English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/215799
Share/Impact:
Statistics
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE
Exportar a otros formatos:

DC FieldValueLanguage
dc.contributor.authorGarcía Cena, Cecilia E.es_ES
dc.contributor.authorGómez Andrés, Davides_ES
dc.contributor.authorPulido Valdeoliva, Irenees_ES
dc.date.accessioned2020-07-01T13:00:59Z-
dc.date.available2020-07-01T13:00:59Z-
dc.date.issued2020-05-04-
dc.identifier.citationIEEE Access 8: 87201-87213 (2020)es_ES
dc.identifier.urihttp://hdl.handle.net/10261/215799-
dc.description.abstractObjective: This article presents the healthy pattern of eye movements (EM) in 145 healthy volunteers from 20 to 86 years old. Volunteers were classi ed into four groups according to their age. A saccadic paradigm, in horizontal and vertical axes, was performed. We described a pattern behavior in healthy volunteers to demonstrate that it can be used to measure the aging and functionality of the brain. Methods: A gaze-tracker based in video-oculography technology was used. Before EM tests, clinical data were collected, participants performed a cognitive test to discard subtle abnormalities and signed an informed consent form. To demonstrate the relationship between EM and brain aging, a linear or quadratic model was computed and statistical analysis among groups was presented. Conclusion: EM variables could be considered as biomarkers to measure the aging effect and functionality of the brain. Video-oculography is a suitable technique for measuring EM in clinical practice. Signi cance: The ocular healthy pattern as well as the methodology followed in this clinical study, is the base for ongoing studies aiming to incorporate EM analysis at routine practice as markers in early diagnosis for patients with neurodegenerative diseases like Alzheimer's dementia or Parkinson's disease.es_ES
dc.description.sponsorshipThis study was supported by the Science, Innovation and University Minister under Grant SNEO 20151101, Spain Government. The authors are most grateful to all healthy volunteers that participated in this study.es_ES
dc.language.isoenges_ES
dc.publisherInstitute of Electrical and Electronics Engineerses_ES
dc.relation.isversionofPublisher's versiones_ES
dc.rightsopenAccesses_ES
dc.subjectAginges_ES
dc.subjectBiomarkeres_ES
dc.subjectMeasurement techniqueses_ES
dc.subjectStatistical analysises_ES
dc.subjectHealthy patternes_ES
dc.titleMeasurement and analysis of eye movements performance to predict healthy brain aginges_ES
dc.typeartículoes_ES
dc.identifier.doihttp://dx.doi.org/10.1109/ACCESS.2020.2992254-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversionhttp://dx.doi.org/10.1109/ACCESS.2020.2992254es_ES
dc.identifier.e-issn2169-3536-
dc.rights.licensehttps://creativecommons.org/licenses/by/4.0/es_ES
dc.contributor.funderMinisterio de Ciencia, Innovación y Universidades (España)es_ES
dc.relation.csices_ES
oprm.item.hasRevisionno ko 0 false*
dc.contributor.orcidGarcía Cena, Cecilia E. [0000-0002-1067-0564]es_ES
dc.contributor.orcidGómez Andrés, David [0000-0001-5654-7791]es_ES
dc.contributor.orcidPulido Valdeoliva, Irene [0000-0003-0188-2458]es_ES
Appears in Collections:(CAR) Artículos
Files in This Item:
File Description SizeFormat 
Healthy_brain_aging.pdfArtículo principal3,66 MBAdobe PDFThumbnail
View/Open
Show simple item record
 


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.