Afficher la notice abrégée

dc.contributor.authorPérez Valero, Eduardo 
dc.contributor.authorMorillas Gutiérrez, Christian Agustín 
dc.contributor.authorLópez Gordo, Miguel Ángel 
dc.contributor.authorMinguillón Campos, Jesús 
dc.date.accessioned2025-01-09T12:00:19Z
dc.date.available2025-01-09T12:00:19Z
dc.date.issued2023-02-16
dc.identifier.citationPerez-Valero, E., Morillas, C., Lopez-Gordo, M. A., & Minguillon, J. (2023). Supporting the detection of early Alzheimer’s disease with a four-channel EEG analysis. International Journal of Neural Systems, 33(04), 2350021. [DOI: 10.1142/S0129065723500211]es_ES
dc.identifier.urihttps://hdl.handle.net/10481/98793
dc.description.abstractAlzheimer’s disease (AD) is the most prevalent form of dementia. Although there is no current cure, medical treatment can help to control its progression. Hence, early-stage diagnosis is crucial to maximize the living standards of the patients. Biochemical markers and medical imaging in combination with neuropsychological tests represent the most extended diagnosis procedure. However, these techniques require specialized personnel and long processing time. Furthermore, the access to some of these techniques is often limited in crowded healthcare systems and rural areas. In this context, electroencephalography (EEG), a non-invasive technique to obtain endogenous brain information, has been proposed for the diagnosis of early-stage AD. Despite the valuable information provided by clinical EEG and high density montages, these approaches are impractical in conditions such as those described above. Consequently, in this study, we evaluated the feasibly of using a reduced EEG montage with only four channels to detect early-stage AD. For this purpose, we involved eight clinically diagnosed AD patients and eight healthy controls. The results we obtained reveal similar accuracies (p-value=0.66) for the reduced montage (0.86) and a 16-channel montage (0.87). This suggests that a four-channel wearable EEG system could be an effective tool for supporting early-stage AD detection.es_ES
dc.description.sponsorshipProjects B-TIC-352- UGR20 and Excellence Research P21 00084 (Junta de Andalucia)es_ES
dc.description.sponsorshipPGC2018-098813-B-C31, PGC2018- 098813-B-C32, PID2021-128529OA-I00 (MCIN/ AEI/10.13039/501100011033 and by ERDF A way of making Europe)es_ES
dc.description.sponsorshipPostdoctoral Fellowship Programme of Junta de Andalucia (PAIDI 2020)es_ES
dc.language.isoenges_ES
dc.publisherWorld Scientific Publishinges_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectAlzheimer’s diseasees_ES
dc.subjectReduced EEG montagees_ES
dc.subjectWearable EEGes_ES
dc.titleSupporting the Detection of Early Alzheimer’s Disease with a Four-Channel EEG Analysises_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1142/S0129065723500211
dc.type.hasVersionVoRes_ES


Fichier(s) constituant ce document

[PDF]

Ce document figure dans la(les) collection(s) suivante(s)

Afficher la notice abrégée

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Excepté là où spécifié autrement, la license de ce document est décrite en tant que Attribution-NonCommercial-NoDerivatives 4.0 Internacional