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dc.contributor.authorLópez de Ipiña Peña, Miren Karmele
dc.contributor.authorSolé Casals, Jordi
dc.contributor.authorSánchez Méndez, José Ignacio
dc.contributor.authorRomero Garcia, Rafael
dc.contributor.authorFernández Gómez de Segura, Elsa
dc.contributor.authorRequejo Rodríguez, Catalina ORCID
dc.contributor.authorPoologaindran, Anujan
dc.contributor.authorFaúndez Zanuy, Marcos
dc.contributor.authorMartí Massó, José Félix ORCID
dc.contributor.authorBergareche, Alberto
dc.contributor.authorSuckling, John
dc.date.accessioned2021-07-28T08:44:16Z
dc.date.available2021-07-28T08:44:16Z
dc.date.issued2021-06-08
dc.identifier.citationFrontiers in Human Neuroscience 15 : (2021) // Article ID 648573es_ES
dc.identifier.issn1662-5161
dc.identifier.urihttp://hdl.handle.net/10810/52581
dc.description.abstract[EN] Essential tremor (ET) is a highly prevalent neurological disorder characterized by actioninduced tremors involving the hand, voice, head, and/or face. Importantly, hand tremor is present in nearly all forms of ET, resulting in impaired fine motor skills and diminished quality of life. To advance early diagnostic approaches for ET, automated handwriting tasks and magnetic resonance imaging (MRI) offer an opportunity to develop early essential clinical biomarkers. In this study, we present a novel approach for the early clinical diagnosis and monitoring of ET based on integrating handwriting and neuroimaging analysis. We demonstrate how the analysis of fine motor skills, as measured by an automated Archimedes’ spiral task, is correlated with neuroimaging biomarkers for ET. Together, we present a novel modeling approach that can serve as a complementary and promising support tool for the clinical diagnosis of ET and a large range of tremors.es_ES
dc.description.sponsorshipThis work was supported in part by the Universidad del País Vasco/Euskal Herriko Unibertsitatea, the University of Cambridge, PPG 17/51 and GIU 092/19, the Basque government (Saiotek SA-2010/00028, ELEKIN, Engineering and Society and Bioengineering Research Groups, GIC18/136, and ELKARTEK 18/99, 20/81), ‘‘Ministerio de Ciencia e Innovación’’ (SAF2016 77758 R), FEDER funds, DomusVi Foundation (FP18/76), and the government of Gipuzkoa (HELENA, SABRINA, DG18/14- 23, DG19/29, DG20/25 projects). This work is also based upon the work from COST Actions CA18106 and CA15225, supported by COST (European Cooperation in Science and Technology).es_ES
dc.language.isoenges_ES
dc.publisherFrontiers Mediaes_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/SAF2016-77758-Res_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectessential tremores_ES
dc.subjectfine motor skillses_ES
dc.subjectneuroimaginges_ES
dc.subjecthandwritinges_ES
dc.subjectearly managementes_ES
dc.titleAnalysis of Fine Motor Skills in Essential Tremor: Combining Neuroimaging and Handwriting Biomarkers for Early Managementes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holderCopyright © 2021 Lopez-de-Ipina, Solé-Casals, Sánchez-Méndez, Romero-Garcia, Fernandez, Requejo, Poologaindran, Faúndez-Zanuy, Martí-Massó, Bergareche and Suckling. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.es_ES
dc.rights.holderAtribución 3.0 España*
dc.relation.publisherversionhttps://www.frontiersin.org/articles/10.3389/fnhum.2021.648573es_ES
dc.identifier.doi10.3389/fnhum.2021.648573
dc.departamentoesIngeniería de sistemas y automáticaes_ES
dc.departamentoeuSistemen ingeniaritza eta automatikaes_ES


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Copyright © 2021 Lopez-de-Ipina, Solé-Casals, Sánchez-Méndez, Romero-Garcia,
Fernandez, Requejo, Poologaindran, Faúndez-Zanuy, Martí-Massó, Bergareche and
Suckling. This is an open-access article distributed under the terms of the Creative
Commons Attribution License (CC BY). The use, distribution or reproduction in
other forums is permitted, provided the original author(s) and the copyright owner(s)
are credited and that the original publication in this journal is cited, in accordance
with accepted academic practice. No use, distribution or reproduction is permitted
which does not comply with these terms.
Except where otherwise noted, this item's license is described as Copyright © 2021 Lopez-de-Ipina, Solé-Casals, Sánchez-Méndez, Romero-Garcia, Fernandez, Requejo, Poologaindran, Faúndez-Zanuy, Martí-Massó, Bergareche and Suckling. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.