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Early detection of Parkinson's disease: Systematic analysis of the influence of the eyes on quantitative biomarkers in resting state electroencephalography

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Early detection of Parkinson's disease: Systematic analysis of the influence of the eyes on quantitative biomarkers in resting state electroencephalography

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dc.contributor.author Giménez-Aparisi, Guillem es_ES
dc.contributor.author Guijarro Estelles, Enrique es_ES
dc.contributor.author Chornet-Lurbe, A. es_ES
dc.contributor.author Ballesta-Martinez, S. es_ES
dc.contributor.author Pardo-Hernandez, M. es_ES
dc.contributor.author Ye Lin, Yiyao es_ES
dc.date.accessioned 2024-06-12T18:19:26Z
dc.date.available 2024-06-12T18:19:26Z
dc.date.issued 2023-10 es_ES
dc.identifier.uri http://hdl.handle.net/10251/205101
dc.description.abstract [EN] While resting state electroencephalography (EEG) provides relevant information on pathological changes in Parkinson's disease, most studies focus on the eyes-closed EEG biomarkers. Recent evidence has shown that both eyes-open EEG and reactivity to eyes-opening can also differentiate Parkinson's disease from healthy aging, but no consensus has been reached on a discriminatory capability benchmark. The aim of this study was to determine the resting-state EEG biomarkers suitable for real-time application that can differentiate Parkinson's patients from healthy subjects under both eyes closed and open. For this, we analysed and compared the quantitative EEG an-alyses of 13 early-stage cognitively normal Parkinson's patients with an age and sex-matched healthy group. We found that Parkinson's disease exhibited abnormal excessive theta activity in eyes-closed, which was reflected by a significantly higher relative theta power, a higher time percentage with a frequency peak in the theta band and a reduced alpha/theta ratio, while Parkinson's patients showed a significantly steeper non-oscillatory spectral slope activity than that of healthy subjects. We also found considerably less alpha and beta reactivity to eyes-opening in Parkinson's disease plus a significant moderate correlation between these EEG-biomarkers and the MDS-UPDRS score, used to assesses the clinical symptoms of Parkinson's Disease. Both EEG recordings with the eyes open and reactivity to eyes-opening provided additional information to the eyes-closed condition.We thus strongly recommend that both eyes open and closed be used in clinical practice recording protocols to promote EEG as a complementary non-invasive screening method for the early detection of Parkinson's disease, which would allow clinicians to design patient-oriented treatment and improve the patient's quality of life. es_ES
dc.description.sponsorship This work was supported by the European Union - NextGenerationEU under the Investigo Program (INVEST/2022/67) and Polisabio (Polisabio 2021/A04). Funding for open access charge: CRUE-Universitat Politecnica de Valencia. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Heliyon es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Electroencephalography es_ES
dc.subject QEEG es_ES
dc.subject Parkinson s disease es_ES
dc.subject Resting state es_ES
dc.subject Eyes-opening reactivity es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Early detection of Parkinson's disease: Systematic analysis of the influence of the eyes on quantitative biomarkers in resting state electroencephalography es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.heliyon.2023.e20625 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UNIVERSIDAD POLITECNICA DE VALENCIA//AP2021_04//DETERMINACIÓN DE BIOMARCADOR PARA LA DETECCIÓN PRECOZ DEL DETERIORO COGNITIVO MEDIANTE EL ANÁLISIS DE CONECTIVIDAD CEREBRAL BASADO EN ELECTROENCEFALOGRAFÍA/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GV INNOV.UNI.CIENCIA//INVEST%2F2022%2F67//FORMACION EN ANALISIS DE DATOS E INTELIGENCIA ARTIFICIAL EN SALUD (FADIAS)/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.description.bibliographicCitation Giménez-Aparisi, G.; Guijarro Estelles, E.; Chornet-Lurbe, A.; Ballesta-Martinez, S.; Pardo-Hernandez, M.; Ye Lin, Y. (2023). Early detection of Parkinson's disease: Systematic analysis of the influence of the eyes on quantitative biomarkers in resting state electroencephalography. Heliyon. 9(10). https://doi.org/10.1016/j.heliyon.2023.e20625 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.heliyon.2023.e20625 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 9 es_ES
dc.description.issue 10 es_ES
dc.identifier.eissn 2405-8440 es_ES
dc.identifier.pmid 37829809 es_ES
dc.identifier.pmcid PMC10565694 es_ES
dc.relation.pasarela S\502410 es_ES
dc.contributor.funder GENERALITAT VALENCIANA es_ES
dc.contributor.funder UNIVERSIDAD POLITECNICA DE VALENCIA es_ES
upv.costeAPC 2047,32 es_ES


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