Diagnosis of Alzheimer’s disease via resting-state EEG: integration of spectrum, complexity, and synchronization signal features

Diagnosis of Alzheimer’s disease via resting-state EEG: integration of spectrum, complexity, and synchronization signal features

BackgroundAlzheimer’s disease (AD) is the most common neurogenerative disorder, making up 70% of total dementia cases with a prevalence of more than 55 million people. Electroencephalogram (EEG) has become a suitable, accurate, and highly sensitive biomarker for the identification and diagnosis of A...

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Dades bibliogràfiques
Autors principals: Xiaowei Zheng, Bozhi Wang, Hao Liu, Wencan Wu, Jiamin Sun, Wei Fang, Rundong Jiang, Yajie Hu, Cheng Jin, Xin Wei, Steve Shyh-Ching Chen
Format: Article
Idioma:English
Publicat: Frontiers Media S.A. 2023-11-01
Col·lecció:Frontiers in Aging Neuroscience
Matèries:
Alzheimer’s disease (AD)
electroencephalogram (EEG)
spectrum
complexity
synchronization
supervised machine learning
Accés en línia:https://www.frontiersin.org/articles/10.3389/fnagi.2023.1288295/full

Internet

https://www.frontiersin.org/articles/10.3389/fnagi.2023.1288295/full

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