectforearm musclesca_CA
dc.subjectmyoelectric prosthesesca_CA
dc.subjectrehabilitationca_CA
dc.subjectteleroboticsca_CA
dc.titleUnderstanding Forearm Muscle Activity during Everyday Common Grasps: Insights for Rehabilitation, Prosthetic Control, and Human–Machine Interactionca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.3390/app14083190
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttps://www.mdpi.com/2076-3417/14/8/3190ca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_CA
project.funder.identifierhttp://dx.doi.org/10.13039/501100011033ca_CA
project.funder.nameMinisterio de Ciencia, Innovación y Universidadesca_CA
project.funder.nameUniversitat Jaume Ica_CA
oaire.awardNumberCIGE/2021/024ca_CA
oaire.awardNumberGACUJIMC/2023/02ca_CA
oaire.awardNumberUJI-A2021-03ca_CA


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Copyright: © 2024 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 (https://creativecommons.org/licenses/by/4.0/
Excepto si se señala otra cosa, la licencia del ítem se describe como: Copyright: © 2024 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 (https://creativecommons.org/licenses/by/4.0/