Détail du document
Identifiant
oai:pubmedcentral.nih.gov:1032...
Sujet
ReviewAuteur
Wijaya, Adi Setiawan, Noor Akhmad Ahmad, Asma Hayati Zakaria, Rahimah Othman, ZahiruddinLangue
enEditeur
AIMS Press
Catégorie
AIMS Neuroscience
Année
2023
Date de référencement
09/10/2023
Mots clés
review research mciRésumé
Mild cognitive impairment (MCI) is often considered a precursor to Alzheimer's disease (AD) and early diagnosis may help improve treatment effectiveness.
To identify accurate MCI biomarkers, researchers have utilized various neuroscience techniques, with electroencephalography (EEG) being a popular choice due to its low cost and better temporal resolution.
In this scoping review, we analyzed 2310 peer-reviewed articles on EEG and MCI between 2012 and 2022 to track the research progress in this field.
Our data analysis involved co-occurrence analysis using VOSviewer and a Patterns, Advances, Gaps, Evidence of Practice, and Research Recommendations (PAGER) framework.
We found that event-related potentials (ERP), EEG, epilepsy, quantitative EEG (QEEG), and EEG-based machine learning were the primary research themes.
The study showed that ERP/EEG, QEEG, and EEG-based machine learning frameworks provide high-accuracy detection of seizure and MCI.
These findings identify the main research themes in EEG and MCI and suggest promising avenues for future research in this field.
Wijaya, Adi,Setiawan, Noor Akhmad,Ahmad, Asma Hayati,Zakaria, Rahimah,Othman, Zahiruddin, 2023, Electroencephalography and mild cognitive impairment research: A scoping review and bibliometric analysis (ScoRBA), AIMS Press
