What a Single Electroencephalographic (eeg) Channel Can Tell Us About Alzheimer's Disease Patients With Mild Cognitive Impairment

dc.contributor.author Del Percio, Claudio
dc.contributor.author Lopez, Susanna
dc.contributor.author Noce, Giuseppe
dc.contributor.author Lizio, Roberta
dc.contributor.author Tucci, Federico
dc.contributor.author Soricelli, Andrea
dc.contributor.author Ferri, Raffaele
dc.contributor.author Yener, Görsev
dc.date.accessioned 2023-06-19T20:56:14Z
dc.date.available 2023-06-19T20:56:14Z
dc.date.issued 2023
dc.description.abstract Abnormalities in cortical sources of resting-state eyes closed electroencephalographic (rsEEG) rhythms recorded by hospital settings (10-20 montage) with 19 scalp electrodes characterized Alzheimer's disease (AD) from preclinical to dementia stages. An intriguing rsEEG application is the monitoring and evaluation of AD progression in large populations with few electrodes in low-cost devices. Here we evaluated whether the above-mentioned abnormalities can be observed from fewer scalp electrodes in patients with mild cognitive impairment due to AD (ADMCI). Clinical and rsEEG data acquired in hospital settings (10-20 montage) from 75 ADMCI participants and 70 age-, education-, and sex-matched normal elderly controls (Nold) were available in an Italian-Turkish archive (PDWAVES Consortium; ). Standard spectral fast fourier transform (FFT) analysis of rsEEG data for individual delta, theta, and alpha frequency bands was computed from 6 monopolar scalp electrodes to derive bipolar C3-P3, C4-P4, P3-O1, and P4-O2 markers. The ADMCI group showed increased delta and decreased alpha power density at the C3-P3, C4-P4, P3-O1, and P4-O2 bipolar channels compared to the Nold group. Increased theta power density for ADMCI patients was observed only at the C3-P3 bipolar channel. Best classification accuracy between the ADMCI and Nold individuals reached 81% (area under the receiver operating characteristic curve) using Alpha2/Theta power density computed at the C3-P3 bipolar channel. Standard rsEEG power density computed from six posterior bipolar channels characterized ADMCI status. These results may pave the way toward diffuse clinical applications in health monitoring of dementia using low-cost EEG systems with a strict number of electrodes in lower- and middle-income countries. en_US
dc.description.sponsorship Ministero della Salute; [FP7-IMI] en_US
dc.description.sponsorship The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Ministero della Salute, (grant numberRicercaCorrente). en_US
dc.identifier.doi 10.1177/15500594221125033
dc.identifier.issn 1550-0594
dc.identifier.issn 2169-5202
dc.identifier.scopus 2-s2.0-85142918552
dc.identifier.uri https://doi.org/10.1177/15500594221125033
dc.identifier.uri https://hdl.handle.net/20.500.14365/4694
dc.language.iso en en_US
dc.publisher Sage Publications Inc en_US
dc.relation.ispartof Clinical Eeg and Neuroscience en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject resting state electroencephalographic (rsEEG) rhythms en_US
dc.subject mild cognitive impairment due to Alzheimer's disease (ADMCI) en_US
dc.subject bipolar rsEEG spectral power density en_US
dc.subject classification en_US
dc.subject telehealth applications en_US
dc.subject Alpha-Rhythms en_US
dc.subject Band Power en_US
dc.subject State en_US
dc.subject Abnormalities en_US
dc.subject Synchronization en_US
dc.subject Oscillations en_US
dc.subject Mechanisms en_US
dc.subject Diagnosis en_US
dc.subject Version en_US
dc.title What a Single Electroencephalographic (eeg) Channel Can Tell Us About Alzheimer's Disease Patients With Mild Cognitive Impairment en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Lopez, Susanna/0000-0002-3568-2668
