Classification Methods Based on Complexity and Synchronization of Electroencephalography Signals in Alzheimer’s Disease

Electroencephalography (EEG) has long been studied as a potential diagnostic method for Alzheimer's disease (AD). The pathological progression of AD leads to cortical disconnection. These disconnections may manifest as functional connectivity alterations, measured by the degree of synchronizati...

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Autori principali: Sou Nobukawa, Teruya Yamanishi, Shinya Kasakawa, Haruhiko Nishimura, Mitsuru Kikuchi, Tetsuya Takahashi
Natura: Artigo
Lingua:Inglês
Pubblicazione: Frontiers Media S.A. 2020-04-01
Serie:Frontiers in Psychiatry
Soggetti:
Alzheimer’s disease
electroencephalography
complexity, functional connectivity
machine learning
Accesso online:https://www.frontiersin.org/article/10.3389/fpsyt.2020.00255/full
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