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A new methodology based on functional principal component analysis tostudy postural stability post-stroke

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A new methodology based on functional principal component analysis tostudy postural stability post-stroke

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dc.contributor.author Sánchez, M.L. es_ES
dc.contributor.author Belda Lois, Juan Manuel es_ES
dc.contributor.author Mena Del Horno, Silvia es_ES
dc.contributor.author Viosca Herrero, Enrique es_ES
dc.contributor.author Igual-Camachoa, C. es_ES
dc.contributor.author Gisbert-Moranta, B. es_ES
dc.date.accessioned 2019-06-09T20:25:43Z
dc.date.available 2019-06-09T20:25:43Z
dc.date.issued 2018 es_ES
dc.identifier.issn 0268-0033 es_ES
dc.identifier.uri http://hdl.handle.net/10251/121860
dc.description.abstract [EN] Background. A major goal in stroke rehabilitation is the establishment of more effective physical therapy techniques to recover postural stability. Functional Principal Component Analysis provides greater insight into recovery trends. However, when missing values exist, obtaining functional data presents some difficulties. The purpose of this study was to reveal an alternative technique for obtaining the Functional Principal Components without requiring the conversion to functional data beforehand and to investigate this methodology to determine the effect of specific physical therapy techniques in balance recovery trends in elderly subjects with hemiplegia post-stroke. Methods: A randomized controlled pilot trial was developed. Thirty inpatients post-stroke were included. Control and target groups were treated with the same conventional physical therapy protocol based on functional criteria, but specific techniques were added to the target group depending on the subjects' functional level. Postural stability during standing was quantified by posturography. The assessments were performed once a month from the moment the participants were able to stand up to six months post-stroke. Findings: The target group showed a significant improvement in postural control recovery trend six months after stroke that was not present in the control group. Some of the assessed parameters revealed significant differences between treatment groups (P < 0.05). Interpretation: The proposed methodology allows Functional Principal Component Analysis to be performed when data is scarce. Moreover, it allowed the dynamics of recovery of two different treatment groups to be determined, showing that the techniques added in the target group increased postural stability compared to the base protocol. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Clinical Biomechanics es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Functional Principal Component Analysis es_ES
dc.subject Stroke es_ES
dc.subject Postural stability es_ES
dc.subject Posturography es_ES
dc.subject Romberg es_ES
dc.subject.classification INGENIERIA MECANICA es_ES
dc.title A new methodology based on functional principal component analysis tostudy postural stability post-stroke es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.clinbiomech.2018.05.003 es_ES
dc.rights.accessRights Abierto es_ES
dc.date.embargoEndDate 2019-07-01 es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Mecánica y de Materiales - Departament d'Enginyeria Mecànica i de Materials es_ES
dc.description.bibliographicCitation Sánchez, M.; Belda Lois, JM.; Mena Del Horno, S.; Viosca Herrero, E.; Igual-Camachoa, C.; Gisbert-Moranta, B. (2018). A new methodology based on functional principal component analysis tostudy postural stability post-stroke. Clinical Biomechanics. 56:18-26. https://doi.org/10.1016/j.clinbiomech.2018.05.003 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.clinbiomech.2018.05.003 es_ES
dc.description.upvformatpinicio 18 es_ES
dc.description.upvformatpfin 26 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 56 es_ES
dc.identifier.pmid 29775954
dc.relation.pasarela S\384780 es_ES


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