gdc.author.id Güntekin, Bahar/0000-0002-0860-0524
gdc.author.id Yener, Gorsev/0000-0002-7756-4387
gdc.author.institutional
gdc.author.wosid Lopez, Susanna/AAB-9716-2019
gdc.author.wosid Lopez, Susanna/AAD-2365-2020
gdc.author.wosid Yener, Gorsev/B-5142-2018
gdc.author.wosid Güntekin, Bahar/A-4974-2018
gdc.bip.impulseclass C4
gdc.bip.influenceclass C5
gdc.bip.popularityclass C4
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Ekonomi Üniversitesi en_US
gdc.description.departmenttemp [Del Percio, Claudio; Lopez, Susanna; Tucci, Federico; Babiloni, Claudio] Sapienza Univ Rome, Dept Physiol & Pharmacol Vittorio Erspamer, Rome, Italy; [Noce, Giuseppe; Lizio, Roberta; Soricelli, Andrea] IRCCS Synlab SDN, Naples, Italy; [Soricelli, Andrea] Univ Naples Parthenope, Dept Motor Sci & Healthiness, Naples, Italy; [Ferri, Raffaele] Oasi Res Inst IRCCS, Troina, Italy; [Nobili, Flavio; Arnaldi, Dario; Fama, Francesco] IRCCS Osped Policlin San Martino, Clin Neurol, Genoa, Italy; [Nobili, Flavio; Arnaldi, Dario] Univ Genoa, Dipartimento Neurosci Oftalmol Genet Riabil & Sci, Genoa, Italy; [Buttinelli, Carla; Giubilei, Franco] Sapienza Univ Rome, Dept Neurosci Mental Hlth & Sensory Organs, Rome, Italy; [Marizzoni, Moira; Frisoni, Giovanni B.] IRCCS Ist Ctr San Giovanni Dio Fatebenefratelli, Lab Alzheimers Neuroimaging & Epidemiol, Brescia, Italy; en_US
gdc.description.endpage 35 en_US
gdc.description.issue 1 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q2
gdc.description.startpage 21 en_US
gdc.description.volume 54 en_US
gdc.description.wosquality Q3
gdc.identifier.openalex W4309595450
gdc.identifier.pmid 36413420
gdc.identifier.wos WOS:000890567400004
gdc.index.type WoS
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gdc.index.type PubMed
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gdc.oaire.impulse 18.0
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gdc.oaire.keywords Cerebral Cortex
gdc.oaire.keywords Mild cognitive impairment due to Alzheimer's disease (ADMCI)
gdc.oaire.keywords Rest
gdc.oaire.keywords Electroencephalography
gdc.oaire.keywords Mild Cognitive Impairment Due to Alzheimer's Disease (ADMCI)
gdc.oaire.keywords Telehealth applications
gdc.oaire.keywords Classification
gdc.oaire.keywords bipolar rseeg spectral power density; classification; mild cognitive impairment due to alzheimer's disease (admci); resting state electroencephalographic (rseeg) rhythms; telehealth applications
gdc.oaire.keywords Cognitive Dysfunction / diagnosis
gdc.oaire.keywords Resting state electroencephalographic (rsEEG) rhythms
gdc.oaire.keywords 618.97
gdc.oaire.keywords Bipolar rsEEG Spectral Power Density
gdc.oaire.keywords Bipolar rsEEG spectral power density
gdc.oaire.keywords Resting State Electroencephalographic (rsEEG) Rhythms
gdc.oaire.keywords Alzheimer Disease
gdc.oaire.keywords bipolar rsEEG spectral power density; classification; mild cognitive impairment due to Alzheimer's disease (ADMCI); resting state electroencephalographic (rsEEG) rhythms; telehealth applications
gdc.oaire.keywords Humans
gdc.oaire.keywords Cognitive Dysfunction
gdc.oaire.keywords Electroencephalography / methods
gdc.oaire.keywords Telehealth Applications
gdc.oaire.keywords Aged
gdc.oaire.popularity 1.5229586E-8
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 03 medical and health sciences
gdc.oaire.sciencefields 0302 clinical medicine
gdc.openalex.collaboration International
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gdc.opencitations.count 6
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gdc.virtual.author Yener, Görsev
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